cognitive functions of critical thinking

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Critical Thinking

Critical thinking is a widely accepted educational goal. Its definition is contested, but the competing definitions can be understood as differing conceptions of the same basic concept: careful thinking directed to a goal. Conceptions differ with respect to the scope of such thinking, the type of goal, the criteria and norms for thinking carefully, and the thinking components on which they focus. Its adoption as an educational goal has been recommended on the basis of respect for students’ autonomy and preparing students for success in life and for democratic citizenship. “Critical thinkers” have the dispositions and abilities that lead them to think critically when appropriate. The abilities can be identified directly; the dispositions indirectly, by considering what factors contribute to or impede exercise of the abilities. Standardized tests have been developed to assess the degree to which a person possesses such dispositions and abilities. Educational intervention has been shown experimentally to improve them, particularly when it includes dialogue, anchored instruction, and mentoring. Controversies have arisen over the generalizability of critical thinking across domains, over alleged bias in critical thinking theories and instruction, and over the relationship of critical thinking to other types of thinking.

2.1 Dewey’s Three Main Examples

2.2 dewey’s other examples, 2.3 further examples, 2.4 non-examples, 3. the definition of critical thinking, 4. its value, 5. the process of thinking critically, 6. components of the process, 7. contributory dispositions and abilities, 8.1 initiating dispositions, 8.2 internal dispositions, 9. critical thinking abilities, 10. required knowledge, 11. educational methods, 12.1 the generalizability of critical thinking, 12.2 bias in critical thinking theory and pedagogy, 12.3 relationship of critical thinking to other types of thinking, other internet resources, related entries.

Use of the term ‘critical thinking’ to describe an educational goal goes back to the American philosopher John Dewey (1910), who more commonly called it ‘reflective thinking’. He defined it as

active, persistent and careful consideration of any belief or supposed form of knowledge in the light of the grounds that support it, and the further conclusions to which it tends. (Dewey 1910: 6; 1933: 9)

and identified a habit of such consideration with a scientific attitude of mind. His lengthy quotations of Francis Bacon, John Locke, and John Stuart Mill indicate that he was not the first person to propose development of a scientific attitude of mind as an educational goal.

In the 1930s, many of the schools that participated in the Eight-Year Study of the Progressive Education Association (Aikin 1942) adopted critical thinking as an educational goal, for whose achievement the study’s Evaluation Staff developed tests (Smith, Tyler, & Evaluation Staff 1942). Glaser (1941) showed experimentally that it was possible to improve the critical thinking of high school students. Bloom’s influential taxonomy of cognitive educational objectives (Bloom et al. 1956) incorporated critical thinking abilities. Ennis (1962) proposed 12 aspects of critical thinking as a basis for research on the teaching and evaluation of critical thinking ability.

Since 1980, an annual international conference in California on critical thinking and educational reform has attracted tens of thousands of educators from all levels of education and from many parts of the world. Also since 1980, the state university system in California has required all undergraduate students to take a critical thinking course. Since 1983, the Association for Informal Logic and Critical Thinking has sponsored sessions in conjunction with the divisional meetings of the American Philosophical Association (APA). In 1987, the APA’s Committee on Pre-College Philosophy commissioned a consensus statement on critical thinking for purposes of educational assessment and instruction (Facione 1990a). Researchers have developed standardized tests of critical thinking abilities and dispositions; for details, see the Supplement on Assessment . Educational jurisdictions around the world now include critical thinking in guidelines for curriculum and assessment.

For details on this history, see the Supplement on History .

2. Examples and Non-Examples

Before considering the definition of critical thinking, it will be helpful to have in mind some examples of critical thinking, as well as some examples of kinds of thinking that would apparently not count as critical thinking.

Dewey (1910: 68–71; 1933: 91–94) takes as paradigms of reflective thinking three class papers of students in which they describe their thinking. The examples range from the everyday to the scientific.

Transit : “The other day, when I was down town on 16th Street, a clock caught my eye. I saw that the hands pointed to 12:20. This suggested that I had an engagement at 124th Street, at one o’clock. I reasoned that as it had taken me an hour to come down on a surface car, I should probably be twenty minutes late if I returned the same way. I might save twenty minutes by a subway express. But was there a station near? If not, I might lose more than twenty minutes in looking for one. Then I thought of the elevated, and I saw there was such a line within two blocks. But where was the station? If it were several blocks above or below the street I was on, I should lose time instead of gaining it. My mind went back to the subway express as quicker than the elevated; furthermore, I remembered that it went nearer than the elevated to the part of 124th Street I wished to reach, so that time would be saved at the end of the journey. I concluded in favor of the subway, and reached my destination by one o’clock.” (Dewey 1910: 68–69; 1933: 91–92)

Ferryboat : “Projecting nearly horizontally from the upper deck of the ferryboat on which I daily cross the river is a long white pole, having a gilded ball at its tip. It suggested a flagpole when I first saw it; its color, shape, and gilded ball agreed with this idea, and these reasons seemed to justify me in this belief. But soon difficulties presented themselves. The pole was nearly horizontal, an unusual position for a flagpole; in the next place, there was no pulley, ring, or cord by which to attach a flag; finally, there were elsewhere on the boat two vertical staffs from which flags were occasionally flown. It seemed probable that the pole was not there for flag-flying.

“I then tried to imagine all possible purposes of the pole, and to consider for which of these it was best suited: (a) Possibly it was an ornament. But as all the ferryboats and even the tugboats carried poles, this hypothesis was rejected. (b) Possibly it was the terminal of a wireless telegraph. But the same considerations made this improbable. Besides, the more natural place for such a terminal would be the highest part of the boat, on top of the pilot house. (c) Its purpose might be to point out the direction in which the boat is moving.

“In support of this conclusion, I discovered that the pole was lower than the pilot house, so that the steersman could easily see it. Moreover, the tip was enough higher than the base, so that, from the pilot’s position, it must appear to project far out in front of the boat. Moreover, the pilot being near the front of the boat, he would need some such guide as to its direction. Tugboats would also need poles for such a purpose. This hypothesis was so much more probable than the others that I accepted it. I formed the conclusion that the pole was set up for the purpose of showing the pilot the direction in which the boat pointed, to enable him to steer correctly.” (Dewey 1910: 69–70; 1933: 92–93)

Bubbles : “In washing tumblers in hot soapsuds and placing them mouth downward on a plate, bubbles appeared on the outside of the mouth of the tumblers and then went inside. Why? The presence of bubbles suggests air, which I note must come from inside the tumbler. I see that the soapy water on the plate prevents escape of the air save as it may be caught in bubbles. But why should air leave the tumbler? There was no substance entering to force it out. It must have expanded. It expands by increase of heat, or by decrease of pressure, or both. Could the air have become heated after the tumbler was taken from the hot suds? Clearly not the air that was already entangled in the water. If heated air was the cause, cold air must have entered in transferring the tumblers from the suds to the plate. I test to see if this supposition is true by taking several more tumblers out. Some I shake so as to make sure of entrapping cold air in them. Some I take out holding mouth downward in order to prevent cold air from entering. Bubbles appear on the outside of every one of the former and on none of the latter. I must be right in my inference. Air from the outside must have been expanded by the heat of the tumbler, which explains the appearance of the bubbles on the outside. But why do they then go inside? Cold contracts. The tumbler cooled and also the air inside it. Tension was removed, and hence bubbles appeared inside. To be sure of this, I test by placing a cup of ice on the tumbler while the bubbles are still forming outside. They soon reverse” (Dewey 1910: 70–71; 1933: 93–94).

Dewey (1910, 1933) sprinkles his book with other examples of critical thinking. We will refer to the following.

Weather : A man on a walk notices that it has suddenly become cool, thinks that it is probably going to rain, looks up and sees a dark cloud obscuring the sun, and quickens his steps (1910: 6–10; 1933: 9–13).

Disorder : A man finds his rooms on his return to them in disorder with his belongings thrown about, thinks at first of burglary as an explanation, then thinks of mischievous children as being an alternative explanation, then looks to see whether valuables are missing, and discovers that they are (1910: 82–83; 1933: 166–168).

Typhoid : A physician diagnosing a patient whose conspicuous symptoms suggest typhoid avoids drawing a conclusion until more data are gathered by questioning the patient and by making tests (1910: 85–86; 1933: 170).

Blur : A moving blur catches our eye in the distance, we ask ourselves whether it is a cloud of whirling dust or a tree moving its branches or a man signaling to us, we think of other traits that should be found on each of those possibilities, and we look and see if those traits are found (1910: 102, 108; 1933: 121, 133).

Suction pump : In thinking about the suction pump, the scientist first notes that it will draw water only to a maximum height of 33 feet at sea level and to a lesser maximum height at higher elevations, selects for attention the differing atmospheric pressure at these elevations, sets up experiments in which the air is removed from a vessel containing water (when suction no longer works) and in which the weight of air at various levels is calculated, compares the results of reasoning about the height to which a given weight of air will allow a suction pump to raise water with the observed maximum height at different elevations, and finally assimilates the suction pump to such apparently different phenomena as the siphon and the rising of a balloon (1910: 150–153; 1933: 195–198).

Diamond : A passenger in a car driving in a diamond lane reserved for vehicles with at least one passenger notices that the diamond marks on the pavement are far apart in some places and close together in others. Why? The driver suggests that the reason may be that the diamond marks are not needed where there is a solid double line separating the diamond lane from the adjoining lane, but are needed when there is a dotted single line permitting crossing into the diamond lane. Further observation confirms that the diamonds are close together when a dotted line separates the diamond lane from its neighbour, but otherwise far apart.

Rash : A woman suddenly develops a very itchy red rash on her throat and upper chest. She recently noticed a mark on the back of her right hand, but was not sure whether the mark was a rash or a scrape. She lies down in bed and thinks about what might be causing the rash and what to do about it. About two weeks before, she began taking blood pressure medication that contained a sulfa drug, and the pharmacist had warned her, in view of a previous allergic reaction to a medication containing a sulfa drug, to be on the alert for an allergic reaction; however, she had been taking the medication for two weeks with no such effect. The day before, she began using a new cream on her neck and upper chest; against the new cream as the cause was mark on the back of her hand, which had not been exposed to the cream. She began taking probiotics about a month before. She also recently started new eye drops, but she supposed that manufacturers of eye drops would be careful not to include allergy-causing components in the medication. The rash might be a heat rash, since she recently was sweating profusely from her upper body. Since she is about to go away on a short vacation, where she would not have access to her usual physician, she decides to keep taking the probiotics and using the new eye drops but to discontinue the blood pressure medication and to switch back to the old cream for her neck and upper chest. She forms a plan to consult her regular physician on her return about the blood pressure medication.

Candidate : Although Dewey included no examples of thinking directed at appraising the arguments of others, such thinking has come to be considered a kind of critical thinking. We find an example of such thinking in the performance task on the Collegiate Learning Assessment (CLA+), which its sponsoring organization describes as

a performance-based assessment that provides a measure of an institution’s contribution to the development of critical-thinking and written communication skills of its students. (Council for Aid to Education 2017)

A sample task posted on its website requires the test-taker to write a report for public distribution evaluating a fictional candidate’s policy proposals and their supporting arguments, using supplied background documents, with a recommendation on whether to endorse the candidate.

Immediate acceptance of an idea that suggests itself as a solution to a problem (e.g., a possible explanation of an event or phenomenon, an action that seems likely to produce a desired result) is “uncritical thinking, the minimum of reflection” (Dewey 1910: 13). On-going suspension of judgment in the light of doubt about a possible solution is not critical thinking (Dewey 1910: 108). Critique driven by a dogmatically held political or religious ideology is not critical thinking; thus Paulo Freire (1968 [1970]) is using the term (e.g., at 1970: 71, 81, 100, 146) in a more politically freighted sense that includes not only reflection but also revolutionary action against oppression. Derivation of a conclusion from given data using an algorithm is not critical thinking.

What is critical thinking? There are many definitions. Ennis (2016) lists 14 philosophically oriented scholarly definitions and three dictionary definitions. Following Rawls (1971), who distinguished his conception of justice from a utilitarian conception but regarded them as rival conceptions of the same concept, Ennis maintains that the 17 definitions are different conceptions of the same concept. Rawls articulated the shared concept of justice as

a characteristic set of principles for assigning basic rights and duties and for determining… the proper distribution of the benefits and burdens of social cooperation. (Rawls 1971: 5)

Bailin et al. (1999b) claim that, if one considers what sorts of thinking an educator would take not to be critical thinking and what sorts to be critical thinking, one can conclude that educators typically understand critical thinking to have at least three features.

• It is done for the purpose of making up one’s mind about what to believe or do.
• The person engaging in the thinking is trying to fulfill standards of adequacy and accuracy appropriate to the thinking.
• The thinking fulfills the relevant standards to some threshold level.

One could sum up the core concept that involves these three features by saying that critical thinking is careful goal-directed thinking. This core concept seems to apply to all the examples of critical thinking described in the previous section. As for the non-examples, their exclusion depends on construing careful thinking as excluding jumping immediately to conclusions, suspending judgment no matter how strong the evidence, reasoning from an unquestioned ideological or religious perspective, and routinely using an algorithm to answer a question.

If the core of critical thinking is careful goal-directed thinking, conceptions of it can vary according to its presumed scope, its presumed goal, one’s criteria and threshold for being careful, and the thinking component on which one focuses. As to its scope, some conceptions (e.g., Dewey 1910, 1933) restrict it to constructive thinking on the basis of one’s own observations and experiments, others (e.g., Ennis 1962; Fisher & Scriven 1997; Johnson 1992) to appraisal of the products of such thinking. Ennis (1991) and Bailin et al. (1999b) take it to cover both construction and appraisal. As to its goal, some conceptions restrict it to forming a judgment (Dewey 1910, 1933; Lipman 1987; Facione 1990a). Others allow for actions as well as beliefs as the end point of a process of critical thinking (Ennis 1991; Bailin et al. 1999b). As to the criteria and threshold for being careful, definitions vary in the term used to indicate that critical thinking satisfies certain norms: “intellectually disciplined” (Scriven & Paul 1987), “reasonable” (Ennis 1991), “skillful” (Lipman 1987), “skilled” (Fisher & Scriven 1997), “careful” (Bailin & Battersby 2009). Some definitions specify these norms, referring variously to “consideration of any belief or supposed form of knowledge in the light of the grounds that support it and the further conclusions to which it tends” (Dewey 1910, 1933); “the methods of logical inquiry and reasoning” (Glaser 1941); “conceptualizing, applying, analyzing, synthesizing, and/or evaluating information gathered from, or generated by, observation, experience, reflection, reasoning, or communication” (Scriven & Paul 1987); the requirement that “it is sensitive to context, relies on criteria, and is self-correcting” (Lipman 1987); “evidential, conceptual, methodological, criteriological, or contextual considerations” (Facione 1990a); and “plus-minus considerations of the product in terms of appropriate standards (or criteria)” (Johnson 1992). Stanovich and Stanovich (2010) propose to ground the concept of critical thinking in the concept of rationality, which they understand as combining epistemic rationality (fitting one’s beliefs to the world) and instrumental rationality (optimizing goal fulfillment); a critical thinker, in their view, is someone with “a propensity to override suboptimal responses from the autonomous mind” (2010: 227). These variant specifications of norms for critical thinking are not necessarily incompatible with one another, and in any case presuppose the core notion of thinking carefully. As to the thinking component singled out, some definitions focus on suspension of judgment during the thinking (Dewey 1910; McPeck 1981), others on inquiry while judgment is suspended (Bailin & Battersby 2009, 2021), others on the resulting judgment (Facione 1990a), and still others on responsiveness to reasons (Siegel 1988). Kuhn (2019) takes critical thinking to be more a dialogic practice of advancing and responding to arguments than an individual ability.

In educational contexts, a definition of critical thinking is a “programmatic definition” (Scheffler 1960: 19). It expresses a practical program for achieving an educational goal. For this purpose, a one-sentence formulaic definition is much less useful than articulation of a critical thinking process, with criteria and standards for the kinds of thinking that the process may involve. The real educational goal is recognition, adoption and implementation by students of those criteria and standards. That adoption and implementation in turn consists in acquiring the knowledge, abilities and dispositions of a critical thinker.

Conceptions of critical thinking generally do not include moral integrity as part of the concept. Dewey, for example, took critical thinking to be the ultimate intellectual goal of education, but distinguished it from the development of social cooperation among school children, which he took to be the central moral goal. Ennis (1996, 2011) added to his previous list of critical thinking dispositions a group of dispositions to care about the dignity and worth of every person, which he described as a “correlative” (1996) disposition without which critical thinking would be less valuable and perhaps harmful. An educational program that aimed at developing critical thinking but not the correlative disposition to care about the dignity and worth of every person, he asserted, “would be deficient and perhaps dangerous” (Ennis 1996: 172).

Dewey thought that education for reflective thinking would be of value to both the individual and society; recognition in educational practice of the kinship to the scientific attitude of children’s native curiosity, fertile imagination and love of experimental inquiry “would make for individual happiness and the reduction of social waste” (Dewey 1910: iii). Schools participating in the Eight-Year Study took development of the habit of reflective thinking and skill in solving problems as a means to leading young people to understand, appreciate and live the democratic way of life characteristic of the United States (Aikin 1942: 17–18, 81). Harvey Siegel (1988: 55–61) has offered four considerations in support of adopting critical thinking as an educational ideal. (1) Respect for persons requires that schools and teachers honour students’ demands for reasons and explanations, deal with students honestly, and recognize the need to confront students’ independent judgment; these requirements concern the manner in which teachers treat students. (2) Education has the task of preparing children to be successful adults, a task that requires development of their self-sufficiency. (3) Education should initiate children into the rational traditions in such fields as history, science and mathematics. (4) Education should prepare children to become democratic citizens, which requires reasoned procedures and critical talents and attitudes. To supplement these considerations, Siegel (1988: 62–90) responds to two objections: the ideology objection that adoption of any educational ideal requires a prior ideological commitment and the indoctrination objection that cultivation of critical thinking cannot escape being a form of indoctrination.

Despite the diversity of our 11 examples, one can recognize a common pattern. Dewey analyzed it as consisting of five phases:

• suggestions , in which the mind leaps forward to a possible solution;
• an intellectualization of the difficulty or perplexity into a problem to be solved, a question for which the answer must be sought;
• the use of one suggestion after another as a leading idea, or hypothesis , to initiate and guide observation and other operations in collection of factual material;
• the mental elaboration of the idea or supposition as an idea or supposition ( reasoning , in the sense on which reasoning is a part, not the whole, of inference); and
• testing the hypothesis by overt or imaginative action. (Dewey 1933: 106–107; italics in original)

The process of reflective thinking consisting of these phases would be preceded by a perplexed, troubled or confused situation and followed by a cleared-up, unified, resolved situation (Dewey 1933: 106). The term ‘phases’ replaced the term ‘steps’ (Dewey 1910: 72), thus removing the earlier suggestion of an invariant sequence. Variants of the above analysis appeared in (Dewey 1916: 177) and (Dewey 1938: 101–119).

The variant formulations indicate the difficulty of giving a single logical analysis of such a varied process. The process of critical thinking may have a spiral pattern, with the problem being redefined in the light of obstacles to solving it as originally formulated. For example, the person in Transit might have concluded that getting to the appointment at the scheduled time was impossible and have reformulated the problem as that of rescheduling the appointment for a mutually convenient time. Further, defining a problem does not always follow after or lead immediately to an idea of a suggested solution. Nor should it do so, as Dewey himself recognized in describing the physician in Typhoid as avoiding any strong preference for this or that conclusion before getting further information (Dewey 1910: 85; 1933: 170). People with a hypothesis in mind, even one to which they have a very weak commitment, have a so-called “confirmation bias” (Nickerson 1998): they are likely to pay attention to evidence that confirms the hypothesis and to ignore evidence that counts against it or for some competing hypothesis. Detectives, intelligence agencies, and investigators of airplane accidents are well advised to gather relevant evidence systematically and to postpone even tentative adoption of an explanatory hypothesis until the collected evidence rules out with the appropriate degree of certainty all but one explanation. Dewey’s analysis of the critical thinking process can be faulted as well for requiring acceptance or rejection of a possible solution to a defined problem, with no allowance for deciding in the light of the available evidence to suspend judgment. Further, given the great variety of kinds of problems for which reflection is appropriate, there is likely to be variation in its component events. Perhaps the best way to conceptualize the critical thinking process is as a checklist whose component events can occur in a variety of orders, selectively, and more than once. These component events might include (1) noticing a difficulty, (2) defining the problem, (3) dividing the problem into manageable sub-problems, (4) formulating a variety of possible solutions to the problem or sub-problem, (5) determining what evidence is relevant to deciding among possible solutions to the problem or sub-problem, (6) devising a plan of systematic observation or experiment that will uncover the relevant evidence, (7) carrying out the plan of systematic observation or experimentation, (8) noting the results of the systematic observation or experiment, (9) gathering relevant testimony and information from others, (10) judging the credibility of testimony and information gathered from others, (11) drawing conclusions from gathered evidence and accepted testimony, and (12) accepting a solution that the evidence adequately supports (cf. Hitchcock 2017: 485).

Checklist conceptions of the process of critical thinking are open to the objection that they are too mechanical and procedural to fit the multi-dimensional and emotionally charged issues for which critical thinking is urgently needed (Paul 1984). For such issues, a more dialectical process is advocated, in which competing relevant world views are identified, their implications explored, and some sort of creative synthesis attempted.

If one considers the critical thinking process illustrated by the 11 examples, one can identify distinct kinds of mental acts and mental states that form part of it. To distinguish, label and briefly characterize these components is a useful preliminary to identifying abilities, skills, dispositions, attitudes, habits and the like that contribute causally to thinking critically. Identifying such abilities and habits is in turn a useful preliminary to setting educational goals. Setting the goals is in its turn a useful preliminary to designing strategies for helping learners to achieve the goals and to designing ways of measuring the extent to which learners have done so. Such measures provide both feedback to learners on their achievement and a basis for experimental research on the effectiveness of various strategies for educating people to think critically. Let us begin, then, by distinguishing the kinds of mental acts and mental events that can occur in a critical thinking process.

