Forms of Reasoning: Insight into Prefrontal Functions?a

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Forms of Reasoning: Insight into Prefrontal Functions?“

KEITH J. HOLYOAK AND JAMES K. KROGER Deprirtmrnt o j Psychology and Brci in Reseurch Institute

University of Cdiforni i i , Los Angelrs Los Angele.5. Cdifiwtiiri 90095

INTRODUCTION

The faculties that have historically been attributed to the prefrontal cortex on the basis of clinical and neuropsychological studies parallel the mental abilities traditionally called “higher cognitive functions” by cognitive psychologists. The frontal lobes appear to be directly involved in such important cognitive tasks as planning, problem solving, and determination of social behavior.’-’ At the same time, patients with frontal damage often remain capable of performing within nor- mal limits on standard intelligence tests. Frontal deficits appear to be both broad in scope and yet selective in important ways, suggesting that models of frontal function could provide important constraints on theories of human cognition.

Nonetheless, only a loose correspondence exists between the recent work of cognitive psychologists on reasoning and brain research, including both clinical studies of the effects of brain damage and neurophysiological studies. Although connectionist models inspired by brain structure have been proposed as models of mechanisms underlying high-level cognition, cognitive theories of reasoning have typically not been based on data from brain research. Conversely, neuropsychological investigations of brain damage seek to specify the contributions of different neural regions to complex human cognition, but their conceptions of high-level cognition are often very general and fail to reflect the intricacies of the cognitive mechanisms involved. This gap is likely attributable to the difficulty neuroscientists have had in formulating detailed descriptions of neural operations in association areas.

Clinical researchers as well as cognitive psychologists have been concerned with such varieties of thinking as deductive and inductive inference, categoriza- tion, judgment and decision making, and problem solving. Thinking, unlike vision and language, has generally been viewed as nonmodular and hence unlikely to be tightly localized in the brain. Human reasoning appears to be in many respects more complex and variegated than the types of conditional responding typically investigated in primate work on frontal functions. Many of the major theoretical constructs that have been influential in cognitive models of thinking-for example, schemas, mental models, and condition-action rules-have not been defined in a way that can be readily related to brain mechanisms. In this paper we sketch some possible links between models of human thinking and models of frontal functions.

This work was supported by National Science Foundation grant SBR-9310614. 253

254 ANNALS NEW YORK ACADEMY OF SCIENCES

Are there particular varieties of thinking and reasoning that selectively depend on brain mechanisms realized in prefrontal cortex? Are there characteristics of the reasoning process that correlate with the emerging picture of neural operation in the frontal lobes? Our aim is limited to exploring how these questions might be developed, rather than proposing any firm answers.

FUNCTIONS OF PREFRONTAL CORTEX

Different models of prefrontal cortex have emphasized a number of major cognitive functions it may subserve, including executive control, various forms of behavioral inhibition, temporal ordering, and working memory. Perhaps the most general description of the overall function of the frontal system is that it serves to mediate behavioral responses to complex environmental contingencies in the absence of control by direct and immediate perceptual This function may involve maintaining an association across time to permit successful matching of a proper response to a stirnulus,'.l0 or the monitoring of a condition so that an appropriate response may be made. I ' Meditation of contingencies involves the frontal lobes when behavior must be directed in the absence of guiding environmental C U ~ S . ~ , ~ ~ In particular, the dorsolateral area (Brodmann's area 46) appears to be responsible for maintaining a representation needed to mediate contingencies across time, after the stimulus being responded to has been withdrawn. It has been shown that subareas within this region are differentially responsible for maintaining representations of identity" and spatial position.14 Other tasks that are frontal-dependent do not require stimulus representations to be actively main- tained in working memory; rather, stimuli are monitored and conditional rules must be retrieved from long-term memory and applied so that behavior is deter- mined by internal mediation and application of contingencies."

It is clear that many high-level cognitive tasks performed by humans depend on behavioral responses controlled by contingencies remote from immediate perceptual cues. Indeed, the most distinctively human cognitive activities include hypothetical reasoning, long-term planning, manipulation of abstract concepts, and internal reorganization of knowledge-activities that require systematic application of internally controlled knowledge. How can performance on such tasks be related to frontal functions? One general approach to delineating the neural substrate of a particular kind of higher cognition is to analyze complex tasks in terms of the simpler cognitive components that comprise it. Working memory is a prime example of a basic cognitive function that has been convincingly associated with a particular brain region and characteristic activity of that r e g i ~ n . ~ . ~ . ~ ~ , ' ~ Reasoning tasks inevitably require the maintenance of a representation of that which is reasoned about; it is likely that this function depends on working memory and the neural substrates that have been shown to underlie it.lS We would therefore expect reasoning tasks to