• Observing : One notices something in one’s immediate environment (sudden cooling of temperature in Weather , bubbles forming outside a glass and then going inside in Bubbles , a moving blur in the distance in Blur , a rash in Rash ). Or one notes the results of an experiment or systematic observation (valuables missing in Disorder , no suction without air pressure in Suction pump )
• Feeling : One feels puzzled or uncertain about something (how to get to an appointment on time in Transit , why the diamonds vary in spacing in Diamond ). One wants to resolve this perplexity. One feels satisfaction once one has worked out an answer (to take the subway express in Transit , diamonds closer when needed as a warning in Diamond ).
• Wondering : One formulates a question to be addressed (why bubbles form outside a tumbler taken from hot water in Bubbles , how suction pumps work in Suction pump , what caused the rash in Rash ).
• Imagining : One thinks of possible answers (bus or subway or elevated in Transit , flagpole or ornament or wireless communication aid or direction indicator in Ferryboat , allergic reaction or heat rash in Rash ).
• Inferring : One works out what would be the case if a possible answer were assumed (valuables missing if there has been a burglary in Disorder , earlier start to the rash if it is an allergic reaction to a sulfa drug in Rash ). Or one draws a conclusion once sufficient relevant evidence is gathered (take the subway in Transit , burglary in Disorder , discontinue blood pressure medication and new cream in Rash ).
• Knowledge : One uses stored knowledge of the subject-matter to generate possible answers or to infer what would be expected on the assumption of a particular answer (knowledge of a city’s public transit system in Transit , of the requirements for a flagpole in Ferryboat , of Boyle’s law in Bubbles , of allergic reactions in Rash ).
• Experimenting : One designs and carries out an experiment or a systematic observation to find out whether the results deduced from a possible answer will occur (looking at the location of the flagpole in relation to the pilot’s position in Ferryboat , putting an ice cube on top of a tumbler taken from hot water in Bubbles , measuring the height to which a suction pump will draw water at different elevations in Suction pump , noticing the spacing of diamonds when movement to or from a diamond lane is allowed in Diamond ).
• Consulting : One finds a source of information, gets the information from the source, and makes a judgment on whether to accept it. None of our 11 examples include searching for sources of information. In this respect they are unrepresentative, since most people nowadays have almost instant access to information relevant to answering any question, including many of those illustrated by the examples. However, Candidate includes the activities of extracting information from sources and evaluating its credibility.
• Identifying and analyzing arguments : One notices an argument and works out its structure and content as a preliminary to evaluating its strength. This activity is central to Candidate . It is an important part of a critical thinking process in which one surveys arguments for various positions on an issue.
• Judging : One makes a judgment on the basis of accumulated evidence and reasoning, such as the judgment in Ferryboat that the purpose of the pole is to provide direction to the pilot.
• Deciding : One makes a decision on what to do or on what policy to adopt, as in the decision in Transit to take the subway.

By definition, a person who does something voluntarily is both willing and able to do that thing at that time. Both the willingness and the ability contribute causally to the person’s action, in the sense that the voluntary action would not occur if either (or both) of these were lacking. For example, suppose that one is standing with one’s arms at one’s sides and one voluntarily lifts one’s right arm to an extended horizontal position. One would not do so if one were unable to lift one’s arm, if for example one’s right side was paralyzed as the result of a stroke. Nor would one do so if one were unwilling to lift one’s arm, if for example one were participating in a street demonstration at which a white supremacist was urging the crowd to lift their right arm in a Nazi salute and one were unwilling to express support in this way for the racist Nazi ideology. The same analysis applies to a voluntary mental process of thinking critically. It requires both willingness and ability to think critically, including willingness and ability to perform each of the mental acts that compose the process and to coordinate those acts in a sequence that is directed at resolving the initiating perplexity.

Consider willingness first. We can identify causal contributors to willingness to think critically by considering factors that would cause a person who was able to think critically about an issue nevertheless not to do so (Hamby 2014). For each factor, the opposite condition thus contributes causally to willingness to think critically on a particular occasion. For example, people who habitually jump to conclusions without considering alternatives will not think critically about issues that arise, even if they have the required abilities. The contrary condition of willingness to suspend judgment is thus a causal contributor to thinking critically.

Now consider ability. In contrast to the ability to move one’s arm, which can be completely absent because a stroke has left the arm paralyzed, the ability to think critically is a developed ability, whose absence is not a complete absence of ability to think but absence of ability to think well. We can identify the ability to think well directly, in terms of the norms and standards for good thinking. In general, to be able do well the thinking activities that can be components of a critical thinking process, one needs to know the concepts and principles that characterize their good performance, to recognize in particular cases that the concepts and principles apply, and to apply them. The knowledge, recognition and application may be procedural rather than declarative. It may be domain-specific rather than widely applicable, and in either case may need subject-matter knowledge, sometimes of a deep kind.

Reflections of the sort illustrated by the previous two paragraphs have led scholars to identify the knowledge, abilities and dispositions of a “critical thinker”, i.e., someone who thinks critically whenever it is appropriate to do so. We turn now to these three types of causal contributors to thinking critically. We start with dispositions, since arguably these are the most powerful contributors to being a critical thinker, can be fostered at an early stage of a child’s development, and are susceptible to general improvement (Glaser 1941: 175)

8. Critical Thinking Dispositions

Educational researchers use the term ‘dispositions’ broadly for the habits of mind and attitudes that contribute causally to being a critical thinker. Some writers (e.g., Paul & Elder 2006; Hamby 2014; Bailin & Battersby 2016a) propose to use the term ‘virtues’ for this dimension of a critical thinker. The virtues in question, although they are virtues of character, concern the person’s ways of thinking rather than the person’s ways of behaving towards others. They are not moral virtues but intellectual virtues, of the sort articulated by Zagzebski (1996) and discussed by Turri, Alfano, and Greco (2017).

On a realistic conception, thinking dispositions or intellectual virtues are real properties of thinkers. They are general tendencies, propensities, or inclinations to think in particular ways in particular circumstances, and can be genuinely explanatory (Siegel 1999). Sceptics argue that there is no evidence for a specific mental basis for the habits of mind that contribute to thinking critically, and that it is pedagogically misleading to posit such a basis (Bailin et al. 1999a). Whatever their status, critical thinking dispositions need motivation for their initial formation in a child—motivation that may be external or internal. As children develop, the force of habit will gradually become important in sustaining the disposition (Nieto & Valenzuela 2012). Mere force of habit, however, is unlikely to sustain critical thinking dispositions. Critical thinkers must value and enjoy using their knowledge and abilities to think things through for themselves. They must be committed to, and lovers of, inquiry.

A person may have a critical thinking disposition with respect to only some kinds of issues. For example, one could be open-minded about scientific issues but not about religious issues. Similarly, one could be confident in one’s ability to reason about the theological implications of the existence of evil in the world but not in one’s ability to reason about the best design for a guided ballistic missile.

Facione (1990a: 25) divides “affective dispositions” of critical thinking into approaches to life and living in general and approaches to specific issues, questions or problems. Adapting this distinction, one can usefully divide critical thinking dispositions into initiating dispositions (those that contribute causally to starting to think critically about an issue) and internal dispositions (those that contribute causally to doing a good job of thinking critically once one has started). The two categories are not mutually exclusive. For example, open-mindedness, in the sense of willingness to consider alternative points of view to one’s own, is both an initiating and an internal disposition.

Using the strategy of considering factors that would block people with the ability to think critically from doing so, we can identify as initiating dispositions for thinking critically attentiveness, a habit of inquiry, self-confidence, courage, open-mindedness, willingness to suspend judgment, trust in reason, wanting evidence for one’s beliefs, and seeking the truth. We consider briefly what each of these dispositions amounts to, in each case citing sources that acknowledge them.

• Attentiveness : One will not think critically if one fails to recognize an issue that needs to be thought through. For example, the pedestrian in Weather would not have looked up if he had not noticed that the air was suddenly cooler. To be a critical thinker, then, one needs to be habitually attentive to one’s surroundings, noticing not only what one senses but also sources of perplexity in messages received and in one’s own beliefs and attitudes (Facione 1990a: 25; Facione, Facione, & Giancarlo 2001).
• Habit of inquiry : Inquiry is effortful, and one needs an internal push to engage in it. For example, the student in Bubbles could easily have stopped at idle wondering about the cause of the bubbles rather than reasoning to a hypothesis, then designing and executing an experiment to test it. Thus willingness to think critically needs mental energy and initiative. What can supply that energy? Love of inquiry, or perhaps just a habit of inquiry. Hamby (2015) has argued that willingness to inquire is the central critical thinking virtue, one that encompasses all the others. It is recognized as a critical thinking disposition by Dewey (1910: 29; 1933: 35), Glaser (1941: 5), Ennis (1987: 12; 1991: 8), Facione (1990a: 25), Bailin et al. (1999b: 294), Halpern (1998: 452), and Facione, Facione, & Giancarlo (2001).
• Self-confidence : Lack of confidence in one’s abilities can block critical thinking. For example, if the woman in Rash lacked confidence in her ability to figure things out for herself, she might just have assumed that the rash on her chest was the allergic reaction to her medication against which the pharmacist had warned her. Thus willingness to think critically requires confidence in one’s ability to inquire (Facione 1990a: 25; Facione, Facione, & Giancarlo 2001).
• Courage : Fear of thinking for oneself can stop one from doing it. Thus willingness to think critically requires intellectual courage (Paul & Elder 2006: 16).
• Open-mindedness : A dogmatic attitude will impede thinking critically. For example, a person who adheres rigidly to a “pro-choice” position on the issue of the legal status of induced abortion is likely to be unwilling to consider seriously the issue of when in its development an unborn child acquires a moral right to life. Thus willingness to think critically requires open-mindedness, in the sense of a willingness to examine questions to which one already accepts an answer but which further evidence or reasoning might cause one to answer differently (Dewey 1933; Facione 1990a; Ennis 1991; Bailin et al. 1999b; Halpern 1998, Facione, Facione, & Giancarlo 2001). Paul (1981) emphasizes open-mindedness about alternative world-views, and recommends a dialectical approach to integrating such views as central to what he calls “strong sense” critical thinking. In three studies, Haran, Ritov, & Mellers (2013) found that actively open-minded thinking, including “the tendency to weigh new evidence against a favored belief, to spend sufficient time on a problem before giving up, and to consider carefully the opinions of others in forming one’s own”, led study participants to acquire information and thus to make accurate estimations.
• Willingness to suspend judgment : Premature closure on an initial solution will block critical thinking. Thus willingness to think critically requires a willingness to suspend judgment while alternatives are explored (Facione 1990a; Ennis 1991; Halpern 1998).
• Trust in reason : Since distrust in the processes of reasoned inquiry will dissuade one from engaging in it, trust in them is an initiating critical thinking disposition (Facione 1990a, 25; Bailin et al. 1999b: 294; Facione, Facione, & Giancarlo 2001; Paul & Elder 2006). In reaction to an allegedly exclusive emphasis on reason in critical thinking theory and pedagogy, Thayer-Bacon (2000) argues that intuition, imagination, and emotion have important roles to play in an adequate conception of critical thinking that she calls “constructive thinking”. From her point of view, critical thinking requires trust not only in reason but also in intuition, imagination, and emotion.
• Seeking the truth : If one does not care about the truth but is content to stick with one’s initial bias on an issue, then one will not think critically about it. Seeking the truth is thus an initiating critical thinking disposition (Bailin et al. 1999b: 294; Facione, Facione, & Giancarlo 2001). A disposition to seek the truth is implicit in more specific critical thinking dispositions, such as trying to be well-informed, considering seriously points of view other than one’s own, looking for alternatives, suspending judgment when the evidence is insufficient, and adopting a position when the evidence supporting it is sufficient.

Some of the initiating dispositions, such as open-mindedness and willingness to suspend judgment, are also internal critical thinking dispositions, in the sense of mental habits or attitudes that contribute causally to doing a good job of critical thinking once one starts the process. But there are many other internal critical thinking dispositions. Some of them are parasitic on one’s conception of good thinking. For example, it is constitutive of good thinking about an issue to formulate the issue clearly and to maintain focus on it. For this purpose, one needs not only the corresponding ability but also the corresponding disposition. Ennis (1991: 8) describes it as the disposition “to determine and maintain focus on the conclusion or question”, Facione (1990a: 25) as “clarity in stating the question or concern”. Other internal dispositions are motivators to continue or adjust the critical thinking process, such as willingness to persist in a complex task and willingness to abandon nonproductive strategies in an attempt to self-correct (Halpern 1998: 452). For a list of identified internal critical thinking dispositions, see the Supplement on Internal Critical Thinking Dispositions .

Some theorists postulate skills, i.e., acquired abilities, as operative in critical thinking. It is not obvious, however, that a good mental act is the exercise of a generic acquired skill. Inferring an expected time of arrival, as in Transit , has some generic components but also uses non-generic subject-matter knowledge. Bailin et al. (1999a) argue against viewing critical thinking skills as generic and discrete, on the ground that skilled performance at a critical thinking task cannot be separated from knowledge of concepts and from domain-specific principles of good thinking. Talk of skills, they concede, is unproblematic if it means merely that a person with critical thinking skills is capable of intelligent performance.

Despite such scepticism, theorists of critical thinking have listed as general contributors to critical thinking what they variously call abilities (Glaser 1941; Ennis 1962, 1991), skills (Facione 1990a; Halpern 1998) or competencies (Fisher & Scriven 1997). Amalgamating these lists would produce a confusing and chaotic cornucopia of more than 50 possible educational objectives, with only partial overlap among them. It makes sense instead to try to understand the reasons for the multiplicity and diversity, and to make a selection according to one’s own reasons for singling out abilities to be developed in a critical thinking curriculum. Two reasons for diversity among lists of critical thinking abilities are the underlying conception of critical thinking and the envisaged educational level. Appraisal-only conceptions, for example, involve a different suite of abilities than constructive-only conceptions. Some lists, such as those in (Glaser 1941), are put forward as educational objectives for secondary school students, whereas others are proposed as objectives for college students (e.g., Facione 1990a).

The abilities described in the remaining paragraphs of this section emerge from reflection on the general abilities needed to do well the thinking activities identified in section 6 as components of the critical thinking process described in section 5 . The derivation of each collection of abilities is accompanied by citation of sources that list such abilities and of standardized tests that claim to test them.

Observational abilities : Careful and accurate observation sometimes requires specialist expertise and practice, as in the case of observing birds and observing accident scenes. However, there are general abilities of noticing what one’s senses are picking up from one’s environment and of being able to articulate clearly and accurately to oneself and others what one has observed. It helps in exercising them to be able to recognize and take into account factors that make one’s observation less trustworthy, such as prior framing of the situation, inadequate time, deficient senses, poor observation conditions, and the like. It helps as well to be skilled at taking steps to make one’s observation more trustworthy, such as moving closer to get a better look, measuring something three times and taking the average, and checking what one thinks one is observing with someone else who is in a good position to observe it. It also helps to be skilled at recognizing respects in which one’s report of one’s observation involves inference rather than direct observation, so that one can then consider whether the inference is justified. These abilities come into play as well when one thinks about whether and with what degree of confidence to accept an observation report, for example in the study of history or in a criminal investigation or in assessing news reports. Observational abilities show up in some lists of critical thinking abilities (Ennis 1962: 90; Facione 1990a: 16; Ennis 1991: 9). There are items testing a person’s ability to judge the credibility of observation reports in the Cornell Critical Thinking Tests, Levels X and Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005). Norris and King (1983, 1985, 1990a, 1990b) is a test of ability to appraise observation reports.

Emotional abilities : The emotions that drive a critical thinking process are perplexity or puzzlement, a wish to resolve it, and satisfaction at achieving the desired resolution. Children experience these emotions at an early age, without being trained to do so. Education that takes critical thinking as a goal needs only to channel these emotions and to make sure not to stifle them. Collaborative critical thinking benefits from ability to recognize one’s own and others’ emotional commitments and reactions.

Questioning abilities : A critical thinking process needs transformation of an inchoate sense of perplexity into a clear question. Formulating a question well requires not building in questionable assumptions, not prejudging the issue, and using language that in context is unambiguous and precise enough (Ennis 1962: 97; 1991: 9).

Imaginative abilities : Thinking directed at finding the correct causal explanation of a general phenomenon or particular event requires an ability to imagine possible explanations. Thinking about what policy or plan of action to adopt requires generation of options and consideration of possible consequences of each option. Domain knowledge is required for such creative activity, but a general ability to imagine alternatives is helpful and can be nurtured so as to become easier, quicker, more extensive, and deeper (Dewey 1910: 34–39; 1933: 40–47). Facione (1990a) and Halpern (1998) include the ability to imagine alternatives as a critical thinking ability.

Inferential abilities : The ability to draw conclusions from given information, and to recognize with what degree of certainty one’s own or others’ conclusions follow, is universally recognized as a general critical thinking ability. All 11 examples in section 2 of this article include inferences, some from hypotheses or options (as in Transit , Ferryboat and Disorder ), others from something observed (as in Weather and Rash ). None of these inferences is formally valid. Rather, they are licensed by general, sometimes qualified substantive rules of inference (Toulmin 1958) that rest on domain knowledge—that a bus trip takes about the same time in each direction, that the terminal of a wireless telegraph would be located on the highest possible place, that sudden cooling is often followed by rain, that an allergic reaction to a sulfa drug generally shows up soon after one starts taking it. It is a matter of controversy to what extent the specialized ability to deduce conclusions from premisses using formal rules of inference is needed for critical thinking. Dewey (1933) locates logical forms in setting out the products of reflection rather than in the process of reflection. Ennis (1981a), on the other hand, maintains that a liberally-educated person should have the following abilities: to translate natural-language statements into statements using the standard logical operators, to use appropriately the language of necessary and sufficient conditions, to deal with argument forms and arguments containing symbols, to determine whether in virtue of an argument’s form its conclusion follows necessarily from its premisses, to reason with logically complex propositions, and to apply the rules and procedures of deductive logic. Inferential abilities are recognized as critical thinking abilities by Glaser (1941: 6), Facione (1990a: 9), Ennis (1991: 9), Fisher & Scriven (1997: 99, 111), and Halpern (1998: 452). Items testing inferential abilities constitute two of the five subtests of the Watson Glaser Critical Thinking Appraisal (Watson & Glaser 1980a, 1980b, 1994), two of the four sections in the Cornell Critical Thinking Test Level X (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005), three of the seven sections in the Cornell Critical Thinking Test Level Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005), 11 of the 34 items on Forms A and B of the California Critical Thinking Skills Test (Facione 1990b, 1992), and a high but variable proportion of the 25 selected-response questions in the Collegiate Learning Assessment (Council for Aid to Education 2017).

Experimenting abilities : Knowing how to design and execute an experiment is important not just in scientific research but also in everyday life, as in Rash . Dewey devoted a whole chapter of his How We Think (1910: 145–156; 1933: 190–202) to the superiority of experimentation over observation in advancing knowledge. Experimenting abilities come into play at one remove in appraising reports of scientific studies. Skill in designing and executing experiments includes the acknowledged abilities to appraise evidence (Glaser 1941: 6), to carry out experiments and to apply appropriate statistical inference techniques (Facione 1990a: 9), to judge inductions to an explanatory hypothesis (Ennis 1991: 9), and to recognize the need for an adequately large sample size (Halpern 1998). The Cornell Critical Thinking Test Level Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005) includes four items (out of 52) on experimental design. The Collegiate Learning Assessment (Council for Aid to Education 2017) makes room for appraisal of study design in both its performance task and its selected-response questions.

Consulting abilities : Skill at consulting sources of information comes into play when one seeks information to help resolve a problem, as in Candidate . Ability to find and appraise information includes ability to gather and marshal pertinent information (Glaser 1941: 6), to judge whether a statement made by an alleged authority is acceptable (Ennis 1962: 84), to plan a search for desired information (Facione 1990a: 9), and to judge the credibility of a source (Ennis 1991: 9). Ability to judge the credibility of statements is tested by 24 items (out of 76) in the Cornell Critical Thinking Test Level X (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005) and by four items (out of 52) in the Cornell Critical Thinking Test Level Z (Ennis & Millman 1971; Ennis, Millman, & Tomko 1985, 2005). The College Learning Assessment’s performance task requires evaluation of whether information in documents is credible or unreliable (Council for Aid to Education 2017).

Argument analysis abilities : The ability to identify and analyze arguments contributes to the process of surveying arguments on an issue in order to form one’s own reasoned judgment, as in Candidate . The ability to detect and analyze arguments is recognized as a critical thinking skill by Facione (1990a: 7–8), Ennis (1991: 9) and Halpern (1998). Five items (out of 34) on the California Critical Thinking Skills Test (Facione 1990b, 1992) test skill at argument analysis. The College Learning Assessment (Council for Aid to Education 2017) incorporates argument analysis in its selected-response tests of critical reading and evaluation and of critiquing an argument.

Judging skills and deciding skills : Skill at judging and deciding is skill at recognizing what judgment or decision the available evidence and argument supports, and with what degree of confidence. It is thus a component of the inferential skills already discussed.

Lists and tests of critical thinking abilities often include two more abilities: identifying assumptions and constructing and evaluating definitions.

In addition to dispositions and abilities, critical thinking needs knowledge: of critical thinking concepts, of critical thinking principles, and of the subject-matter of the thinking.

We can derive a short list of concepts whose understanding contributes to critical thinking from the critical thinking abilities described in the preceding section. Observational abilities require an understanding of the difference between observation and inference. Questioning abilities require an understanding of the concepts of ambiguity and vagueness. Inferential abilities require an understanding of the difference between conclusive and defeasible inference (traditionally, between deduction and induction), as well as of the difference between necessary and sufficient conditions. Experimenting abilities require an understanding of the concepts of hypothesis, null hypothesis, assumption and prediction, as well as of the concept of statistical significance and of its difference from importance. They also require an understanding of the difference between an experiment and an observational study, and in particular of the difference between a randomized controlled trial, a prospective correlational study and a retrospective (case-control) study. Argument analysis abilities require an understanding of the concepts of argument, premiss, assumption, conclusion and counter-consideration. Additional critical thinking concepts are proposed by Bailin et al. (1999b: 293), Fisher & Scriven (1997: 105–106), Black (2012), and Blair (2021).

According to Glaser (1941: 25), ability to think critically requires knowledge of the methods of logical inquiry and reasoning. If we review the list of abilities in the preceding section, however, we can see that some of them can be acquired and exercised merely through practice, possibly guided in an educational setting, followed by feedback. Searching intelligently for a causal explanation of some phenomenon or event requires that one consider a full range of possible causal contributors, but it seems more important that one implements this principle in one’s practice than that one is able to articulate it. What is important is “operational knowledge” of the standards and principles of good thinking (Bailin et al. 1999b: 291–293). But the development of such critical thinking abilities as designing an experiment or constructing an operational definition can benefit from learning their underlying theory. Further, explicit knowledge of quirks of human thinking seems useful as a cautionary guide. Human memory is not just fallible about details, as people learn from their own experiences of misremembering, but is so malleable that a detailed, clear and vivid recollection of an event can be a total fabrication (Loftus 2017). People seek or interpret evidence in ways that are partial to their existing beliefs and expectations, often unconscious of their “confirmation bias” (Nickerson 1998). Not only are people subject to this and other cognitive biases (Kahneman 2011), of which they are typically unaware, but it may be counter-productive for one to make oneself aware of them and try consciously to counteract them or to counteract social biases such as racial or sexual stereotypes (Kenyon & Beaulac 2014). It is helpful to be aware of these facts and of the superior effectiveness of blocking the operation of biases—for example, by making an immediate record of one’s observations, refraining from forming a preliminary explanatory hypothesis, blind refereeing, double-blind randomized trials, and blind grading of students’ work. It is also helpful to be aware of the prevalence of “noise” (unwanted unsystematic variability of judgments), of how to detect noise (through a noise audit), and of how to reduce noise: make accuracy the goal, think statistically, break a process of arriving at a judgment into independent tasks, resist premature intuitions, in a group get independent judgments first, favour comparative judgments and scales (Kahneman, Sibony, & Sunstein 2021). It is helpful as well to be aware of the concept of “bounded rationality” in decision-making and of the related distinction between “satisficing” and optimizing (Simon 1956; Gigerenzer 2001).

Critical thinking about an issue requires substantive knowledge of the domain to which the issue belongs. Critical thinking abilities are not a magic elixir that can be applied to any issue whatever by somebody who has no knowledge of the facts relevant to exploring that issue. For example, the student in Bubbles needed to know that gases do not penetrate solid objects like a glass, that air expands when heated, that the volume of an enclosed gas varies directly with its temperature and inversely with its pressure, and that hot objects will spontaneously cool down to the ambient temperature of their surroundings unless kept hot by insulation or a source of heat. Critical thinkers thus need a rich fund of subject-matter knowledge relevant to the variety of situations they encounter. This fact is recognized in the inclusion among critical thinking dispositions of a concern to become and remain generally well informed.

Experimental educational interventions, with control groups, have shown that education can improve critical thinking skills and dispositions, as measured by standardized tests. For information about these tests, see the Supplement on Assessment .

What educational methods are most effective at developing the dispositions, abilities and knowledge of a critical thinker? In a comprehensive meta-analysis of experimental and quasi-experimental studies of strategies for teaching students to think critically, Abrami et al. (2015) found that dialogue, anchored instruction, and mentoring each increased the effectiveness of the educational intervention, and that they were most effective when combined. They also found that in these studies a combination of separate instruction in critical thinking with subject-matter instruction in which students are encouraged to think critically was more effective than either by itself. However, the difference was not statistically significant; that is, it might have arisen by chance.

Most of these studies lack the longitudinal follow-up required to determine whether the observed differential improvements in critical thinking abilities or dispositions continue over time, for example until high school or college graduation. For details on studies of methods of developing critical thinking skills and dispositions, see the Supplement on Educational Methods .

12. Controversies

Scholars have denied the generalizability of critical thinking abilities across subject domains, have alleged bias in critical thinking theory and pedagogy, and have investigated the relationship of critical thinking to other kinds of thinking.

McPeck (1981) attacked the thinking skills movement of the 1970s, including the critical thinking movement. He argued that there are no general thinking skills, since thinking is always thinking about some subject-matter. It is futile, he claimed, for schools and colleges to teach thinking as if it were a separate subject. Rather, teachers should lead their pupils to become autonomous thinkers by teaching school subjects in a way that brings out their cognitive structure and that encourages and rewards discussion and argument. As some of his critics (e.g., Paul 1985; Siegel 1985) pointed out, McPeck’s central argument needs elaboration, since it has obvious counter-examples in writing and speaking, for which (up to a certain level of complexity) there are teachable general abilities even though they are always about some subject-matter. To make his argument convincing, McPeck needs to explain how thinking differs from writing and speaking in a way that does not permit useful abstraction of its components from the subject-matters with which it deals. He has not done so. Nevertheless, his position that the dispositions and abilities of a critical thinker are best developed in the context of subject-matter instruction is shared by many theorists of critical thinking, including Dewey (1910, 1933), Glaser (1941), Passmore (1980), Weinstein (1990), Bailin et al. (1999b), and Willingham (2019).

McPeck’s challenge prompted reflection on the extent to which critical thinking is subject-specific. McPeck argued for a strong subject-specificity thesis, according to which it is a conceptual truth that all critical thinking abilities are specific to a subject. (He did not however extend his subject-specificity thesis to critical thinking dispositions. In particular, he took the disposition to suspend judgment in situations of cognitive dissonance to be a general disposition.) Conceptual subject-specificity is subject to obvious counter-examples, such as the general ability to recognize confusion of necessary and sufficient conditions. A more modest thesis, also endorsed by McPeck, is epistemological subject-specificity, according to which the norms of good thinking vary from one field to another. Epistemological subject-specificity clearly holds to a certain extent; for example, the principles in accordance with which one solves a differential equation are quite different from the principles in accordance with which one determines whether a painting is a genuine Picasso. But the thesis suffers, as Ennis (1989) points out, from vagueness of the concept of a field or subject and from the obvious existence of inter-field principles, however broadly the concept of a field is construed. For example, the principles of hypothetico-deductive reasoning hold for all the varied fields in which such reasoning occurs. A third kind of subject-specificity is empirical subject-specificity, according to which as a matter of empirically observable fact a person with the abilities and dispositions of a critical thinker in one area of investigation will not necessarily have them in another area of investigation.

The thesis of empirical subject-specificity raises the general problem of transfer. If critical thinking abilities and dispositions have to be developed independently in each school subject, how are they of any use in dealing with the problems of everyday life and the political and social issues of contemporary society, most of which do not fit into the framework of a traditional school subject? Proponents of empirical subject-specificity tend to argue that transfer is more likely to occur if there is critical thinking instruction in a variety of domains, with explicit attention to dispositions and abilities that cut across domains. But evidence for this claim is scanty. There is a need for well-designed empirical studies that investigate the conditions that make transfer more likely.

It is common ground in debates about the generality or subject-specificity of critical thinking dispositions and abilities that critical thinking about any topic requires background knowledge about the topic. For example, the most sophisticated understanding of the principles of hypothetico-deductive reasoning is of no help unless accompanied by some knowledge of what might be plausible explanations of some phenomenon under investigation.

Critics have objected to bias in the theory, pedagogy and practice of critical thinking. Commentators (e.g., Alston 1995; Ennis 1998) have noted that anyone who takes a position has a bias in the neutral sense of being inclined in one direction rather than others. The critics, however, are objecting to bias in the pejorative sense of an unjustified favoring of certain ways of knowing over others, frequently alleging that the unjustly favoured ways are those of a dominant sex or culture (Bailin 1995). These ways favour:

• reinforcement of egocentric and sociocentric biases over dialectical engagement with opposing world-views (Paul 1981, 1984; Warren 1998)
• distancing from the object of inquiry over closeness to it (Martin 1992; Thayer-Bacon 1992)
• indifference to the situation of others over care for them (Martin 1992)
• orientation to thought over orientation to action (Martin 1992)
• being reasonable over caring to understand people’s ideas (Thayer-Bacon 1993)
• being neutral and objective over being embodied and situated (Thayer-Bacon 1995a)
• doubting over believing (Thayer-Bacon 1995b)
• reason over emotion, imagination and intuition (Thayer-Bacon 2000)
• solitary thinking over collaborative thinking (Thayer-Bacon 2000)
• written and spoken assignments over other forms of expression (Alston 2001)
• attention to written and spoken communications over attention to human problems (Alston 2001)
• winning debates in the public sphere over making and understanding meaning (Alston 2001)

A common thread in this smorgasbord of accusations is dissatisfaction with focusing on the logical analysis and evaluation of reasoning and arguments. While these authors acknowledge that such analysis and evaluation is part of critical thinking and should be part of its conceptualization and pedagogy, they insist that it is only a part. Paul (1981), for example, bemoans the tendency of atomistic teaching of methods of analyzing and evaluating arguments to turn students into more able sophists, adept at finding fault with positions and arguments with which they disagree but even more entrenched in the egocentric and sociocentric biases with which they began. Martin (1992) and Thayer-Bacon (1992) cite with approval the self-reported intimacy with their subject-matter of leading researchers in biology and medicine, an intimacy that conflicts with the distancing allegedly recommended in standard conceptions and pedagogy of critical thinking. Thayer-Bacon (2000) contrasts the embodied and socially embedded learning of her elementary school students in a Montessori school, who used their imagination, intuition and emotions as well as their reason, with conceptions of critical thinking as

thinking that is used to critique arguments, offer justifications, and make judgments about what are the good reasons, or the right answers. (Thayer-Bacon 2000: 127–128)

Alston (2001) reports that her students in a women’s studies class were able to see the flaws in the Cinderella myth that pervades much romantic fiction but in their own romantic relationships still acted as if all failures were the woman’s fault and still accepted the notions of love at first sight and living happily ever after. Students, she writes, should

be able to connect their intellectual critique to a more affective, somatic, and ethical account of making risky choices that have sexist, racist, classist, familial, sexual, or other consequences for themselves and those both near and far… critical thinking that reads arguments, texts, or practices merely on the surface without connections to feeling/desiring/doing or action lacks an ethical depth that should infuse the difference between mere cognitive activity and something we want to call critical thinking. (Alston 2001: 34)

Some critics portray such biases as unfair to women. Thayer-Bacon (1992), for example, has charged modern critical thinking theory with being sexist, on the ground that it separates the self from the object and causes one to lose touch with one’s inner voice, and thus stigmatizes women, who (she asserts) link self to object and listen to their inner voice. Her charge does not imply that women as a group are on average less able than men to analyze and evaluate arguments. Facione (1990c) found no difference by sex in performance on his California Critical Thinking Skills Test. Kuhn (1991: 280–281) found no difference by sex in either the disposition or the competence to engage in argumentative thinking.

The critics propose a variety of remedies for the biases that they allege. In general, they do not propose to eliminate or downplay critical thinking as an educational goal. Rather, they propose to conceptualize critical thinking differently and to change its pedagogy accordingly. Their pedagogical proposals arise logically from their objections. They can be summarized as follows:

• Focus on argument networks with dialectical exchanges reflecting contesting points of view rather than on atomic arguments, so as to develop “strong sense” critical thinking that transcends egocentric and sociocentric biases (Paul 1981, 1984).
• Foster closeness to the subject-matter and feeling connected to others in order to inform a humane democracy (Martin 1992).
• Develop “constructive thinking” as a social activity in a community of physically embodied and socially embedded inquirers with personal voices who value not only reason but also imagination, intuition and emotion (Thayer-Bacon 2000).
• In developing critical thinking in school subjects, treat as important neither skills nor dispositions but opening worlds of meaning (Alston 2001).
• Attend to the development of critical thinking dispositions as well as skills, and adopt the “critical pedagogy” practised and advocated by Freire (1968 [1970]) and hooks (1994) (Dalgleish, Girard, & Davies 2017).

A common thread in these proposals is treatment of critical thinking as a social, interactive, personally engaged activity like that of a quilting bee or a barn-raising (Thayer-Bacon 2000) rather than as an individual, solitary, distanced activity symbolized by Rodin’s The Thinker . One can get a vivid description of education with the former type of goal from the writings of bell hooks (1994, 2010). Critical thinking for her is open-minded dialectical exchange across opposing standpoints and from multiple perspectives, a conception similar to Paul’s “strong sense” critical thinking (Paul 1981). She abandons the structure of domination in the traditional classroom. In an introductory course on black women writers, for example, she assigns students to write an autobiographical paragraph about an early racial memory, then to read it aloud as the others listen, thus affirming the uniqueness and value of each voice and creating a communal awareness of the diversity of the group’s experiences (hooks 1994: 84). Her “engaged pedagogy” is thus similar to the “freedom under guidance” implemented in John Dewey’s Laboratory School of Chicago in the late 1890s and early 1900s. It incorporates the dialogue, anchored instruction, and mentoring that Abrami (2015) found to be most effective in improving critical thinking skills and dispositions.

What is the relationship of critical thinking to problem solving, decision-making, higher-order thinking, creative thinking, and other recognized types of thinking? One’s answer to this question obviously depends on how one defines the terms used in the question. If critical thinking is conceived broadly to cover any careful thinking about any topic for any purpose, then problem solving and decision making will be kinds of critical thinking, if they are done carefully. Historically, ‘critical thinking’ and ‘problem solving’ were two names for the same thing. If critical thinking is conceived more narrowly as consisting solely of appraisal of intellectual products, then it will be disjoint with problem solving and decision making, which are constructive.

Bloom’s taxonomy of educational objectives used the phrase “intellectual abilities and skills” for what had been labeled “critical thinking” by some, “reflective thinking” by Dewey and others, and “problem solving” by still others (Bloom et al. 1956: 38). Thus, the so-called “higher-order thinking skills” at the taxonomy’s top levels of analysis, synthesis and evaluation are just critical thinking skills, although they do not come with general criteria for their assessment (Ennis 1981b). The revised version of Bloom’s taxonomy (Anderson et al. 2001) likewise treats critical thinking as cutting across those types of cognitive process that involve more than remembering (Anderson et al. 2001: 269–270). For details, see the Supplement on History .

As to creative thinking, it overlaps with critical thinking (Bailin 1987, 1988). Thinking about the explanation of some phenomenon or event, as in Ferryboat , requires creative imagination in constructing plausible explanatory hypotheses. Likewise, thinking about a policy question, as in Candidate , requires creativity in coming up with options. Conversely, creativity in any field needs to be balanced by critical appraisal of the draft painting or novel or mathematical theory.

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Cognitive and behavioural flexibility: neural mechanisms and clinical considerations

• Lucina Q. Uddin   ORCID: orcid.org/0000-0003-2278-8962 1 , 2   na1  

Nature Reviews Neuroscience volume  22 ,  pages 167–179 ( 2021 ) Cite this article

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• Cognitive control
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Cognitive and behavioural flexibility permit the appropriate adjustment of thoughts and behaviours in response to changing environmental demands. Brain mechanisms enabling flexibility have been examined using non-invasive neuroimaging and behavioural approaches in humans alongside pharmacological and lesion studies in animals. This work has identified large-scale functional brain networks encompassing lateral and orbital frontoparietal, midcingulo-insular and frontostriatal regions that support flexibility across the lifespan. Flexibility can be compromised in early-life neurodevelopmental disorders, clinical conditions that emerge during adolescence and late-life dementias. We critically evaluate evidence for the enhancement of flexibility through cognitive training, physical activity and bilingual experience.

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Introduction.

The year 2020 will be remembered as a time marked by an unprecedented need for flexibility. In response to the global COVID-19 pandemic, governments, institutions, businesses and individuals made necessary and creative adaptations to cope with an uncertain, rapidly evolving situation 1 . This public health and economic crisis necessitated a great degree of cognitive and behavioural flexibility on the part of individuals adapting to the novel situation with which they were confronted. Responses to the pandemic, ranging from denial and maintenance of the status quo to swift and decisive action to curtail the spread of the causative virus, provided a real-world example of why an optimal level of flexibility is adaptive.

Developmental and lifespan research suggests that flexibility promotes academic achievement, employment success 2 , successful transitioning to adulthood 3 and other optimal life outcomes. Likewise, flexibility in later life can mitigate the effects of ageing on cognitive decline 4 . Flexibility is typically thought to comprise both cognitive and behavioural components. ‘Cognitive flexibility’ is broadly defined as the mental ability to switch between thinking about two different concepts according to the context of a situation 5 . ‘Behavioural flexibility’ refers to the adaptive change of behaviour in response to changing environmental contingencies 6 . The constructs of cognitive flexibility and behavioural flexibility are thus closely intertwined. Since most laboratory tasks used to assess cognitive flexibility require behavioural outputs, they in effect measure aspects of both cognitive and behavioural flexibility. Likewise, it is hard to imagine a flexible behavioural response that is not associated with flexible cognition. The terms ‘cognitive flexibility’ and ‘behavioural flexibility’ are often used interchangeably in the neuroscience literature, and the differentiation in terminology is most likely attributable to the different disciplines (cognitive psychology and behavioural neuroscience, respectively) from which they arose.

Components of flexibility

Cognitive and behavioural flexibility fall under the broader category of executive functions, or processes necessary for the control of goal-directed behaviour 7 . Projects such as the Cognitive Atlas 8 that aim to systematically characterize psychological processes classify flexibility under executive and cognitive control. The question of whether different processes falling under the executive function umbrella can be considered unitary reflections of the same underlying mechanism 9 has been approached using latent variable analysis to examine the extent of unity or diversity of executive functions. In one influential account, executive functions are postulated to comprise three latent variables, described as mental set-shifting (‘shifting’), information updating and monitoring in working memory (‘updating’) and inhibition of prepotent responses (‘inhibition’), that are moderately correlated with one another, yet clearly separable 7 . This framework has helped address the task impurity problem — the issue that because executive functions necessarily manifest themselves by operating on other cognitive processes, any executive task strongly implicates other processes not directly relevant to the target executive function. When we use the term ‘flexibility’, we mean to invoke the aspect of executive function that is typically associated with shifting.

Relatedly, a large and growing literature on flexibility comes from the study of working memory gating, or the process by which relevant contextual information is updated in working memory while distracting information is kept out 10 . Studies investigating neural mechanisms underlying flexibility in working memory are reviewed elsewhere 11 , 12 .

Box  1 describes two classic paradigms in cognitive and behavioural neuroscience that have historically been used to assess flexibility in human and animals. The Wisconsin Card Sorting Test (WCST) is a neuropsychological task developed for humans that measures the ability to infer rules to guide behaviour, create an attentional set based on abstract categories, and switch attention and adjust behaviour with changing task demands 13 . Performance on the WCST is strongly related to shifting (also referred to as ‘attention switching‘ or ‘task switching’), which involves the disengagement of an irrelevant task set and subsequent active engagement of a relevant task set 7 . Reversal learning tasks are often used to study behavioural flexibility in humans as well as rodents and non-human primates 14 . These paradigms assess the ability to respond adaptively in the face of changing stimulus–outcome or response–outcome contingencies 15 . What are referred to as ‘switch trials’ in cognitive flexibility studies are paralleled by ‘reversals’ in behavioural flexibility experiments. Both switches and reversals are points at which shifting from one task or mode of response to another is required. The first aim of this Review is to draw information from these and related neuroscience studies (Box  2 ) to summarize what is known regarding the brain systems and processes underlying cognitive and behavioural flexibility.

In the clinical realm, although diagnosis based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) is still the norm in psychiatry, there has been a push from the US National Institute of Mental Health to shift towards consideration of behaviour dimensionally — that is, along a continuum — rather than categorically. This research domain criteria (RDoC) approach recognizes that dimensions of behaviour can cut across traditional diagnostic categories and urges the integration of multiple levels of information from genomics to neural circuits to behaviour and self-report (for example, using questionnaires that are filled out by the participants themselves) to understand basic dimensions of functioning spanning the full range of human behaviour 16 . This framework may lead to a revised diagnostic nosology that is more firmly grounded in biology 17 . The ‘cognitive systems’ domain of the RDoC matrix includes constructs labelled ‘cognitive control’ and ‘working memory’, which contain subconstructs (goal selection/performance monitoring and flexible updating) that are closely tied to the constructs of cognitive and behavioural flexibility. Consensus regarding which cognitive tasks best probe flexibility can potentially be built by adopting the RDoC framework, which itself is continuously undergoing refinement 18 .

Cognitive and behavioural flexibility are compromised in clinical conditions affecting early life such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD); those that emerge in adolescence, including schizophrenia and mood disorders; and dementias with later-life onset. While many of these conditions share flexibility deficits, the heterogeneous nature, severity and patterns of co-morbid symptoms complicate efforts to develop treatment strategies for enhancing flexibility. The scope of this Review will span these clinical considerations with the goal of identifying common cognitive, pharmacological and neurobiological factors contributing to inflexibility transdiagonostically. Finally, we critically evaluate potential avenues for flexibility training and discuss future directions for translational neuroscience.

Box 1 Experimental paradigms used to assess cognitive and behavioural flexibility in humans and animals

The Wisconsin Card Sorting Test (see the figure, part a ) was first developed in 1948 to assess perseveration, abstract reasoning and set-shifting 142 . The test takes 20–30 minutes to administer as follows: four cards incorporating three stimulus parameters (colour, shape and number of objects) are presented to the participants, who are then asked to sort individual response cards according to different principles. Four different ways of classifying each card are possible, and participants must learn using feedback provided by the experimenter whether a given classification is correct or not. After the participant has correctly sorted several cards according to one learned rule, the experimenter changes the rule without letting the participant know that the rule has been changed. Individuals with frontal lobe damage and children younger than 4 years tend to persist in sorting cards according to previously learned rules and have difficulty flexibly switching to new sorting rules 143 . In reversal learning paradigms (see the figure, part b ) animals form associations between two choices and their reward outcomes initially over a series of trials. After a successful learning period, the choice–outcome mapping is reversed. The ability of the animal to adapt and change behaviour after the first reversal is a measure of behavioural flexibility 144 . Part a is reproduced by special permission of the Publisher, Psychological Assessment Resources, Inc., 16204 North Florida Avenue, Lutz, Florida 33549, from the Wisconsin Card Sorting Test, Copyright 1981, 1993 by PAR, Inc. Further reproduction is prohibited without permission of PAR, Inc. Part b is adapted from Brady, A. M. & Floresco, S. B. Operant procedures for assessing behavioural flexibility in rats. J. Vis. Exp. 96 , e52387, https://doi.org/10.3791/52387 (2015).

Box 2 How is creativity related to flexibility?

Flexible thinking is a critical component of creativity, or the ability to think of new ideas or make new things. Flexibility and creativity have not historically been studied in tandem, despite the obvious parallels between the constructs. While cognitive flexibility is conceptualized as an aspect of executive function and is associated with a rich human neuroimaging literature, creativity has only recently become the topic of cognitive neuroscientific investigations. A query of researchers from academic societies focused on creativity (the Society for the Neuroscience of Creativity and the Society for the Psychology of Aesthetics, Creativity, and the Arts) yielded several cognitive constructs deemed relevant to creativity, including ‘flexibility’, ‘cognitive control’ and ‘ divergent thinking ’ 145 . A meta-analysis of neuroimaging studies of divergent thinking indicates that brain networks underlying creative idea generation are composed of lateral prefrontal, posterior parietal and anterior cingulate cortices, as well as the caudate 146 . A study examining neuroimaging predictors of creativity assessed with visual and verbal tests of divergent thinking, everyday creative behaviour and creative achievement revealed that greater creativity was broadly predicted by grey matter of the inferior frontal gyrus and inferior parietal lobule as well as white matter integrity of the basal ganglia 147 . These findings align with functional activation studies showing inferior frontal gyrus involvement in verbal creative problem-solving 148 . The overlap in lateral frontoparietal and striatal involvement for both flexibility and creativity points to potential shared neural substrates for these related constructs. Future work in creativity could thus benefit from closer integration with the literature on cognitive flexibility.

Neural substrates of flexibility

Cognitive flexibility follows a protracted, inverted U-shaped developmental trajectory from early childhood through adolescence and adulthood, peaking between the second and third decades of life, and declining in late life 19 . Here we will summarize the role of lateral and orbital frontoparietal, midcingulo-insular and frontostriatal functional brain networks in supporting flexibility across the lifespan. The cognitive processes and neural properties contributing to the development of flexibility, its maturation in young adulthood and its decline with ageing will be delineated.

Cognitive flexibility in humans

In studies of the neural basis of cognitive flexibility, participants perform task-switching or set-shifting paradigms while their brain activity is monitored using functional MRI (fMRI) 20 . It is important to keep in mind that laboratory-based measures and neuropsychological tests have high construct validity but may not always converge with real-world flexible behaviours as indexed using self-report or informant-report questionnaires, which typically have greater ecological validity 21 . The Behaviour Rating Inventory of Executive Function (BRIEF) is an assessment available in versions for both children and adults that includes a measure of an individual’s ability to shift, or make transitions, tolerate change, flexibly problem-solve, switch attention and change focus from one topic to another 22 , 23 . Adult participants complete the BRIEF as a self-report, and parents and teachers can complete this assessment to evaluate school-aged children. Test batteries that include assessments of flexibility in children and adults include the WCST, the Dimensional Change Card Sort 24 , the Delis–Kaplan Executive Function System (D-KEFS) 25 , NEPSY-II 26 and the Cambridge Neuropsychological Test Automated Battery Intra–Extra Dimensional Set Shift task 27 .

Cognitive flexibility is difficult to isolate, as it requires the confluence of several aspects of executive function 20 , 28 . Neurosynth is a tool for synthesizing the results of human neuroimaging studies to produce mappings between neural activation patterns and cognitive states using text mining and automated meta-analyses 29 . Entering the terms describing the latent variables comprising executive function into Neurosynth reveals that the brain maps associated with these interrelated cognitive constructs are highly overlapping 7 (Fig.  1a ).

a | Three latent variables that constitute executive function are referred to as ‘shifting (flexibility)’, ‘updating (working memory)’ and ‘inhibition’ 7 . Automated meta-analyses of published functional neuroimaging studies can be conducted with Neurosynth , a Web-based platform that uses text mining to extract activation coordinates from studies reporting on a specific psychological term of interest and machine learning to estimate the likelihood that activation maps are associated with specific psychological terms, thus creating mapping between neural and cognitive states (see ref. 29 for detailed methods). Neurosynth reveals that brain imaging studies including the terms ‘shifting’, ‘updating’ and ‘inhibition’ report highly overlapping patterns of activation in lateral frontoparietal and midcingulo-insular brain regions, underscoring the difficulty of isolating the construct of flexibility from associated executive functions. a | Maps created by first, entering the terms ‘shifting’, ‘updating’ and ‘inhibition’ individually into Neurosynth; second, displaying the ‘uniformity test’ results to view z scores corresponding to the degree to which each voxel in the brain is consistently activated in studies that use each of the selected terms; third, downloading the resulting brain images (with thresholding at a false discovery rate of 0.01) in the form of NIfTi files; and fourth, displaying the brain images using the image viewer MRIcron with the following settings: 2.3 <  z  < 8 (scale); x  = 45 (Montreal Neurological Institute (MNI) coordinate for sagittal slice), y  = 19 (MNI coordinate for coronal slice) and z  = 45 (MNI coordinate for axial slice). The uniformity test map depicts z scores from a one-way ANOVA testing whether the proportion of studies that report activation at a given voxel differs from the rate that would be expected if activations were uniformly distributed throughout grey matter. b | Brain regions supporting executive function and flexibility operate within the context of the broader networks shown in part a . During performance of a flexible item selection task, participants directly engage the inferior frontal junction (IFJ), which influences activity in other lateral frontoparietal and midcingulo-insular regions. ACC, anterior cingulate cortex; AG, angular gurus; AI, anterior insula; dlPFC, dorsolateral prefrontal cortex; IPL, inferior parietal lobule. Part b adapted with permission from ref. 33 , Massachusetts Institute of Technology.

A large body of literature on human functional neuroimaging studies using task-switching and set-shifting paradigms points to a central role for the lateral frontoparietal network (L-FPN) and the midcingulo-insular network (M-CIN) in supporting executive function and cognitive flexibility 20 , 30 . The L-FPN is also referred to as the executive control network and includes lateral prefrontal cortices (PFCs; dorsolateral PFC (dlPFC), ventrolateral PFC and inferior frontal junction (IFJ)), the inferior parietal lobule (IPL), posterior inferior temporal lobes and portions of the midcingulate gyrus. The M-CIN is sometimes referred to as the salience network or the cingulo-opercular network, and includes bilateral anterior insulae (AI), the anterior midcingulate cortex and subcortical nodes, including the amygdala and thalamus 31 .

While whole-brain activation patterns reveal how effortful control and executive functions broadly engage these systems, approaches for estimating task-modulated network connectivity are beginning to reveal how specific experimental manipulations are associated with dynamic relationships among brain regions. For example, one study found that the IFJ is engaged during the updating of task representations, a core aspect of flexibility 32 . During a task requiring flexible selection of items based on different stimulus dimensions, participants initially directly engaged the IFJ, leading to recruitment of other L-FPN and M-CIN regions, including the dlPFC, IPL, anterior midcingulate cortex and AI via functional connections 33 . Considerable individual variability in functional network topography supporting cognitive flexibility was observed, and the strength of functional connectivity between selected brain regions was related to individual differences in task performance (Fig.  1b ). This finding is in line with earlier work demonstrating domain-general task-switching activation in the IFJ 34 , a brain region that exhibits meta-analytic co-activation and resting state functional connectivity with the AI, dlPFC and IPL 35 .

Behavioural flexibility in animals

Assessment of behavioural flexibility in marmoset monkeys reveals that animals with lateral PFC lesions are not impaired in reversal learning or in shifting behavioural responses to a previously rewarded alternative. These monkeys are, however, impaired with regard to extradimensional shifts . Monkeys with orbitofrontal cortex (OFC) lesions show the opposite behaviour: impairment in reversal learning but no deficits in extradimensional shifts. These findings have led to the proposal that the lateral PFC is necessary for shifting of responding between abstract perceptual dimensions, whereas the OFC and associated corticostriatal loops are necessary for shifting of responding between different stimuli with specific associations with reinforcement 36 . Similar findings have been observed in rodents engaging in reversal learning paradigms. OFC inactivation in rats impairs reversal learning owing to perseverance of previously learned choices 15 . Neurons in the mouse OFC respond saliently and transiently to rule switches during reversal learning 37 . Dorsomedial striatal inactivation impairs both reversal learning and strategy switching, resulting in an inability to maintain new choice patterns once they are selected. The dorsomedial striatum is thought to dynamically interact with multiple prefrontal subregions that generate new strategies to facilitate behavioural flexibility 38 .

For humans, reversal learning is much easier to perform than extradimensional shifts, but similar neuroanatomy to that seen in animals has been observed using fMRI 39 . Neuroimaging additionally reveals the role of the dorsal anterior cingulate cortex and the inferior frontal gyrus in suppression of prior learned responses and response inhibition during reversal learning 40 .

Brain dynamics supporting flexibility

Brain dynamics underlie complex forms of cognition and behaviour, including flexibility. Recent work has examined time-varying or dynamic changes in functional coupling between brain regions 41 , 42 , 43 . Sliding window functional connectivity analyses can be used to quantify brain dynamic metrics, including ‘dwell time’ (the time spent in a particular brain state), ‘frequency of occurrence’ (the number of times a given brain state occurs) and ‘transitions’ (the number of times transitions between brain states are observed) (Fig.  2a , b ). With use of this approach, it has been shown that certain patterns of whole-brain dynamics are associated with elevated levels of cognitive flexibility. Individuals who score higher on the WCST exhibit more episodes of more frequently occurring brain states, and fewer episodes of less frequently occurring brain states that have previously been associated with low vigilance and arousal 44 (Fig.  2c ). Dynamic patterns among specific networks have also been linked with flexible behaviours. Time-varying functional connectivity of the M-CIN predicts individual differences in cognitive flexibility 45 . Dynamics between the default mode or medial frontoparietal network (M-FPN) and the L-FPN have also been linked to cognitive flexibility 46 . A study using hidden Markov models demonstrates that the proportion of time an individual spends in a brain state characterized by functional connectivity of M-FPN and L-FPN regions relates to individual differences in cognitive flexibility 47 . Multimodal investigations considering both anatomical connectivity and activation dynamics find that greater alignment between white matter networks and functional signals is associated with greater cognitive flexibility 48 .

a | In sliding window dynamic functional connectivity analyses, time-varying patterns of connectivity between brain regions are quantified as follows. Whole-brain functional connectivity matrices computed for each window (for example, 45 seconds of functional MRI time-series data) are subjected to clustering, and each window is assigned to a ‘brain state’, here labelled 1, 2 and 3. b | Dynamic metrics, including frequency, dwell time and transitions between states, can then be computed on the basis of trajectories of brain state evolution over time 141 . c | Brain states are ordered from most frequently occurring on the left (state 1, characterized by weak correlations among brain regions) to least frequently occurring on the right (state 5, characterized by strong correlations among brain regions). Higher executive function performance measured outside the scanner is associated with greater episodes of more frequently occurring states and fewer episodes of less frequently occurring states. In the colour bar, hot colours (red) represent high correlation values and cool colours (blue) represent low correlation values. WCST, Wisconsin Card Sorting Test. Parts a , b and c adapted with permission from 44 , Elsevier.

The emerging links between brain dynamics and flexible behaviours in neurotypical adults 49 have set the stage for understanding how these processes are affected in development and ageing. Neural flexibility, or the frequency with which brain regions change allegiance between functional modules, has recently been shown to increase with age during the first 2 years of life 50 . At the other end of the lifespan, older adults performing well on a cognitive test battery were found to exhibit brain states characterized by global coherence, whereas those performing poorly exhibited greater frequency of switching between dynamic brain states 51 . Ease of transitions between brain states distinguishes younger from older individuals, and is further linked with executive function indexed by the D-KEFS. In younger adults, executive function ability is correlated with efficiency in brain dynamics of the M-CIN, whereas for older adults this ability is associated with efficiency in the M-FPN 52 . Brain regions in higher-order association cortices exhibit high levels of functional flexibility, with dissociable age-related changes observed in frontal and parietal regions across the lifespan 53 . Several recent studies have further shown how individual differences in task performance are related to patterns of dynamic brain organization 54 , 55 . Taken together, this emerging literature is in line with the notion that the ability of the brain to flexibly reconfigure itself in response to changing demands may underlie individual differences in flexible behaviours.

Brain variability and flexibility

Variability in neural signals, while initially conceptualized as noise 56 , has more recently been linked with cognitive capacity. Between childhood and mid-adulthood, brain signal variability increases with age, shows negative correlations with reaction time variability and positive correlations with accuracy 57 . Brain variability appears to increase during task performance compared with rest in younger and faster-performing adults, whereas older and slower-performing adults exhibit less differentiation in brain variability across experimental conditions 58 . These findings build on work demonstrating that blood oxygen level-dependent (BOLD) variability is a better predictor of age than BOLD mean 59 . Across the age range from 6 to 85 years, BOLD signal variability decreases linearly across most of the brain, with the exception of the AI, a critical M-CIN node involved in flexibility, which shows the opposite pattern 60 (Fig.  3 ). In line with findings from functional activation studies, it has been shown that increased IFJ variability is linked to better performance on a cognitive flexibility task 61 . Older adults aged 59–73 years who exhibit upregulated brain signal variability show higher levels of task performance 62 . The suggestion is that higher variability might reflect a broader repertoire of metastable brain states and transitions between them to enable optimal responses 57 .

a | Mean squared successive difference is one approach for computing brain signal variability. Applied to neural time-series data, mean squared successive difference is calculated according to the equation shown. b | Regionally specific increases and decreases in brain signal variability across the lifespan may be associated with changes in behavioural performance. Brain signal variability decreases linearly across the lifespan in most brain regions, with the exception of the anterior insula, which exhibits linear age-related increases in variability. In early and late life, the speculation is that larger differences in variability between brain regions may lead to suboptimal behavioural performance. Optimal behavioural performance may be associated with a balance between high and low variability in different brain regions (black arrows) during midlife. Part b is adapted from ref. 60 , CC BY 4.0 ( https://creativecommons.org/licenses/by/4.0/ ).

Flexibility in clinical conditions

Executive function impairments broadly, and flexibility impairments specifically, are observed across many forms of psychopathology and may serve as transdiagnostic intermediate phenotypes 63 . All of the DSM-V categories (with the possible exception of sleep–wake disorders) include clinical conditions in which domains of executive function are compromised; this raises the question of the extent to which the construct of flexibility has discriminative value. In several of the disorders in which flexibility deficits have been documented, these impairments can be observed even while performance on basic perceptual and motor tasks remains unaltered.

Flexibility deficits are observed in neurodevelopmental conditions with early life onset, such as ASD and ADHD, as well as psychiatric conditions that emerge in adolescence, including mood disorders, obsessive–compulsive disorder (OCD) and schizophrenia. Late life onset dementias, including Parkinson disease and Alzheimer disease, are also marked by rigidity and cognitive inflexibility. The extent to which common and distinct neural mechanisms underlie the variety of flexibility deficits observed across the lifespan in these conditions will be explored in this section (Table  1 ).

Flexibility in developmental disorders

ASD and ADHD are two prevalent, heterogeneous neurodevelopmental disorders typically diagnosed in the first 5 years of life. In children with ASD or ADHD, executive function and flexibility deficits are often observed in laboratory settings and in day-to-day activities 64 , 65 . Although children with ASD, ADHD or co-morbid ASD and ADHD may all exhibit flexibility deficits, the nature and severity of these issues can differ across and even within these disorders.

Early work in developmental psychopathology 66 and recent meta-analyses confirm broad executive dysfunction in ASD across domains 67 as well as more specific impairments in flexibility, typically assessed with the WCST 64 , 68 . Restricted and repetitive behaviours (RRBs), considered core deficits in ASD, can include stereotyped movements, insistence on sameness, and circumscribed or perseverative interests 69 . The severity of RRBs is associated with measures of cognitive inflexibility in ASD 70 . Studies of the neural circuitry underlying RRBs transdiagostically point to a critical role for frontostriatal systems in mediating these behaviours 71 . A recent review of neural mechanisms underlying cognitive and behavioural flexibility in autism additionally points to atypical patterns of L-FPN and M-CIN activation in response to task switching and set-shifting 72 .

While ASD is characterized by difficulty in flexibly adapting to changes in routines, children with ADHD have difficulty with attentional focus and exhibit high levels of variability in moment-to-moment behaviours 73 . Diagnostic criteria for ADHD include inattention, hyperactivity and impulsivity 69 , which can be thought of as manifestations of distractibility or too much flexibility. Still, the story is not as simple as ‘impaired flexibility in ASD’ versus ‘heightened flexibility in ADHD’, as there is a very high degree of co-morbidity between these two disorders 74 such that the combination of impaired flexibility and inattention can manifest itself in the same individual. Some reports claim that executive dysfunction is more pervasive and more severe in ADHD than in ASD 75 , yet studies targeting flexibility document that children with ASD perform poorer on the WCST than do children with ADHD 76 . Age-related improvements in executive function are more clearly observed in ASD than in ADHD 77 . Even though not all children with a primary diagnosis of ASD exhibit executive dysfunction 78 , the vast majority of children with co-morbid ASD and ADHD do exhibit executive function impairments 65 .

Only a handful of neuroimaging studies have examined ASD and ADHD together. One found evidence for shared and distinct patterns of intrinsic functional connectivity centrality in children with these disorders 79 . Another reported no evidence for group differences in functional network connectivity across diagnostic groups 80 . Although it is hypothesized that the common behavioural manifestations of cognitive inflexibility across ASD and ADHD should be reflected in shared neural substrates, few assessments of brain circuitry supporting flexibility across these disorders have been conducted. Data-driven techniques are now being used to identify key dimensions of functioning that overlap across diagnostic categories and also present heterogeneously within diagnostic categories 81 . For example, transdiagnostic executive function subtypes have been identified with use of community detection algorithms, and children within the subtype characterized by inflexibility showed a failure to modulate parietal lobe activation in response to increasing executive task demands 82 . Other work examining ASD, ADHD and co-morbid ASD and ADHD using latent profile analysis also provides evidence for transdiagnostic executive function classes 65 . A study using magnetoencephalography found that during an intradimensional/extradimensional set-shift task, children with ASD exhibited greater parietal activity than children with ADHD, and both groups showed sustained parietal activation with an absence of sequential progression of brain activation from parietal to frontal regions 83 . Further work is needed to understand the brain activation patterns and dynamics underlying reduced or heightened flexibility in these neurodevelopmental disorders, as well as the paradoxical combinations (for example, inflexibility alongside distractibility) that can sometimes be observed. This work might focus on how dynamics within specific brain networks might support different domains of executive function. For example, intrinsic dynamics of the M-CIN (but not the L-FPN) have been shown to relate to individual differences in distractibility in neurotypical adults 84 .

Measurement issues complicate the assessment of flexibility deficits and their neural bases in ASD and ADHD, as different combinations of laboratory-based measures, neuropsychological tests and informant-report questionnaires have been used across studies 72 . It is important to note that well-documented inflexible everyday behaviours in ASD are not necessarily directly related to cognitive flexibility deficits assessed experimentally 85 . Standardized informant-report assessments specifically targeting flexible behaviours in autism have been developed, such as the Flexibility Scale, which reveals factors related to routines/rituals, transitions/change, special interests, social flexibility and generativity 86 . Still, these types of nuanced measure of flexibility are not yet routinely used in transdiagnostic assessment settings, leaving several open questions as to the specific profile of executive function and flexibility deficits that characterize neurodevelopmental disorders.

Flexibility in adolescence and midlife

Adolescence is a critical developmental period marked by dramatic physical, social and emotional changes that require cognitive flexibility for successful navigation. Adolescence also coincides with a period of vulnerability and risk of the onset of psychopathologies, including anxiety, depression, OCD and schizophrenia. Brain circuitry supporting cognitive control is still undergoing development during adolescence 87 , in part owing to differential development of limbic and executive control systems 88 . These asymmetries are evident in studies demonstrating that adolescents learn faster from negative reward prediction errors than adults, and recruit the right AI to a greater degree during probabilistic reversal learning 89 .

Signs of mood disorders, including anxiety and depression, can develop during the adolescent years. Pathological anxiety involves excessive worry or the tendency to dwell on difficulties and perceive future problems as more likely than they are in reality, whereas depression involves rumination or passively focusing on distressing thoughts in response to sad mood and experiences 69 . Worry and rumination may reflect the same underlying construct of repetitive negative thinking, which is likely a product of inflexible thinking and difficulty engaging the L-FPN executive control systems in the service of emotion regulation 90 .

Another adolescent-onset disorder characterized by severe flexibility impairments is OCD. Flexibility deficits in OCD manifest themselves as maladaptive patterns of recurrent and persistent thoughts, urges and impulses that are intrusive, as well as compulsions, including repetitive behaviours that an individual feels driven to perform 69 . Neuroimaging investigations across OCD and ASD provide evidence that increased functional connectivity within frontostriatal circuitry relates to more severe symptoms of repetitive behaviour 91 . In OCD, reduced activation of the OFC and frontostriatal regions during cognitive flexibility task performance is regularly reported 92 , 93 .

Schizophrenia is another condition emerging during late adolescence that is associated with reduced cognitive flexibility, often accompanied by frontal lobe hypometabolism 94 . Individuals with schizophrenia perform worse than individuals with OCD on the WCST, suggesting the involvement of different subsystems within basal–corticofrontal circuits in these two disorders 95 . Just as in the general population, frontostriatal circuitry appears to be linked with variability of cognitive flexibility performance in schizophrenia 96 .

Flexibility in neurological disorders

While executive function and flexibility deficits are observed in normal ageing, these issues can be further exacerbated in neurological disorders that affect later life. Older adults exhibit reduced efficiency of lateral prefrontal control regions, and compensate for age-related declines in task-switching performance by relying on enhanced frontotemporal connectivity compared with younger adults 97 . The default–executive coupling hypothesis of ageing proposes that declining performance on executive control tasks and reduced flexibility in older adulthood are underpinned by inflexible coupling of the M-FPN and lateral prefrontal regions 98 . A recent meta-analysis of fMRI studies of executive function in ageing reveals that the IFJ is recruited to a different degree in younger versus older adults. Furthermore, decreased functional connectivity between the IFJ and other executive function-related brain regions is observed with increasing age 99 . Whole-brain computational models permit quantification of metastability and recalibration processes underlying changes in cognitive performance over the lifespan. Such models can help clarify how dedifferentiation observed at the network level, such as that proposed by the default–executive coupling hypothesis of ageing, can be seen as compensation for the decline of structural integrity in the ageing brain 100 .

One of the signs of dementia is heightened executive function impairment compared with that from normal ageing, including a deterioration of mental flexibility and the onset of cognitive rigidity. A burgeoning functional neuroimaging literature including task-switching and set-shifting tasks adapted from neuropsychological assessments (most notably the WCST) investigates cognitive flexibility deficits in ageing and dementia, confirming the critical role of PFC recruitment in maintaining these functions 101 . Flexibility deficits observed in Parkinson disease may result from dysfunction of frontostriatal loops resulting from dopamine depletion 102 . Across neurological disorders, different aspects of cognitive flexibility may be impaired. For example, frontoparietal changes affecting set-shifting ability characterize patients with amyotrophic lateral sclerosis, whereas frontostriatal changes affecting rule inference are seen in primary dystonia and Parkinson disease 103 .

Dysexecuitve syndrome, which involves impairment of working memory, cognitive flexibility and inhibitory control, is seen in progressive dementia syndrome due to Alzheimer disease. This syndrome is accompanied by frontoparietal hypometabolism as demonstrated by positron emission tomography 104 . Taken together, the literature on flexibility in ageing and dementia points to frontoparietal and frontostriatal dysfunction, as might be predicted from the human and animal research.

While we focus on maladaptive outcomes associated with flexibility deficits here, flexibility reductions can also be associated with adaptive or healthy traits, and the level of flexibility required can fluctuate depending on the context. Therefore, alterations in flexibility might in some cases represent normative adaptations to the perceived characteristics of the environment. In Parkinson disease, cognitive impairments such as slowed thinking and cognitive inflexibility parallel motor impairments 102 , suggesting that reduced flexibility might be an appropriate reaction to a world that is experienced as more stationary. Cognitive stability — the opposite of cognitive flexibility — can likewise be beneficial during tasks requiring focused attention and distractor inhibition 105 . Thus, reduced flexibility may paradoxically be optimal under specific conditions.

Drugs and training of flexibility

Animal studies have revealed how specific neurotransmitter systems underlie flexible cognition and behaviour. In humans, cognitive training paradigms and physical activity have been touted as means to bolster flexibility, and there is some initial evidence from studies of development and ageing that bilingualism may confer greater flexibility. This section will summarize what is known regarding the pharmacology of cognitive and behavioural flexibility, then critically review the research on cognitive flexibility enhancement and training.

Pharmacology supporting flexibility

Serotonin and striatal dopamine neurotransmitter systems have a modulatory role in reversal learning, as evidenced by human and animal lesion, stimulation and neuroimaging studies 106 . In humans, transient cerebral serotonin depletion affects processing of negative feedback during reversal learning 107 . l -DOPA withdrawal studies demonstrate that patients with Parkinson disease not receiving medication show inflexibility in the form of increased switch costs when switching between tasks 108 . Methylphenidate, a psychostimulant influencing dopamine and noradrenaline activity, has long been used to treat ADHD and other developmental disorders 109 . There is some evidence from studies of rhesus monkeys given therapeutic doses of methylphenidate that the drug can impair task-switching performance. This indicates that the improved ability to focus attention may come at the expense of hindering flexibility 110 . Taken together, these findings suggest that serotonergic and dopaminergic signalling are critically involved in flexible cognition and behaviour.

The striatal cholinergic systems also appear to play a role in behavioural flexibility. Proton magnetic resonance spectroscopy studies in humans during reversal learning show that lower levels of choline in the dorsal striatum are associated with a lower number of perseverative trials 111 . Studies of the contributions of the cholinergic system to flexibility are complicated, however, by the fact that many cholinergic neurons co-release glutamate or GABA along with acetylcholine 112 .

Interventions to improve flexibility

Computerized cognitive training, physical activity and specialized curricula have been described as potential interventions to improve flexibility in children, yet the evidence supporting the efficacy of these interventions is mixed. Successful programmes involve repeated practice and progressive increases in challenge to executive functions, and children who are more impaired initially benefit the most from cognitive training and physical activity interventions 2 . Generally, training in a specific aspect of executive function can produce short-term narrow transfer, but does not generalize to other aspects of executive function. For example, working memory training can improve working memory performance, but not inhibitory processing or other skills 113 . Implementing a game-based flexibility training designed to increase motivation in children, one study found long-term transfer effects in untrained executive control tasks. The study authors also reported greater performance improvements in the game-based flexibility training group on reading comprehension, an effect that appeared only at the 6-week follow up. These findings suggest that the addition of game elements to executive control training tasks may result in enhanced complexity that facilitates transfer to academic abilities 114 .

Flexibility training in neurodevelopmental disorders has also produced mixed results. One computerized working memory and cognitive flexibility training designed for children with ASD did not result in differential improvement in a randomized controlled trial 115 . An executive function intervention known as Unstuck and On Target aims to address insistence on sameness, flexibility, goal setting and planning using a cognitive behavioural programme. This intervention has been shown to be effective for improving classroom behaviour, flexibility and problem-solving in children with ASD 116 .

Cognitive training has been used to combat age-related cognitive decline, and training-induced structural and functional brain changes in healthy older adults (60 years of age and older) have been demonstrated 117 . A task-switching study reported training-related improvements in task performance, but limited transfer to untrained similar flexibility tasks and no improvements for untrained domains of executive function after 1 year 118 .

Studies examining the effects of aerobic exercise or resistance training interventions without a cognitive component seem to suggest little or no executive function benefit, although exercise that is cognitively challenging, such as martial arts, can produce measurable benefits 119 . In adults of around 60 years of age and older, aerobic exercise interventions may contribute to salutary effects on cognition through prevention of volumetric decreases of hippocampal volume over time 120 . The small effects reported in studies of physical activity interventions on executive function stand in contrast to the fact that children with greater cardiovascular fitness perform better on executive function components, including information processing and control, visuospatial working memory and attention efficiency 121 . Likewise, individuals who are generally more physically active have better executive function than those who are more sedentary 122 .

Effects of bilingualism on flexibility

More than 50% of the global population is bilingual, or able to use two languages with equal fluency. The concept of a ‘bilingual advantage’ suggests that individuals fluent in two languages may develop cognitive advantages, particularly within the executive function domain. Evidence supporting the bilingual advantage identifies inhibition and monitoring as potential mechanisms conferring enhanced executive control in individuals with diverse language experiences 123 . This model suggests that both languages in a bilingual individual’s repertoire are always active to a degree, and there is a constant competition for selection. Lifelong experience of managing and resolving competition between languages imposes demands that require brain regions not typically used for language processing 124 . This bilingual experience reorganizes brain networks to create more effective mechanisms for executive control and results in cognitive benefits when non-linguistic processing draws on the same executive control networks 125 . As language switching involves the same frontal systems involved in executive control and inhibitory processes, it is thought that the bilingual experience results in general enhancement of these brain systems 123 , 126 .

Current research in bilingualism has produced mixed results, and there is no consensus regarding the relationship between bilingualism and cognitive advantages in the executive function domain. Some researchers report cognitive benefits in bilingual individuals 127 , while others fail to replicate these findings in typically developing children 128 and adults 129 . However, the bilingual advantage has been observed in children of lower socio-economic status 124 , 127 . Likewise, in individuals experiencing age-related cognitive decline, a ‘cognitive reserve’ has been observed whereby the bilingual brain is more resistant to neurodegeneration and dementia 123 . The observation that bilingual experience helps offset age-related losses in executive processes has led to the proposal that bilingualism may act as a neuroprotective factor against dementia by buffering against the decline in cognitive control abilities typically observed in later life 130 , 131 . Thus, the bilingual advantage may manifest itself under specific circumstances, but further research is needed on this topic.

Summary and future directions

The global COVID-19 pandemic highlighted the critical need for optimal levels of flexibility at the level of institutions and individuals. Neuroscience research has probed flexibility using paradigms that are capable of spanning both human and animal investigations. This research has demonstrated that cognitive and behavioural flexibility involve executive control processes that rely on the coordinated functioning among several large-scale frontoparietal and frontostriatal brain networks enacting salience detection, attention, inhibition, working memory and switching processes 20 . Understanding the typical development of these networks, their stabilization in adulthood and their potential for breakdown with ageing is the first step towards pinpointing effective strategies for addressing flexibility deficits in psychiatric and neurological disorders and enhancing flexibility across the lifespan. For example, the identification of unique brain profiles supporting various degrees of flexibility across clinical and neurotypical populations could aid in identifying interventions with the highest probability of success for a particular individual. Capturing mechanistic insights with the aid of neuroimaging will help to improve our current diagnostic nosology and move us towards achieving the goals of precision medicine.

Future directions include addressing issues of measurement to maximize ecological and construct validity in research on flexibility. It is important to acknowledge that highly reliable self-report or informant-report measures may better predict individual differences in real-life outcomes, whereas laboratory performance-based measures that are sensitive to within-person experimental manipulations can reveal processes underlying task performance 21 . Standardized, transdiagnostic assessments that are normed for targeted age ranges must be developed and universally adopted to permit characterization of common and unique aspects of flexibility that are affected across clinical conditions. Several self-report scales have been developed for use in adults, including the Cognitive Control and Flexibility Questionnaire 132 , the Cognitive Flexibility Scale 133 and the Psychological Flexibility Questionnaire 134 . Consistent use of questionnaires in future studies will provide a clearer picture of the clinical profile of flexibility deficits. Generally however, self-report/informant-report and behavioural measures are only weakly correlated, as behavioural measures index responses during structured situations, whereas self-report/informant-report queries how individuals behave in real-life situations 21 . Going forward, the challenge of how to bridge laboratory-based, objective behavioural measures of flexibility with real-world indices of flexible behaviour must be tackled. Recent approaches focus on measurement of ‘hot’ or emotionally salient flexibility 135 , 136 , and have also turned towards implicit rather than explicit flexibility performance measures 33 as possible bridges between real-world and laboratory performance.

Translational neuroscience research adopting the RDoC framework will likely continue to build on findings that interactions among the M-CIN, L-FPN and M-FPN are implicated as common neurobiological substrates for mental illness 28 , 137 . The emerging field of computational psychiatry that strives to use data-driven approaches and machine-learning to improve disease classification and predict treatment outcomes 138 will benefit by focusing on transdiagnostic constructs such as flexibility, with clear links to real-life outcomes. The success of these clinically oriented endeavours, however, hinges on progress in neuroinformatics efforts to construct biologically informed taxonomies of psychological processes 139 .

At present, there have been no interventional studies demonstrating the role of changing brain network dynamics in supporting successful training of flexibility. Following similar work providing evidence for dynamic reconfiguration of brain networks with working memory training 140 , future research should focus efforts towards delineating how effective cognitive and behavioural flexibility training alters brain dynamics. Studies of cognitive training generally provide limited support for far transfer of skills. Similarly, while the cumulative effects of exercise are clearly beneficial for the brain and cognition, more research is needed to determine the type and dosage of physical activity intervention that is most suited to enhance executive function and flexibility. If bilingualism can confer a flexibility advantage in some instances, then encouraging bilingualism might be a ‘natural intervention’ strategy to improve flexibility. The bolstering of flexibility that may be conferred by bilingualism provides an added incentive to promote the learning of multiple languages from a young age. The next frontier of flexibility research will likely involve collaborations among clinical psychologists, medical professionals, neuroscientists, engineers, computer scientists and educators.

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This work was supported by the US National Institute of Mental Health (R01MH107549), the Canadian Institute for Advanced Research and a Gabelli Senior Scholar award from the University of Miami to L.Q.U.

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A statistical approach for identifying clusters based on a series of continuous variables or indicators. This type of analysis assumes that there are unobserved latent profiles that generate responses on indicator items.

Also referred to as ‘shifting’, this refers to the ability to switch back and forth between multiple tasks.

Automatic behavioural responses with which immediate reinforcement is associated. Executive functions are necessary for overriding prepotent responses.

A system for classification of diseases.

The research domain criteria (RDoC) matrix is a tool to help implement the principles of RDoC in research studies.

In psychology, the idea that a test is valid if it measures what it claims to measure or is designed to measure.

In the study of creativity, the type of thinking used in an open-ended task, such as coming up with multiple uses for a given object.

In psychology, the idea that something measured with a laboratory test translates to performance in real-life settings.

In psychology, cognitive constructs are terms used to described mental processes. Examples of cognitive constructs include ‘attention‘, ‘memory’ and ‘perception’.

In set-shifting tasks, an extradimensional shift is one in which the important aspect of a stimulus switches from one category to another (for example, in a discrimination task, when colour is no longer an informative aspect of the stimulus, and shape becomes the discriminating characteristic).

Statistical models in which the system being modelled is assumed to be a Markov process (where the probability of each event depends on the state in the previous event) with unobservable or hidden states.

A state of a dynamical system other than the state of least energy. In a non-linear system such as the brain, ‘metastability’ refers to a state in which signals fall outside their natural equilibrium state, but persist for an extended period of time.

Phenomena in which training or learning in one context applies to another.

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Cognition ; Cognitive abilities ; Intelligence ; Mental functioning ; Neuropsychological function ; Thought

Cognitive function is a broad term that refers to mental processes involved in the acquisition of knowledge, manipulation of information, and reasoning. Cognitive functions include the domains of perception, memory, learning, attention, decision making, and language abilities.

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Classical models of human cognition have been conceptualized by cognitive scientists within an information processing paradigm. This approach is grounded by a computational metaphor which draws an analogy between mental operations with the functioning of a computer. Although the central nervous system is recognized as the mechanism underpinning cognition under this approach, a distinction between the brain and cognition is likened to the relation between computer hardware (often referred to as “wetware”) and computer software. Historically, two competing information processing...

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What Does 'Cognitive' Mean in Psychology?

How People Think and What's Involved in Cognitive Processes

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Daniel B. Block, MD, is an award-winning, board-certified psychiatrist who operates a private practice in Pennsylvania.

Verywell / Laura Porter

• Improving Cognitive Skills

Frequently Asked Questions

'Cognitive' is a term used in psychology to describe anything related to thinking, learning, and understanding. So when you hear people talk about cognitive skills or processes, they are referring to different aspects of how the brain works—things like remembering information, learning new things, paying attention, and processing all of the information you encounter each day. 

Cognitive abilities are something you use each and every day. For example, when you are learning a new instrument, you are using your cognitive skills to learn the basics of music theory, pick up melodies, learn the notes, and put that information together to produce music.

'Cognitive' refers to the mental processes involved in gaining knowledge and comprehension. Some of the many different cognitive processes include thinking, knowing, remembering, judging, and problem-solving .

These are higher-level brain functions that encompass language, imagination, perception, and planning. Cognitive psychology is the field of psychology that investigates how people think and the processes involved in cognition. 

At a Glance

Cognitive psychology seeks to understand all of the mental processes involved in human thought and behavior. It focuses on cognitive processes such as decision-making, problem-solving, attention, memory, learning, and more. Keep reading to learn more about different types of cognitive processes, factors that can affect cognition, and the different uses for these cognitive processes.

Types of Cognitive Processes

There are many different types of cognitive processes. They include:

Attention is a cognitive process that allows people to focus on a specific environmental stimulus. Attention is an important cognitive ability because it allows us to focus on the information we need, while also filtering out irrelevant distractions.

Language and language development are cognitive processes that involve the ability to understand and express thoughts through spoken and written words. This allows us to communicate with others, including conveying our own thoughts and learning about others. It also plays an important role in thought.

Learning requires cognitive processes involved in taking in new things, synthesizing information, and integrating it with prior knowledge. Cognitive psychologists often study the mental processes that involved in processing, comprehending, and remembering information.

Memory is an important cognitive process that allows people to encode, store, and retrieve information. It is a critical component in the learning process and allows people to retain knowledge about the world and their personal histories.

Perception is a cognitive process that allows people to take in information through their senses, then utilize this information to respond and interact with the world.

Thought is an essential part of every cognitive process. It allows people to engage in decision-making , problem-solving, and higher reasoning.

Hot Cognition vs. Cold Cognition

Some split cognition into two categories: hot and cold. Hot cognition refers to mental processes in which emotion plays a role, such as reward-based learning . Conversely, cold cognition refers to mental processes that don't involve feelings or emotions, such as working memory .

What is an example of cognition?

Cognition includes all of the conscious and unconscious processes involved in thinking, perceiving, and reasoning. Examples of cognition include paying attention to something in the environment, learning something new, making decisions, processing language, sensing and perceiving environmental stimuli, solving problems, and using memory. 

History of the Study of Cognition

The study of how humans think dates back to the time of ancient Greek philosophers Plato and Aristotle.

Philosophical Origins

Plato's approach to the study of the mind suggested that people understand the world by first identifying basic principles buried deep inside themselves, then using rational thought to create knowledge. This viewpoint was later advocated by philosophers such as Rene Descartes and linguist Noam Chomsky. It is often referred to as rationalism.

Aristotle, on the other hand, believed that people acquire knowledge through their observations of the world around them. Later thinkers such as John Locke and B.F. Skinner also advocated this point of view, which is often referred to as empiricism.

Early Psychology

During the earliest days of psychology—and for the first half of the 20th century—psychology was largely dominated by psychoanalysis , behaviorism , and humanism .

Eventually, a formal field of study devoted solely to the study of cognition emerged as part of the "cognitive revolution" of the 1960s. This field is known as cognitive psychology.

The Emergence of Cognitive Psychology

One of the earliest definitions of cognition was presented in the first textbook on cognitive psychology, which was published in 1967. According to Ulric Neisser, a psychologist and the book's author, cognition is "those processes by which the sensory input is transformed, reduced, elaborated, stored, recovered, and used."

What Can Affect Cognitive Processes?

It is important to remember that these cognitive processes are complex and often imperfect. Some of the factors that can affect or influence cognition include:

Research indicates that as we age, our cognitive function tends to decline. Age-related cognitive changes include processing things more slowly, finding it harder to recall past events, and a failure to remember information that was once known (such as how to solve a particular math equation or historical information).

Attention Issues

Selective attention is a limited resource, so there are a number of things that can make it difficult to focus on everything in your environment. Attentional blink , for example, happens when you are so focused on one thing that you completely miss something else happening right in front of you.

Cognitive Biases

Cognitive biases are systematic errors in thinking related to how people process and interpret information about the world. Confirmation bias is one common example that involves only paying attention to information that aligns with your existing beliefs while ignoring evidence that doesn't support your views. 

Some studies have connected cognitive function with certain genes. For example, a 2020 study published in Brain Communications found that a person's level of brain-derived neurotrophic factor (BDNF), which is 30% determined by heritability, can impact the rate of brain neurodegeneration, a condition that ultimately impacts cognitive function.

Memory Limitations

Short-term memory is surprisingly brief, typically lasting just 20 to 30 seconds, whereas long-term memory can be stable and enduring, with memories lasting years and even decades. Memory can also be fragile and fallible. Sometimes we forget and other times we are subject to misinformation effects that may even lead to the formation of false memories .

Uses for Cognitive Processes

Cognitive processes affect every aspect of life, from school to work to relationships. Some specific uses for these processes include the following.

Learning New Things

Learning requires being able to take in new information, form new memories, and make connections with other things that you already know. Researchers and educators use their knowledge of these cognitive processes to create instructive materials to help people learn new concepts .

Forming Memories

Memory is a major topic of interest in the field of cognitive psychology. How we remember, what we remember, and what we forget reveal a great deal about how cognitive processes operate.

While people often think of memory as being much like a video camera—carefully recording, cataloging, and storing life events away for later recall—research has found that memory is much more complex.

Making Decisions

Whenever people make any type of a decision, it involves making judgments about things they have processed. This might involve comparing new information to prior knowledge, integrating new information into existing ideas, or even replacing old knowledge with new knowledge before making a choice.

Impact of Cognition

Our cognitive processes have a wide-ranging impact that influences everything from our daily life to our overall health.

Perceiving the World

As you take in sensations from the world around you, the information that you see, hear, taste, touch, and smell must first be transformed into signals that the brain can understand. The perceptual process allows you to take in this sensory information and convert it into a signal that your brain can recognize and act upon.

Forming Impressions

The world is full of an endless number of sensory experiences . To make meaning out of all this incoming information, it is important for the brain to be able to capture the fundamentals. Events are reduced to only the critical concepts and ideas that we need.

Filling in the Gaps

In addition to reducing information to make it more memorable and understandable, people also elaborate on these memories as they reconstruct them. In some cases, this elaboration happens when people are struggling to remember something . When the information cannot be recalled, the brain sometimes fills in the missing data with whatever seems to fit.

Interacting With the World

Cognition involves not only the things that go on inside our heads but also how these thoughts and mental processes influence our actions. Our attention to the world around us, memories of past events, understanding of language, judgments about how the world works, and abilities to solve problems all contribute to how we behave and interact with our surrounding environment.

Tips for Improving Cognitive Skills

Cognitive processes are influenced by a range of factors, including genetics and experiences. While you cannot change your genes or age, there are things that you can do to protect and maximize your cognitive abilities:

• Stay healthy . Lifestyle factors such as eating a nutritious diet and getting regular exercise can have a positive effect on cognitive functioning.  
• Think critically . Question your assumptions and ask questions about your thoughts, beliefs, and conclusions.
• Stay curious and keep learning . A great way to flex your cognitive abilities is to keep challenging yourself to learn more about the world.
• Skip multitasking . While it might seem like doing several things at once would help you get done faster, research has shown it actually decreases both productivity and work quality.

In psychology, the term 'cognitive' refers to all of the different mental events involved in thinking, learning, and comprehending. Cognitive processes such as learning, attention, perception, and memory are important parts of the human experience. Understanding how they function can provide insight into normal human thought and behavior and how different cognitive conditions might create problems and impairments. 

Thinking is an important component, but cognition also encompasses unconscious and perceptual processes as well. In addition to thinking, cognition involves language, attention, learning, memory, and perception.

People utilize cognitive skills to think, learn, recall, and reason. Five important cognitive skills include short-term memory, logic, processing speed, attention, and spatial recognition.

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Metacognition, Social Cognition, Embodied Cognition, Language, Sensory Perception, Thinking

Reviewed by Psychology Today Staff

Cognition refers, quite simply, to thinking. There are the obvious applications of conscious reasoning—doing taxes, playing chess, deconstructing Macbeth—but thought takes many subtler forms, such as interpreting sensory input, guiding physical actions, and empathizing with others.

The old metaphor for human cognition was the computer—a logical information-processing machine. You can’t spell cognition without the “cog.” Yet while some of our thoughts may be binary, there's a lot more to our “wetware” than 0's and 1's. Psychological research on cognition focuses not just on thinking, but also on attention , the creation and storage of memories, knowledge acquisition and retention, language learning, and logical reasoning. As people gain new experiences, their cognition can change in subtle but powerful ways.

• Reasoning and Decision Making
• How We Learn New Information
• What Is Metacognition?

The greatest divide between humans and all other animals resides in our higher-order mental processes. Much of cognition-related research has focused on the broad areas of reasoning and decision-making —including how people apply logic, think through problems, and make choices large and small.

One prominent area of research, for example, was popularized by noted psychologists Daniel Kahneman and Amos Tversky and focuses on the distinction between “fast” and “slow” thinking. Fast thinking is intuitive, automatic, and nearly impossible to switch off, relying on heuristic processes to come to a “good enough” decision. By contrast, slow thinking takes a great deal of time and energy analyzing all available data before reaching a conclusion.

Other areas of interest include cognitive biases, such as humans’ tendency to engage in stereotyping and self-serving biases (believing that one is above average on many traits). Isolating and understanding these biases, most of which occur unconsciously, is thought to help people think more objectively.

The brain processes information using a vast web of brain cells called neurons. Information is detected by and encoded in various neurons, which communicate with each other via electrical signals and chemicals called neurotransmitters. That communication between neurons forms the basis of what we experience as thought.

Common examples of cognitive biases include confirmation bias , or the tendency to search for information that supports what one already believes, and anchoring bias , in which someone gives undue weight to the first piece of information they receive, even if it’s incorrect or incomplete.

For more common cognitive biases, see Bias .

Research suggests that how one thinks is influenced by the culture in which one lives . People in Western cultures, for example, tend to focus on the attributes of individual objects or ideas and consider parts of a problem separately from the whole; people in Eastern cultures, by contrast, may be more likely to focus on the broader context and the relationships between objects or ideas.

Decision-making can be complicated by external factors such as incomplete information or an urgent deadline. It may also be hindered by internal processes—such as anxiety about making the “wrong” decision or feeling overwhelmed by an excessive number of choices. Evidence also suggests that when two choices promise relatively similar outcomes, it takes longer to determine which one is “best” than it does to distinguish between vastly dissimilar options.

To learn more, see Decision-Making.

Psychological research suggests that a few simple strategies could lead to better decision-making . These include making the decision when rested and minimally stressed ; taking time to think through complicated decisions, rather than acting on impulse; gathering necessary facts; and creating “rules” to help guide decisions that occur frequently. 

Learning—or the process of taking in new information and acquiring new behaviors and skills—is a key component of cognition. Humans are far from the only species that learns, but our advanced cognitive skills mean that we are able to learn more complex tasks, and grapple with more complex ideas, than most other known life forms. While some learning happens automatically and without conscious thought—learning not to touch a hot stove after one is burned, for instance—other kinds of learning require deliberate practice in order for the information to stick.

When the brain processes new information, new connections form between neurons. If that information is reinforced via repeated practice, these connections grow stronger and can communicate more efficiently; if it isn’t, the connections weaken and may be pruned away. Learning, therefore, literally rewires the brain, creating new links in the vast network of neurons.

Learning occurs via a number of pathways, such as association—if two stimuli are repeatedly paired together, a person or animal will learn that they go together and shift their behavior or expectations accordingly. Learning also happens via socialization; children, for example, learn what behavior is appropriate by observing and modeling the behavior of adults and other children. Human children, along with many other animals, also learn via play , which teaches them how to cooperate, share, follow rules, and think creatively.

The brain is plastic, meaning that it grows and changes over time; learning is a key driver of those changes . In response to new information and stimulating experiences, the brain generates new dendritic spines, which store memories and facilitate improved connections between nerve cells. When stimulation is lacking or information is no longer needed, the same spines may wither and connections between synapses weaken.

Studies show that breaking learning into brief, spread-out chunks is typically more effective than trying to cram the same amount into one longer session. Prioritizing sleep is also essential for effective learning, as sleep helps the brain consolidate short-term memories into long-term ones and prune away irrelevant information.

Memory and learning are closely intertwined. After a fact, concept, or physical skill is learned, it must be stored in one’s memory in order to be recalled or applied later on. Working memory —or the short-term storage of information that is being mentally manipulated—is especially essential for learning new concepts and solving problems.

Metacognition is the act of thinking about one’s own mental processes. Metacognitive awareness allows people to identify, monitor, and uproot negative self-talk and self-limiting beliefs, and to be efficient in goal-setting and task execution. Thinking about and challenging one’s own thinking is at the heart of many types of therapy , including CBT.

Evaluating one’s thinking style or problem-solving processes may help someone identify cognitive biases that are interfering with their decision-making. Metacognition may also help them identify areas where their knowledge or comprehension is lacking.

Thinking aloud is thought to be related to metacognition, as it verbalizes and thus brings attention to an individual’s thought process. Some evidence suggests that articulating one’s thoughts out loud can improve concentration in certain high-pressure situations, such as during a competition . 

Metacognitive therapy is a form of cognitive behavioral therapy that examines patients’ metacognitive beliefs about how their minds work and aims to change those that foster counterproductive thought habits. It is generally a time-limited approach. Evidence suggests that it may be most helpful for treating anxiety and depression . 

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Critical Thinking: A Simple Guide and Why It’s Important

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Critical Thinking: A Simple Guide and Why It’s Important was originally published on Ivy Exec .

Strong critical thinking skills are crucial for career success, regardless of educational background. It embodies the ability to engage in astute and effective decision-making, lending invaluable dimensions to professional growth.

At its essence, critical thinking is the ability to analyze, evaluate, and synthesize information in a logical and reasoned manner. It’s not merely about accumulating knowledge but harnessing it effectively to make informed decisions and solve complex problems. In the dynamic landscape of modern careers, honing this skill is paramount.

The Impact of Critical Thinking on Your Career

☑ problem-solving mastery.

Visualize critical thinking as the Sherlock Holmes of your career journey. It facilitates swift problem resolution akin to a detective unraveling a mystery. By methodically analyzing situations and deconstructing complexities, critical thinkers emerge as adept problem solvers, rendering them invaluable assets in the workplace.

☑ Refined Decision-Making

Navigating dilemmas in your career path resembles traversing uncertain terrain. Critical thinking acts as a dependable GPS, steering you toward informed decisions. It involves weighing options, evaluating potential outcomes, and confidently choosing the most favorable path forward.

☑ Enhanced Teamwork Dynamics

Within collaborative settings, critical thinkers stand out as proactive contributors. They engage in scrutinizing ideas, proposing enhancements, and fostering meaningful contributions. Consequently, the team evolves into a dynamic hub of ideas, with the critical thinker recognized as the architect behind its success.

☑ Communication Prowess

Effective communication is the cornerstone of professional interactions. Critical thinking enriches communication skills, enabling the clear and logical articulation of ideas. Whether in emails, presentations, or casual conversations, individuals adept in critical thinking exude clarity, earning appreciation for their ability to convey thoughts seamlessly.

☑ Adaptability and Resilience

Perceptive individuals adept in critical thinking display resilience in the face of unforeseen challenges. Instead of succumbing to panic, they assess situations, recalibrate their approaches, and persist in moving forward despite adversity.

☑ Fostering Innovation

Innovation is the lifeblood of progressive organizations, and critical thinking serves as its catalyst. Proficient critical thinkers possess the ability to identify overlooked opportunities, propose inventive solutions, and streamline processes, thereby positioning their organizations at the forefront of innovation.

☑ Confidence Amplification

Critical thinkers exude confidence derived from honing their analytical skills. This self-assurance radiates during job interviews, presentations, and daily interactions, catching the attention of superiors and propelling career advancement.

So, how can one cultivate and harness this invaluable skill?

✅ developing curiosity and inquisitiveness:.

Embrace a curious mindset by questioning the status quo and exploring topics beyond your immediate scope. Cultivate an inquisitive approach to everyday situations. Encourage a habit of asking “why” and “how” to deepen understanding. Curiosity fuels the desire to seek information and alternative perspectives.

✅ Practice Reflection and Self-Awareness:

Engage in reflective thinking by assessing your thoughts, actions, and decisions. Regularly introspect to understand your biases, assumptions, and cognitive processes. Cultivate self-awareness to recognize personal prejudices or cognitive biases that might influence your thinking. This allows for a more objective analysis of situations.

✅ Strengthening Analytical Skills:

Practice breaking down complex problems into manageable components. Analyze each part systematically to understand the whole picture. Develop skills in data analysis, statistics, and logical reasoning. This includes understanding correlation versus causation, interpreting graphs, and evaluating statistical significance.

✅ Engaging in Active Listening and Observation:

Actively listen to diverse viewpoints without immediately forming judgments. Allow others to express their ideas fully before responding. Observe situations attentively, noticing details that others might overlook. This habit enhances your ability to analyze problems more comprehensively.

✅ Encouraging Intellectual Humility and Open-Mindedness:

Foster intellectual humility by acknowledging that you don’t know everything. Be open to learning from others, regardless of their position or expertise. Cultivate open-mindedness by actively seeking out perspectives different from your own. Engage in discussions with people holding diverse opinions to broaden your understanding.

✅ Practicing Problem-Solving and Decision-Making:

Engage in regular problem-solving exercises that challenge you to think creatively and analytically. This can include puzzles, riddles, or real-world scenarios. When making decisions, consciously evaluate available information, consider various alternatives, and anticipate potential outcomes before reaching a conclusion.

✅ Continuous Learning and Exposure to Varied Content:

Read extensively across diverse subjects and formats, exposing yourself to different viewpoints, cultures, and ways of thinking. Engage in courses, workshops, or seminars that stimulate critical thinking skills. Seek out opportunities for learning that challenge your existing beliefs.

✅ Engage in Constructive Disagreement and Debate:

Encourage healthy debates and discussions where differing opinions are respectfully debated.

This practice fosters the ability to defend your viewpoints logically while also being open to changing your perspective based on valid arguments. Embrace disagreement as an opportunity to learn rather than a conflict to win. Engaging in constructive debate sharpens your ability to evaluate and counter-arguments effectively.

✅ Utilize Problem-Based Learning and Real-World Applications:

Engage in problem-based learning activities that simulate real-world challenges. Work on projects or scenarios that require critical thinking skills to develop practical problem-solving approaches. Apply critical thinking in real-life situations whenever possible.

This could involve analyzing news articles, evaluating product reviews, or dissecting marketing strategies to understand their underlying rationale.

In conclusion, critical thinking is the linchpin of a successful career journey. It empowers individuals to navigate complexities, make informed decisions, and innovate in their respective domains. Embracing and honing this skill isn’t just an advantage; it’s a necessity in a world where adaptability and sound judgment reign supreme.

So, as you traverse your career path, remember that the ability to think critically is not just an asset but the differentiator that propels you toward excellence.

Menthol’s Surprising Effect on Alzheimer’s Cognitive Decline in Mice: Study Highlights

A startling discovery emerged from recent scientific investigations, suggesting that menthol inhalation can enhance cognitive functions in mice suffering from Alzheimer’s disease. Researchers stumbled upon the chemical compound’s ability to curtail brain damage typically affiliated with the disorder.

The study observed a notable decline in levels of the interleukin-1-beta (IL-1β) protein, which plays a critical role in modulating the body’s inflammatory response. This response is often a natural protective measure but can be detrimental when in excess.

This transformative study, published in April 2023, underscores the promise of using specific odors as potential therapeutic approaches for Alzheimer’s. Understanding odorous stimuli and their corresponding cerebral and immune reactions could unlock new health-restorative strategies.

Immunologist Juan José Lasarte from the Center for Applied Medical Research (CIMA) in Spain expressed the revelation when the findings were announced. The study demonstrated that rodents inhaled menthol, showcasing improved cognitive abilities in both Alzheimer’s-affected and healthy young mice.

Experiments indicated that a six-month regimen of menthol prevented the deterioration of cognitive skills and memory in mice with Alzheimer’s. Furthermore, menthol seemingly regulated IL-1β protein to non-hazardous levels in the brain.

Artificially reducing the population of T regulatory (Treg) cells, which are crucial for immune modularity, mirrored some of the benefits seen with menthol exposure, offering a potential pathway for future interventions.

Neuroscientist Ana Garcia-Osta from CIMA highlights the dual effect of menthol exposure and Treg cell inhibition in lowering IL-1β. She also noted that using a specific drug to block this protein, which is already employed in certain autoimmune diseases, improved cognitive functions in both normal and Alzheimer’s-affected mice.

Pre-existing research underlines multiple correlations between the olfactory system and our immune and nervous systems, though their intricacies are complex. Despite this, it’s discernible that certain aromas can incite specific brain reactions, influencing memory, emotions, and more.

Central nervous system disorders, including Alzheimer’s, Parkinson’s, and schizophrenia, often involve a diminished sense of smell, which this new research could complement. Further studies in humans will be essential to validate these promising results.

“Our findings provide a significant advance in our comprehension of the ties between the immune system, central nervous system, and olfaction,” insists immunologist Noelia Casares from CIMA.

Ultimately, the research infers that odorants and immune modulators could be crucial in preventing and managing Alzheimer’s and other central nervous system conditions.

The study findings have been disseminated in the Frontiers in Immunology journal.

This article originally appeared in May 2023.

FAQs About Menthol and Alzheimer’s in Mice

Can menthol be used to improve cognitive functions in humans with alzheimer’s.

While the study shows promise in mice, more research is required to determine whether menthol could have the same effects in humans with Alzheimer’s.

Is IL-1β protein related to Alzheimer’s disease?

The interleukin-1-beta (IL-1β) protein is associated with the body’s inflammatory response and has been linked to the cognitive decline observed in Alzheimer’s disease.

What role do T regulatory (Treg) cells play in the immune response?

T regulatory cells help regulate the immune system, ensuring it responds adequately without causing excessive harm to the body.

How can odorants affect the brain and immune system?

Specific odors can trigger particular responses in the brain, potentially leading to changes in memory, emotion, and the body’s immune response.

This groundbreaking study offers a potential avenue for exploring the therapeutic applications of odors like menthol in mitigating cognitive impairment in Alzheimer’s disease. Although the research conducted on mice shows optimistic results, it is critical to approach these findings with caution until substantial human studies confirm their efficacy and safety. With a deeper understanding of the intricate relationship between olfaction and cognitive health, we may unlock novel and non-invasive treatment options for Alzheimer’s and other central nervous system disorders in the future.

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• v.18(2); 2019 Jun

The “online brain”: how the Internet may be changing our cognition

Joseph firth.

1 NICM Health Research Institute, Western Sydney University, Westmead, Australia

2 Division of Psychology and Mental Health, University of Manchester, Manchester, UK

3 Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia

John Torous

4 Division of Digital Psychiatry, Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA

Brendon Stubbs

5 Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK

6 Physiotherapy Department, South London and Maudsley NHS Foundation Trust, London, UK

Josh A. Firth

7 Department of Zoology, Edward Grey Institute, University of Oxford, Oxford, UK

8 Merton College, University of Oxford, Oxford, UK

Genevieve Z. Steiner

9 Translational Health Research Institute, Western Sydney University, Penrith, NSW, Australia

10 Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin University, Cambridge, UK

Mario Alvarez‐Jimenez

11 Orygen, The National Centre of Excellence in Youth Mental Health, University of Melbourne, Melbourne, Australia

John Gleeson

12 School of Psychology, Australian Catholic University, Melbourne, Australia

Davy Vancampfort

13 Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium

14 University Psychiatric Center, KU Leuven, Leuven, Belgium

Christopher J. Armitage

15 NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK

16 NIHR Greater Manchester Patient Safety Translational Research Centre, Manchester, UK

Jerome Sarris

17 Professorial Unit, The Melbourne Clinic, Department of Psychiatry, University of Melbourne, Australia

The impact of the Internet across multiple aspects of modern society is clear. However, the influence that it may have on our brain structure and functioning remains a central topic of investigation. Here we draw on recent psychological, psychiatric and neuroimaging findings to examine several key hypotheses on how the Internet may be changing our cognition. Specifically, we explore how unique features of the online world may be influencing: a) attentional capacities, as the constantly evolving stream of online information encourages our divided attention across multiple media sources, at the expense of sustained concentration; b) memory processes, as this vast and ubiquitous source of online information begins to shift the way we retrieve, store, and even value knowledge; and c) social cognition, as the ability for online social settings to resemble and evoke real‐world social processes creates a new interplay between the Internet and our social lives, including our self‐concepts and self‐esteem. Overall, the available evidence indicates that the Internet can produce both acute and sustained alterations in each of these areas of cognition, which may be reflected in changes in the brain. However, an emerging priority for future research is to determine the effects of extensive online media usage on cognitive development in youth, and examine how this may differ from cognitive outcomes and brain impact of uses of Internet in the elderly. We conclude by proposing how Internet research could be integrated into broader research settings to study how this unprecedented new facet of society can affect our cognition and the brain across the life course.

The Internet is the most widespread and rapidly adopted technology in the history of humanity. In only decades, Internet use has completely re‐invented the ways in which we search for information, consume media and entertainment, and manage our social networks and relationships. With the even more recent advent of smartphones, Internet access has become portable and ubiquitous to the point at which the population of the developed world can be considered “online” 1 , 2 , 3 .

However, the impact that this new channel for connection, information, communication, and screen time is having on our brains and cognitive functioning is unclear. Prior to the Internet, a large body of research had convincingly demonstrated that the brain is somewhat malleable to environmental demands and stimuli, particularly with regards to learning new processes, due to its capacity for neuroplasticity 4 . Various scenarios have been observed to induce long‐term changes in the neuronal architecture of the human brain, including second‐language acquisition 5 , learning new motor skills (such as juggling) 6 , and even formal education or exam preparation 7 . The widespread use of the Internet across the globe has introduced, for many, the necessity and opportunity to learn a myriad of new skills and ways to interact with society, which could bring about neural changes. As an example, even simple interactions with the Internet through the smartphone's touchscreen interface have been demonstrated to bring about sustained neurocognitive alterations due to neural changes in cortical regions associated with sensory and motor processing of the hand and thumb 8 . Beyond this, the Internet also presents a novel platform for almost‐endless learning of new information and complex processes, relevant to both the online and offline world 9 .

Along with neuroplastic mechanisms, other environmental and biological factors can also cause changes in the brain's structure and function, resulting in cognitive decline 10 . In aging samples, for instance, there is evidence to indicate that age‐related cognitive decline may be partly driven by a process of atrophy. Some studies have shown that adopting a less engaging lifestyle across the lifespan may accelerate loss of cognitive function 11 , due to lower “cognitive reserve” (the ability of the brain to withstand insult from age and/or pathology) 12 . Some emerging evidence indicates that disengaging from the “real world” in favor of virtual settings may similarly induce adverse neurocognitive changes. For example, a recent randomized controlled trial (RCT) 13 found that six weeks of engaging in an online role playing game caused significant reductions in grey matter within the orbitofrontal cortex – a brain region implicated in impulse control and decision making. However, the study did not address the extent to which these results were specific to online gaming, rather than general internet usage. Nonetheless, this raises the possibility that various types of Internet usage could differentially affect the brain and cognitive processes – in both adverse and beneficial ways. This may be of particular relevance to the developing brains of children and adolescents, as many cognitive processes (particularly those relevant to higher executive functions and social cognition) are not entirely innate, but rather are strongly influenced by environmental factors 14 .

Although only recently emerging, this possibility has led to a substantial body of research empirically investigating the multiple potential pathways through which the Internet could affect our brains’ structure, function, and cognitive development. Specifically, the bulk of existing research can be separated into three specific domains, examining how the internet is affecting: a) attention (i.e., how the constant influx of online information, prompts and notifications competing for our attention may encourage individuals to displace their concentration across multiple incoming media streams – and the consequences this may have for attentional‐switching versus sustained‐attention tasks); b) memory and knowledge (i.e., the extent to which we rely on the Internet as our primary informational resource, and how unique properties of online information access may affect how we process new memories and value our internal knowledge); c) social cognition (along with the personal and societal consequences of increasingly embedding our social networks, interactions, and status within the online world).

In this state‐of‐the‐art review, we present the current leading hypotheses of how the Internet may alter these cognitive processes, subsequently examining the extent to which these hypotheses are supported by recent findings from psychological, psychiatric and neuroimaging research. In this way, we aggregate the contemporary evidence arising from multiple fields of research to produce revised models on how the Internet may be affecting our brains and cognition. Furthermore, whereas studies to date have focused upon only specific age groups, we examine the effects of the Internet on the human brain across the entire life course. In particular, we explore how the potential benefits/drawbacks of extensive Internet integration with cognitive processes may differ among children and older adults. Finally, we identify important gaps in the existing literature to present key priorities for future research in order to gain new insights for minimizing detrimental effects of the Internet, while capitalizing on this new feature of our societies to potentially influence neurocognitive processes in a beneficial way.

“DIGITAL DISTRACTIONS”: A HIJACK OF ATTENTION ON THE INFORMATION HIGHWAY?

How does the internet gain and sustain our attention.

The Internet consumes a considerable chunk of our attention on a day‐to‐day basis. The vast majority of adults go online daily, and over a quarter report being online “almost constantly” 2 . Within this, one in five American adults are now “smartphone‐only” Internet users 1 . Importantly, the introduction of these Internet‐enabled mobile devices has also reduced the “digital divide” previously experienced by lower and middle income countries 15 . The amount and frequency of Internet usage is even more pronounced amongst younger people. Most adults today witnessed the beginning of the transition from “Internet‐free” to “Internet‐everywhere” societies. However, younger generations (termed “digital natives” 16 ) have been brought up entirely within a “connected world” , particularly in developed countries. Consequently, digital natives are often the first to adopt new online technologies as they arise 16 , and engage extensively with all existing features of the Internet. For instance, 95% of US teens have access to a smartphone, and 45% are online “almost constantly” 3 .

Multiple factors are driving the rapid uptake and extensive usage of Internet‐enabled technologies across the globe. This is partly due to the Internet now being unavoidable, ubiquitous, and a highly functional aspect of modern living. For instance, Internet use is now deeply entwined with education, travel, socializing, commerce, and the majority of workplaces. Along with pragmatic uses, the Internet also offers an endless array of recreational and entertainment activities, through podcasts, e‐books, videos, streaming movies and gaming. However, the ability of the Internet to capture and hold attention is not solely due to the quality of media content available online. Rather, it is also driven by the underlying design and presentation of the online world. One such example is the self‐evolving “attraction mechanism”; whereby aspects of the Internet that fail to gain attention are quickly drowned out in the sea of incoming information, while the successful aspects of the adverts, articles, apps or anything that does manage to capture our attention (even superficially) are logged (through clicks and scrolls), noticed (through online shares), and subsequently proliferated and expanded upon. Alongside this, leading technology companies have been accused of intentionally capitalizing on the addictive potential of Internet, by studying, testing, and refining the attention‐grabbing aspects of their websites and applications (“apps”) to promote extremely high levels of engagement, without due concern for user well‐being 17 .

Furthermore, even when not using the Internet for any specific purpose, smartphones have introduced widespread and habitual “checking” behaviours, characterized by quick but frequent inspections of the device for incoming information from news, social media, or personal contacts 18 . These habits are thought to be the result of behavioural reinforcement from “information rewards” that are received immediately on checking the device 19 , potentially engaging the cortico‐striatal dopaminergic system due to their readily available nature 20 . The variable‐ratio reinforcement schedule inherent to device checking may further perpetuate these compulsive behaviours 21 .

Cognitive consequences of the attention‐grabbing Internet

The unprecedented potential of the Internet to capture our attention presents an urgent need for understanding the impact that this may have on our thought processes and well‐being. Already, education providers are beginning to perceive detrimental effects of the Internet on children's attention, with over 85% of teachers endorsing the statement that “today's digital technologies are creating an easily distracted generation” 22 . The primary hypothesis on how the Internet affects our attentional capacities is through hyperlinks, notifications, and prompts providing a limitless stream of different forms of digital media, thus encouraging us to interact with multiple inputs simultaneously, but only on a shallow level, in a behavioural pattern termed “media multi‐tasking” 23 , 24 .

The seminal study by Ophir et al 23 was among the first to explore the sustained impact of media multi‐tasking on cognitive capacities. This was a cross‐sectional study of individuals who engaged in “heavy” (i.e., frequent and extensive) media multi‐tasking compared to those who did not. Cognitive testing of the two groups produced the then‐surprising finding that those involved in heavy media multi‐tasking performed worse in task‐switching tests than their counterparts – contrary to the authors’ expectation that the “extra practice” afforded by frequent media multi‐tasking would confer cognitive benefit in task‐switching scenarios. Closer inspection of findings suggested that the impeded task‐switching ability in heavy media multi‐tasking individuals was due to their increased susceptibility to distraction from irrelevant environmental stimuli 23 .

Since these initial findings, the effects of media multi‐tasking on cognition have come under increasing scrutiny, because the increasingly diverse forms of entertainment and activities available through the online world can further our capabilities (and temptation) of engaging in media multi‐tasking 25 , even on single devices. For instance, Yeykelis et al 26 measured participants’ media multi‐tasking between different types of online media content while using just one device (personal laptops), and found that switches occurred as frequently as every 19 seconds, with 75% of all on‐screen content being viewed for less than one minute. Measures of skin conductance during the study found that arousal increased in the seconds leading up to media switching, reaching a high point at the moment of the switch, followed by a decline afterward 26 . Again, this suggests that the proclivity for alternating between different computer windows, opening new hyperlinks, and performing new searches could be driven by the readily available nature of the informational rewards, which are potentially awaiting in the unattended media stream. Supporting this, the study also found that, whereas switching from work‐related content to entertainment was associated with increased arousal in anticipation of the switch, there was no anticipatory arousal spike associated with entertainment to work‐content switches 26 .

The growing concern around the increasing amount of media multi‐tasking with the spread of ubiquitous Internet access has resulted in further empirical studies. These have produced conflicting findings, with some failing to find any adverse effects on attention 27 , and others indicating that media multi‐tasking may even be linked to increased performance for other aspects of cognition, such as multisensory integration 28 . Nonetheless the literature, on balance, does seem to indicate that those who engage in frequent and extensive media multi‐tasking in their day‐to‐day lives perform worse in various cognitive tasks than those who do not, particularly for sustained attention 25 .

Imaging studies have shed light onto the neural differences which may account for these cognitive deficits. Functionally, those who engage in heavy media multi‐tasking perform poorer in distracted attention tasks, even though exhibiting greater activity in right prefrontal regions 29 . As right prefrontal regions are typically activated in response to distractor stimuli, the observed increases in recruitment of these regions alongside poorer performance suggests that heavy media multi‐taskers require greater cognitive effort to maintain concentration when faced with distractor stimuli 29 . Structurally, high levels of Internet usage 30 and heavy media multi‐tasking 31 are associated with decreased grey matter in prefrontal regions associated with maintaining goals in face of distraction (such as the right frontal pole and anterior cingulate cortex). However, the findings to date must be interpreted with caution, as various confounding factors may be affecting the results of these cross‐sectional imaging studies. Although the differences persist when controlling for general digital media use and other simple confounders (age, gender, etc.), further research is required to examine if the observed neural differences are specifically attributable to heavy vs. light media multi‐tasking, or in fact driven by broader differences in lifestyle between the two groups.

Given the amount of time that people now spend in media multi‐tasking via personal digital devices, it is increasingly relevant to consider not only sustained changes which arise in those who engage in large amounts of media multi‐tasking, but also the acute effects on immediate cognitive capacities. A meta‐analysis of 41 studies showed that engaging in multi‐tasking was associated with significantly poorer overall cognitive performance, with a moderate‐to‐large effect size (Cohen's d=–0.71, 95% CI: –0.86 to –0.57). This has been confirmed by more recent studies, further showing that even short‐term engagement with an extensively hyperlinked online environment (i.e., online shopping for 15 minutes) reduces attentional scope for a sustained duration after coming offline, whereas reading a magazine does not produce these deficits 32 .

Overall, the available evidence strongly indicates that engaging in multi‐tasking via digital media does not improve our multi‐tasking performance in other settings – and in fact seems to decrease this cognitive capacity through reducing our ability to ignore incoming distractions. Much of the multi‐tasking investigations so far have been focusing on personal computers. However, smartphone technologies may even further encourage people to engage in media multi‐tasking through high rates of incoming prompts from emails, direct messages and social media notifications occurring while both using and not using the device. Thus, along with determining long‐term consequences of media multi‐tasking, future research should examine how the constant multi‐tasking made possible by Internet‐enabled mobile devices may impact daily functioning through acute but high frequency effects.

Furthermore, both the immediate and chronic effects of media multi‐tasking are relatively unexplored in children and adolescents, who are the prime users of such technologies 33 and are at a phase of development that is crucial for refining higher cognitive abilities 14 . The first longitudinal study of media multi‐tasking in young people has recently found that frequent multi‐tasking behaviours do predict the development of attentional deficits specifically in early adolescents, but not in older teens 34 . Additionally, extensive media multi‐tasking during childhood and adolescence could also negatively impact cognitive development through indirect means, by reducing engagement with academic and social activities, as well as by interfering with sleep 35 , or reducing the opportunity to engage in creative thinking 36 , 37 . Clearly, further research is necessary to properly measure the effects of ubiquitous computing on children's cognitive development, and to find practical ways for ameliorating any detrimental impact this may be having.

“iFORMATION”: NEUROCOGNITIVE RESPONSES TO ONLINE INFORMATION GATHERING

The internet and transactive memory.

In response to the question “How has the Internet changed your life?” , some common answers include finding new friends, renewing old friendships, studying online, finding romantic relationships, furthering career opportunities, shopping, and travel 38 . However, the most common answer is people stating that the Internet has “changed the way in which they access information” 38 . Indeed, for the first time in human history, the majority of people living in the developed world have access to almost all factual information in existence literally at their fingertips.

Along with the obvious advantages, this unique situation also introduces the possibility of the Internet ultimately negating or replacing the need for certain human memory systems – particularly for aspects of “semantic memory” (i.e., memory of facts) – which are somewhat independent from other types of memory in the human brain 39 . An initial indication of Internet information gathering affecting typical memory processes was provided by Sparrow et al 40 , who demonstrated that the ability to access information online caused people to become more likely to remember where these facts could be retrieved rather than the facts themselves, indicating that people quickly become reliant on the Internet for information retrieval.

It could be argued that this is not unique to the Internet, but rather just an example of the online world acting as a form of external memory or “transactive memory” 40 , 41 . Transactive memory has been an integral part of human societies for millennia, and refers to the process by which people opt to outsource information to other individuals within their families, communities, etc., such that they are able to just remember the source of the knowledge, rather than attempting to store all of this information themselves 41 . Although beneficial at a group level, using transactive memory systems does reduce an individual's ability to recall the specifics of the externally stored information 42 . This may be due to individuals using transactive memory for “cognitive offloading” , implicitly reducing their allocation of cognitive resources towards remembering this information, since they know this will be available for future reference externally. This phenomenon has been demonstrated in multiple contexts, including those of team work 43 and other “non‐Internet” technologies (e.g., photography reducing individuals’ memories of the objects they photographed) 44 .

However, it is becoming clear that the Internet actually presents something entirely novel and distinct from previous transactive memory systems 45 , 46 . Crucially, the Internet seems to bypass the “transactional” aspect that is inherent to other forms of cognitive offloading in two ways. First, the Internet does not place any responsibility on the user to retain unique information for others to draw upon (as would typically be required in human societies) 45 . Second, unlike other transactive memory stores, the Internet acts as a single entity that is responsible for holding and retrieving virtually all factual information, and thus does not require individuals to remember what exact information is externally stored, or even where it is located. In this way, the Internet is becoming a “supernormal stimulus” 46 for transactive memory – making all other options for cognitive offloading (including books, friends, community) become redundant, as they are outcompeted by the novel capabilities for external information storage and retrieval made possible by the Internet.

How does a supernormal stimulus interact with normal cognition?

Unfortunately, the rapid methods of acquisition and constant availability of information afforded by the Internet may not necessarily lead to better use of information gained. For instance, an experimental study 47 found that individuals instructed to search for specific information online completed the information gathering task faster than those using printed encyclopedias, but were subsequently less able to recall the information accurately.

During Internet and encyclopedia information gathering tasks, functional magnetic resonance imaging was used to examine activation in the ventral and dorsal streams. These regions are referred to as the “what” and “where” streams, respectively, due to their indicated roles in storing either the specific content (ventral stream) or external location (dorsal stream) of incoming information 47 . Although there was no difference in activation of the dorsal stream, results showed that the poorer recall of Internet‐sought information compared to encyclopedia‐based learning was associated with reduced activation of the ventral (“what”) stream during online information gathering. These findings further support the possibility, initially raised by Sparrow et al 40 , that online information gathering, while faster, may fail to sufficiently recruit brain regions for storing information on a long‐term basis.

The potential for online searching to produce a sustained impact upon our cognitive processes has been investigated in a series of studies examining pre‐post changes following a six‐day Internet search training paradigm. In these studies, young adults were given an hour per day of Internet search tasks, and undertook an array of cognitive and neuroimaging assessments pre‐ and post‐training. Results showed that the six‐day Internet search training reduced regional homogeneity and functional connectivity of brain areas involved in long‐term memory formation and retrieval (e.g., temporal gyrus) 48 . This indicates that a reliance on online searching may impede memory retrieval by reducing the functional connectivity and synchronization of associated brain regions 48 . Furthermore, when faced with new questions after the six days, the training had increased participants’ self‐reported impulses towards using the Internet to answer those questions, which was reflected in a recruitment of prefrontal brain areas required for behavioural and impulse control 49 . This increased propensity for relying on Internet searches for gathering new information has been replicated in subsequent studies 50 , and is in keeping with the “supernormal stimulus” nature of the Internet, potentially suggesting that online information gathering quickly trains people to become dependent on this tool when faced with unknown issues.

However, despite the possible adverse effects on regular “offline” memory, the six‐days training did make people more efficient at using the Internet for retrieving information, as participants became faster at the search tasks, with no loss of accuracy 51 . Search training also produced increases in white matter integrity of the fiber tracts connecting the frontal, occipital, parietal and temporal lobes, significantly more than the non‐search control condition 52 . In other studies, cognitive offloading via digital devices has also been found to improve people's ability to focus on aspects that are not immediately retrievable, and thus remember these better in the future 53 .

These findings seem to support the emergent hypotheses that relying on the Internet for factual memory storage may actually produce cognitive benefit in other areas, perhaps by “freeing up” cognitive resources 54 , and thus enabling us to use our newly available cognitive capacities for more ambitious undertakings than previously possible 45 . Researchers advocating this view have pointed to multiple domains of collective human endeavor that have already been transformed by the Internet's provision of supernormal transactive memory, such as education, journalism and even academia 55 . As online technologies continue to advance (particularly with regards to “wearables”), it is conceivable that the performance benefits from the Internet, which are already visible at the societal level, could ultimately become integrated within individuals themselves, enabling new heights of cognitive function 56 .

Unfortunately, however, a more sobering finding with regards to the immediate possibility of ubiquitous Internet access enabling new heights of human intelligence is provided by Barr et al 57 , who observed that analytical thinkers, with higher cognitive capacities, actually use their smartphone less for transactive memory in day‐to‐day situations compared to individuals with non‐analytical thinking styles. Furthermore, the reduced smartphone usage in analytical versus non‐analytical thinkers was specific to online information searching, with no differences in social media or entertainment usages, thus indicating that the differences are likely due to the Internet furthering “cognitive miserliness” among less analytical thinkers 57 .

Alongside this, the increasing reliance on the Internet for information may cause individuals to “blur the lines” between their own capabilities and their devices’ 58 . In a series of experiments, Fisher et al 59 investigated how the Internet influences our self‐perceived knowledge. Results showed that online searching increases our sense of how much we know, even though the illusion of self‐knowledge is only perceived for the domains in which the Internet can “fill in the gaps” for us. The experiments also demonstrated how quickly individuals internalized the Internet's external knowledge as their own – as even immediately after using the Internet to answer the task questions, participants attributed their higher quality explanations to “increased brain activity” . More recent studies have shown that illusions of self‐knowledge similarly persist when using smartphones to retrieve online information 58 . As individuals become more and more connected with their personal digital devices (which are also always accessible), it seems inevitable that the distinction between self and Internet's abilities will become increasingly elusive, potentially creating a constant illusion of “greater than actual knowledge” among large portions of the population.

Overall, the Internet clearly can provide a “superstimulus” for transactive memory, which is already changing the way we store, retrieve, and even value knowledge. However, with popular online information sources such as Google and Wikipedia less than 20 years old, it is currently not possible to ascertain how this may eventually be reflected in long‐term changes to the structure and function of the human brain. Nonetheless, our constant connection with the online world through personal devices (i.e., smartphones), along with the emerging potential for more direct integration through wearable devices, certainly indicates that we are set to become more reliant on the Internet for factual information as time goes on. Also, whereas the studies described above have focused on factual knowledge, the Internet is also now becoming a superstimulus for spatial information (through providing constant access to online maps and global positioning system). As spatial memory is somewhat independent from semantic memory in the human brain 60 , further research should investigate the multitude of ways in which extensive use of these external memory systems may reduce, enhance or alter our cognitive capacities.

ONLINE SOCIAL NETWORKS: FAULTY CONNECTIONS, OR FALSE DICHOTOMY?

Human sociality in the online world.

Social relationships and having a sense of connection are important determinants of happiness and stress relief 61 , 62 , mental and physical well‐being 63 , 64 , and even mortality 65 . Over the past decade, the proportion of an individual's social interactions that take place online within social networking sites (e.g., Facebook, Instagram, Twitter) has grown dramatically 66 , 67 , and our connection with these sites is now strongly meshed with the offline world. The real‐world implications of this are perhaps best evidenced by the critical role that social media have played in multiple global affairs, including reportedly starting and precipitating the London Riots, the Occupy movement 68 , and even the Arab Spring 69 , along with potentially influencing the outcomes of the UK's European Union Referendum (“Brexit”) 70 and the 2016 US elections 71 . Clearly, understanding the shift from real‐world interactions into the online social environment (and vice versa) holds significance to almost all aspects of people's lives.

Our motivations towards using social media is broadly similar to the instinctual desires underlying “real world” social interactions, as people are drawn to online sociality in order to exchange information and ideas, along with gaining social support and friendships 72 . However, whether or not these virtual interactions engage the human brain in ways analogous to real‐world socialization remains a topic of debate since the turn of the century 73 . Whereas it would be highly beneficial if social media sites could fulfil the implicit human needs for social connection, it may be that the distinction between online and offline networks is so great that entirely different cognitive domains are involved in navigating these different environments 74 , 75 .

How does the online environment affect our fundamental social structures?

To investigate the neuroimaging correlates of offline and online networks, the seminal study by Kanai et al 74 collected real‐world social network size, online sociality (i.e., Facebook friends) and magnetic resonance imaging scans from 125 participants. Results showed that both real‐world social network size and number of Facebook friends were significantly associated with amygdala volume. As this has previously been established as a key brain region for social cognition and social network size 76 , these results present a strong case for the overlap between online and offline sociality in the human brain.

However, those authors also found that the grey matter volume of other brain regions (specifically, posterior regions of the middle temporal gyrus and superior temporal sulcus, and the right entorhinal cortex) were predicted by the numbers of participants’ Facebook friends, but held no relationship to their real‐world social networks. This suggests that certain unique aspects of social media implicate aspects of the brain that are not central in “real‐world” social settings. For instance, the tendency for online networks to encourage us towards holding many weak social connections, involving thousands of face‐to‐name pairs, could require high associative memory capacities, which is not typically required in real‐world networks (as these are comprised of fewer, but more familiar, relationships) 74 . As associative memory formation for name‐face pairs involves the right entorhinal cortex 77 , 78 , this could explain the exclusive relationship that this region holds with online social (but not real‐world) network size 74 .

Indeed, one key difference which may separate how the brain handles online and offline social networks is the unique capacity afforded by the Internet for people to hold, and simultaneously interact with, millions of “friendships” 79 , 80 . Empirical testing of this hypothesis is a most fruitful area of investigation stemming from research into the fundamental similarities and differences between these two social worlds at a biological level 66 . When defining “friendships” under a broad context (people who maintain contact and share an emotional bond) 66 , two patterns are prominent across a diverse range of real‐world social networks: a) the average individual has around 150 “friendships” (but this is highly variable between individuals), and b) this is made up of five hierarchical layers, consisting of primary partners, intimate relationships, best friends, close friends, and all friends, which follow a size‐scaling ratio of around 3 (i.e., each cumulative layer is 3 times bigger than the last), and therefore have set average (cumulative/inclusive) sizes of 1.5, 5, 15, 50 and 150 respectively 66 . The patterns of the average number of 150 total friendship connections, and the scaling sizes of the five hierarchical layers of relationships making this up, have been found across regions and time periods within various human organizations, ranging from hunter‐gatherer societies 81 , 82 and historical village populations 83 , armies 66 , residential camps 84 , to personal networks of modern Europeans 85 .

Thus, given the unprecedented potential that online social networks allow in terms of number of connections, and the varied contexts these take place over 79 , 80 , it is imaginable that this extraordinary environment may allow these two apparently set aspects of real‐world social networks to be bypassed. However, recent findings have confirmed that user‐to‐user friendship connections, posting patterns and exchanges within Twitter, Facebook, and even online gaming platforms, all indicate a similar average number of general friendships (around 150, despite high skew), along with maintaining the same scaled sizes of the hierarchical structure of the five distinct friendship layers (as determined by reciprocal communication exchanges) 86 , 87 , 88 , 89 . Therefore, even within the unique realms of online social networks, the most fundamental operations of human social networks appear to remain relatively unchanged 88 , 89 . So, it is highly conceivable that the social connections formed in the online world are processed in similar ways to those of the offline world, and thus have much potential to carry over from the Internet to shape “real‐world” sociality, including our social interactions and our perceptions of social hierarchies, in ways that are not restricted to the context of the Internet.

The driving forces that sustain the set structural patterns of social networks, even when faced with the immense connective potential of the online world, may be broadly explained by two overlapping mechanisms. First, constraints on social cognition within the human brain seem to carry over across social contexts 66 . For instance, humans struggle to engagingly interact with more than three individuals simultaneously in the real world, and this limitation on attention also appears to apply online 90 , 91 . This evidence is in agreement with the hypothesis that circumventing the cognitive constraints on social relationships may be difficult even when technology affords unnatural opportunities to do so 88 .

The second driver of set boundaries on social activity is that simple underlying factors may produce social constraints, even within online settings. Most obviously, investment in social relationships is limited by time constraints, and this may contribute to the set patterns of both the number and type of social connections 93 , 94 . In line with this, analyses across various social contexts have shown that temporal limitations govern the number of social interactions that individuals engage in, and how they distribute these across their different kinds of relationships 93 , 94 . Again, these general interaction rates remain similar within online social networks 87 , 88 .

The possibility that the parameters on all social networks (online or offline) are governed by basic underlying factors is further supported by research showing that similar structures also exist within simpler social systems, such as animal societies 66 , 95 . For instance, the sizes and scaling of hierarchical “friendship” layers found in online and offline human networks are also found in dolphins, elephants, and various primate species 96 , and the phenomena of humans increasing the number and strength of their social networks connections following the death of a friend on Facebook 97 is also seen in wild birds, which show compensatory up‐regulation of their social network connections upon experiencing the loss of a social associate 98 .

Supporting the idea that limited cognitive capacities govern our social structures is research showing that the brain regions predicting individual variation in social network size in humans also do so for macaques 99 . Strong support for simple underlying factors (such as time) governing our general patterning of social interactions can be found in studies demonstrating that entirely computationally simulated systems replicate some of the apparent complexities of human social networks, even under relatively simple rules 100 , 101 . Examples include agent‐based models generating similar social layering structures as humans when sociality is defined as time‐limited 100 .

In light of the current evidence regarding how the Internet may have affected human thinking surrounding social networks, it is undeniable that the online environment poses unique potential and context for social activity 79 , 80 , 102 , 103 , which may invoke some non‐identical cognitive processes and brain areas in comparison to the offline world 74 , 75 . Nevertheless, aside from these comparatively fine‐scale differences, it appears that our brains process the online and offline social networks in surprisingly similar ways, as demonstrated by the shared cognitive capacities and simple underlying factors ultimately governing their fundamental structure 87 , 88 . As such, the online social world has very significant implications for not only measuring and understanding human sociality, but also for governing the outcomes of social processes across various aspects of life.

Social cognitive responses to the online social world

Given the evidence above, an appropriate metaphor for the relationship between online and real‐world sociality could be a “new playing field for the same game” . Even beyond the fundamental structure, emerging research suggests that neurocognitive responses to online social occurrences are similar to those of real‐life interactions. For instance, being rejected online has been shown to increase activity in brain regions strongly linked with social cognition and real‐world rejection (medial prefrontal cortex 104 ) in both adults and children 105 , 106 , 107 . However, within the “same old game” of human sociality, online social media is bending some of the rules – potentially at the expense of users 17 . For instance, whereas real‐world acceptance and rejection is often ambiguous and open to self‐interpretation, social media platforms directly quantify our social success (or failure), by providing clear metrics in the form of “friends” , “followers” , and “likes” (or the potentially painful loss/absence of these) 107 . Given the addictive nature of this immediate, self‐defining feedback, social media companies may even capitalize upon this to maximally engage users 17 . However, growing evidence indicates that relying on online feedback for self‐esteem can have adverse effects on young people, particularly those with low social‐emotional well‐being, due to high rates of cyberbullying 108 , increased anxiety and depression 109 , 110 , and increased perceptions of social isolation and exclusion among those who feel rejected online 111 .

Another process common to human social behaviour in both online and offline worlds is the tendency to make upward social comparisons 112 , 113 . Whereas these can be adaptive and beneficial under regular environmental conditions 112 , this implicit cognitive process can also be hijacked by the artificial environmental manufactured on social media 113 , 114 , which showcases hyper‐successful individuals constantly putting their best foot forward, and even using digital manipulation of images to inflate physical attractiveness. By facilitating exposure to these drastically upward social comparisons (which would rarely be encountered in everyday life), online social media can produce unrealistic expectations of oneself – leading to poor body image and negative self‐concept, particularly for younger people 107 , 111 , 115 , 116 . For instance, in adolescents (particularly females), those who spent more time on social media and smartphones have a greater prevalence of mental health problems, including depression, than those who spent more time on “non‐screen” activities 116 , with greater than 5 hrs/day (versus 1 hr/day) associated with a 66% increased risk of one suicide‐related outcome 117 .

However, a causal relationship between high levels of social media use and poorer mental health is currently difficult to establish, as there is most likely a complex interaction between several confounding factors, including reduced sleep and in‐person social interaction, and increased sedentary behaviour and perceived loneliness 116 , 118 . Nonetheless, given the large amounts of social media use observed among young people, future research should thoroughly examine the potentially detrimental effects that this new setting for sociality may have on health and well‐being, along with aiming to establish the driving factors – such that adjustments can be made in subsequent iterations of social media in order to produce more positive outcomes.

Whereas young people with mental disorders may be the most vulnerable to negative input from social media, these media may also present a new platform for improving mental health in this population, if used correctly. In future, social media may also be exploited to promote ongoing engagement with Internet‐based interventions, while addressing key (but frequently neglected) targets such as social connectedness, social support and self‐efficacy, to aim to bring about sustained functional improvements in severe and complex mental health conditions 119 . To achieve these goals, online social media‐based interventions need to be designed to promote engagement by harnessing, in an ethical and transparent manner, effective strategies used by the industry. For instance, developing technologies which are increasingly adopted by online marketing and tech companies, such as natural language processing, sentiment analyses and machine learning, could be capitalized upon, for example making it possible to identify those at increased risk for suicide or relapse 120 , and rationalizing human driven support to those who need it most at the time they need it 121 . In addition, online systems will be able to learn from what helps individuals and when, opening a window into personalized, real time interventions 121 .

While the use of online social media‐based interventions is in its infancy, pioneering efforts indicate that these interventions are safe, engaging, and have the potential to improve clinical and social outcomes in both patients and their relatives 122 , 123 , 124 , 125 , 126 , 127 . That said, online interventions have failed up to now to be adopted by mental health services 128 , 129 . The main reasons include high attrition rates, poor study designs which reduce translational potential, and a lack of consensus around the required standards of evidence for widespread implementation of Internet‐delivered therapies 130 , 131 , 132 . Efforts are currently underway to determine the long‐term effects of the first generation of social media‐based interventions for mental illness via large randomized controlled trials 133 , 134 . Alongside this clinical use, developing public health strategies for young adults in the general population to avoid the potential adverse effects and negative aspects of typical social media are also warranted.

CONCLUSIONS AND DIRECTIONS

As digital technologies become increasingly integrated with everyday life, the Internet is becoming highly proficient at capturing our attention, while producing a global shift in how people gather information, and connect with one another. In this review, we found emerging support for several hypotheses regarding the pathways through which the Internet is influencing our brains and cognitive processes, particularly with regards to: a) the multi‐faceted stream of incoming information encouraging us to engage in attentional‐switching and “multi‐tasking” , rather than sustained focus; b) the ubiquitous and rapid access to online factual information outcompeting previous transactive systems, and potentially even internal memory processes; c) the online social world paralleling “real world” cognitive processes, and becoming meshed with our offline sociality, introducing the possibility for the special properties of social media to impact on “real life” in unforeseen ways.

However, with fewer than 30 years since the Internet became publicly available, the long‐term effects have yet to be established. Within this, it seems particularly important that future research determines the impact of the Internet on us throughout different points in the lifespan. For instance, the Internet's digital distractions and supernormal capacities for cognitive offloading seem to create a non‐ideal environment for the refinement of higher cognitive functions in critical periods of children and adolescents’ brain development. Indeed, the first longitudinal studies on this topic have found that adverse attentional effects of digital multi‐tasking are particularly pronounced in early adolescence (even compared to older teens) 34 , and that higher frequency of Internet use over 3 years in children is linked with decreased verbal intelligence at follow‐up, along with impeded maturation of both grey and white matter regions 135 .

On the other hand, the opposite may be true in older adults experiencing cognitive decline, for whom the online environment may provide a new source of positive cognitive stimulation. For instance, Internet searching engaged more neural circuitry than reading text pages in Internet savvy older adults (aged 55‐76 years) 9 . Furthermore, experimental studies have found that computer games available online and through smartphones can be used to attenuate aging‐related cognitive decline 136 , 137 , 138 . Thus, the Internet may present a novel and accessible platform for adults to maintain cognitive function throughout old age. Building from this, successful cognitive aging has previously been shown to be dependent upon learning and deploying cognitive strategies, which can compensate for aging‐related decline in “raw” memory capacities 139 . This has previously been referred to as optimizing internal cognitive processes (e.g., through mnemonic strategies), or taking advantage of cognitive offloading in traditional formats (list making, transactive memory, etc.) 139 . Nonetheless, as Internet‐based technologies become more deeply integrated with our daily cognitive processing (through smartphones, wearables, etc.), digital natives could feasibly develop forms of “online cognition” in the aging brain, whereby older adults can increasingly take advantage of web‐based transactive memory and other emerging online processes to fulfil (or even exceed) the typical capacities of a younger brain.

Although it is an emerging area of study, the same could apply for social aspects of the online world. Whereas young people seem particularly prone to the rejections, peer pressure, and negative appraisals this world may induce 107 , older adults may ultimately be able to harness social media in order to overcome isolation and thus continue to benefit from the diverse range of physical, mental and neurocognitive benefits associated with social connection 73 . Viewed collectively, the nascent research in this area already indicates that equivalent types of Internet usage may have differential effects on individuals’ cognitive and social functioning depending on their point in the lifespan.

For better or for worse, we are already conducting a mass‐scale experiment of extensive Internet usage across the global population. A more fine‐scale analysis is essential to gaining a fuller understanding of the sustained impact of this usage across our society. This could include measuring frequency, duration and types of Internet usage as a standard part of national data projects, for instance through collecting Internet data (from either device‐based or self‐report measures) in “biobank” assessment protocols. Combining this with the extensive genetic, socio‐demographic, lifestyle and neuroimaging data gathered by some ongoing projects, researchers could be able to establish the impact of Internet usage on psychological well‐being and brain functioning across entire populations (rather than the currently limited study samples), while also controlling for multiple confounders.

Overall, this early phase of the Internet's introduction into our society is a crucial period for commencing rigorous and extensive research into how different types of Internet usage interact with human cognition, in order to maximize our opportunities for harnessing this new tool in a beneficial manner, while minimizing the potentially adverse effects.

ACKNOWLEDGEMENTS

J. Firth is supported by a Blackmores Institute Fellowship. J. Sarris is supported by an Australian National Health and Medical Research Council (NHMRC) Clinical Research Fellowship (APP1125000). B. Stubbs is supported by the Health Education England and the National Institute for Health Research Integrated Clinical Academic Programme Clinical Lectureship (ICA‐CL‐2017‐03‐001). G.Z. Steiner is supported by an NHMRC‐Australian Research Council (ARC) Dementia Research Development Fellowship (APP1102532). M. Alvarez‐Jimenez is supported by an NHMRC Career Development Fellowship (APP1082934). C.J. Armitage is supported by National Institute for Health Research (NIHR) Manchester Biomedical Research Centre and NIHR Greater Manchester Patient Safety Translational Research Centre. The views expressed in this paper are those of the authors and not necessarily those of the above‐mentioned entities.

Social Cognitive and Addiction Neuroscience Lab at the University of Iowa

Research in the scanlab.

Research projects in the UIOWA Social Cognitive and Addiction Neuroscience Lab generally focus on one of the following areas:

The role of cognitive control in social behavior

Effects of alcohol on cognitive control 

Individual differences in neurobiologically based risks for addiction, primarily alcohol use disorder

Effects of incidental stimulus exposure on cognition and behavior (i.e., priming effects). 

The common theme around which these lines of work are integrated is the interplay between salience (i.e., motivational significance) and cognitive control (see Inzlicht, Bartholow, & Hirsch, 2015 ).

Salience, Cognitive Control, and Social Behavior

The interaction of salience and cognitive control is an enduring area of interest in the SCANlab, going back to Dr. Bartholow’s undergraduate days. In his undergraduate senior honors thesis, Dr. Bartholow found that participants asked to read résumés later recalled more gender-inconsistent information about job candidates. This general theme carried through to Dr. Bartholow’s dissertation research, in which he used event-related brain potentials (ERPs) to examine the neurocognitive consequences of expectancy violations. In that study, expectancy-violating behaviors elicited a larger P3-like positivity in the ERP and were recalled better compared to expectancy-consistent behaviors ( Bartholow et al., 2001 , 2003 ). Back then, we interpreted this effect as evidence for context updating (the dominant P3 theory at the time). As theoretical understanding of the P3 has evolved, we now believe this finding reflects the fact that unexpected information is salient, prompting engagement of controlled processing (see Nieuwenhuis et al., 2005 ).

Our research has been heavily influenced by cognitive neuroscience models of the structure of information processing, especially the continuous flow model ( Coles et al., 1985 ; Eriksen & Schultz, 1979) and various conflict monitoring theories (e.g., Botvinick et al., 2001 ; Shenhav et al., 2016 ). In essence, these models posit (a) that information about a stimulus accumulates gradually as processing unfolds, and (b) as a consequence, various stimulus properties or contextual features can energize multiple, often competing responses simultaneously, leading to a need to engage cognitive control to maintain adequate performance. This set of basic principles has influenced much of our research across numerous domains of interest (see Bartholow, 2010 ).

Applied to social cognition, these models imply that responses often classified as “automatic” (e.g., measures of implicit attitudes) might be influenced by control. We first tested this idea in the context of a racial categorization task in which faces were flanked by stereotype-relevant words ( Bartholow & Dickter, 2008 ). In two experiments, we found that race categorizations were faster when faces appeared with stereotype-congruent versus –incongruent words, especially when stereotype-congruent trials were more probable. Further, the ERP data showed that that this effect was not due to differences in the evaluative categorization of the faces (P3 latency), but instead reflected increased response conflict (N2 amplitude) due to partial activation of competing responses (lateralized readiness potential; LRP) on stereotype-incongruent trials. A more recent, multisite investigation (funded by the National Science Foundation ) extended this work by testing the role of executive cognitive function (EF) in the expression of implicit bias. Participants (N = 485) completed a battery of EF measures and, a week later, a battery of implicit bias measures. As predicted, we found that expression of implicit race bias was heavily influenced by individual differences in EF ability ( Ito et al., 2015 ). Specifically, the extent to which bias expression reflected automatic processes was reduced as a function of increases in general EF ability.

Another study demonstrating the role of conflict and control in “implicit” social cognition was designed to identify the locus of the affective congruency effect ( Bartholow et al., 2009 ), wherein people are faster to categorize the valence of a target if it is preceded by a valence-congruent (vs. incongruent) prime. This finding traditionally has been explained in terms of automatic spreading of activation in working memory (e.g., Fazio et al., 1986 ). By measuring ERPs while participants completed a standard evaluative priming task, we showed (a) that incongruent targets elicit response conflict; (b) that the degree of this conflict varies along with the probability of congruent targets, such that (c) when incongruent targets are highly probable, congruent targets elicit more conflict (also see Bartholow et al., 2005 ); and (d) that this conflict is localized to response generation processes, not stimulus evaluation.

Salience, Cognitive Control, and Alcohol

Drinking alcohol is inherently a social behavior. Alcohol commonly is consumed in social settings, possibly because it facilitates social bonding and group cohesion ( Sayette et al., 2012 ). Many of the most devastating negative consequences of alcohol use and chronic heavy drinking also occur in the social domain. Theorists have long posited that alcohol’s deleterious effects on social behavior stem from impaired cognitive control. Several of our experiments have shown evidence consistent with this idea, in that alcohol increases expression of race bias due to its impairment of control-related processes ( Bartholow et al., 2006 , 2012 ).

But exactly how does this occur? One answer, we believe, is that alcohol reduces the salience of events, such as a control failure (i.e., an error), that normally spur efforts at increased control. Interestingly, we found ( Bartholow et al., 2012 ) that alcohol does not reduce awareness of errors, as others had suggested ( Ridderinkhof et al., 2002 ), but rather reduces the salience or motivational significance of errors. This, in turn, hinders typical efforts at post-error control adjustment. Later work further indicated that alcohol’s control-impairing effects are limited to situations in which control has already failed, and that recovery of control following errors takes much longer when people are drunk ( Bailey et al., 2014 ). Thus, the adverse consequences people often experience when intoxicated might stem from alcohol’s dampening of the typical “affect alarm,” seated in the brain’s salience network (anterior insula and dorsal anterior cingulate cortex), which alerts us when control is failing and needs to be bolstered ( Inzlicht et al., 2015 ).

Incidental Stimulus Exposure Effects

A fundamental tenet of social psychology is that situational factors strongly affect behavior. Despite recent controversies related to some specific effects, we remain interested in the power of priming, or incidental stimulus exposure, to demonstrate this basic premise. We have studied priming effects in numerous domains, including studies showing that exposure to alcohol-related images or words can elicit behaviors often associated with alcohol consumption, such as aggression and general disinhibition.

Based on the idea that exposure to stimuli increases accessibility of relevant mental content ( Higgins, 2011 ), we reasoned that seeing alcohol-related stimuli might not only bring to mind thoughts linked in memory with alcohol, but also might instigate behaviors that often result from alcohol consumption. As an initial test of this idea, in the guise of a study on advertising effectiveness we randomly assigned participants to view magazine ads for alcoholic beverages or for other grocery items and asked them to rate the ads on various dimensions. Next, we asked participants if they would help us pilot test material for a future study on impression formation by reading a paragraph describing a person and rating him on various traits, including hostility. We reasoned that the common association between alcohol and aggression might lead to a sort of hostile perception bias when evaluating this individual. As predicted, participants who had seen ads for alcohol rated the individual as more hostile than did participants who had seen ads for other products, and this effect was larger among people who had endorsed (weeks previously) the notion that alcohol increases aggression ( Bartholow & Heinz, 2006 ). Subsequently, this finding has been extended to participants’ own aggression in verbal ( Friedman et al., 2007 ) and physical domains ( Pedersen et al., 2014 ), and has been replicated in other labs (e.g., Bègue et al., 2009 ; Subra et al., 2010 ).

Of course, aggression is not the only behavior commonly assumed to increase with alcohol. Hence, we have tested whether this basic phenomenon extends into other behavioral domains, and found similar effects with social disinhibition ( Freeman et al., 2010 ), tension-reduction (Friedman et al., 2007), race bias ( Stepanova et al., 2012 , 2018 a, 2018 b), and risky decision-making (Carter et al., in prep.). Additionally, it could be that participants are savvy enough to recognize the hypotheses in studies of this kind when alcohol-related stimuli are presented overtly (i.e., experimental demand). Thus, we have also tested the generality of the effect by varying alcohol cue exposure procedures, including the use of so-called “sub-optimal” exposures (i.e., when prime stimuli are presented too quickly to be consciously recognized). Here again, similar effects have emerged (e.g., Friedman et al., 2007; Loersch & Bartholow, 2011 ; Pedersen et al., 2014).

Taken together, these findings highlight the power of situational cues to affect behavior in theoretically meaningful ways. On a practical level, they point to the conclusion that alcohol can affect social behavior even when it is not consumed, suggesting, ironically, that even nondrinkers can experience its effects.

Aberrant Salience and Control as Risk Factors for Addiction

Salience is central to a prominent theory of addiction known as incentive sensitization theory (IST; e.g., Robinson & Berridge, 1993 ). Briefly, IST posits that, through use of addictive drugs, including alcohol, people learn to pair the rewarding feelings they experience (relaxation, stimulation) with various cues present during drug use. Eventually, repeated pairing of drug-related cues with reward leads those cues to take on the rewarding properties of the drug itself. That is, the cues become infused with incentive salience, triggering craving, approach and consummatory behavior.

Research has shown critical individual differences in vulnerability to attributing incentive salience to drug cues, and that vulnerable individuals are at much higher risk for addiction. Moreover, combining incentive sensitization with poor cognitive control (e.g., during a drinking episode) makes for a “potentially disastrous combination” ( Robinson & Berridge, 2003 , p. 44). To date, IST has been tested primarily in preclinical animal models. Part of our work aims to translate IST to a human model.

In a number of studies over the past decade, we have discovered that a low sensitivity to the effects of alcohol (i.e., needing more drinks to feel alcohol’s effects), known to be a potent risk factor for alcoholism, is associated with heightened incentive salience for alcohol cues. Compared with their higher-sensitivity (HS) peers, among low-sensitivity (LS) drinkers alcohol-related cues (a) elicit much larger neurophysiological responses ( Bartholow et al., 2007 , 2010 ; Fleming & Bartholow, in prep.); (b) capture selective attention ( Shin et al., 2010 ); (c) trigger approach-motivated behavior ( Fleming & Bartholow, 2014 ); (d) produce response conflict when relevant behaviors must be inhibited or overridden by alternative responses ( Bailey & Bartholow, 2016 ; Fleming & Bartholow, 2014), and (e) elicit greater feelings of craving (Fleming & Bartholow, in prep.; Piasecki et al., 2017 ; Trela et al., in press). These findings suggest that LS could be a human phenotype related to sign-tracking , a conditioned response reflecting susceptibility to incentive sensitization and addiction ( Robinson et al., 2014 ).

Recently, our lab has conducted two major projects designed to examine how the incentive salience of alcohol-related cues is associated with underage drinking. One such project, funded by the National Institute on Alcohol Abuse and Alcoholism (NIAAA; R01-AA020970 ), examined the extent to which pairing beer brands with major U.S. universities enhances the incentive salience of those brands for underage students. Major brewers routinely associate their brands with U.S. universities through direct marketing and by advertising during university-related programming (e.g., college sports). We tested whether affiliating a beer brand with students’ university increases the incentive salience of the brand, and whether individual differences in the magnitude of this effect predict changes in underage students’ alcohol use. We found (a) that P3 amplitude elicited by a beer brand increased when that brand was affiliated with students’ university, either in a contrived laboratory task or by ads presented during university-related sports broadcasts; (b) that stronger personal identification with the university increased this effect; and (c) that variability in this effect predicted changes in alcohol use over one month, controlling for baseline levels of use ( Bartholow et al., 2018 ).

A current project, also funded by the NIAAA ( R01-AA025451 ), aims to connect multiple laboratory-based measures of the incentive salience of alcohol-related cues to underage drinkers’ reports of craving, alcohol use, and alcohol-related consequences as they occur in their natural environments. This project will help us to better understand the extent to which changes in drinking lead to changes in alcohol sensitivity and to corresponding changes in the incentive salience of alcohol-related cues.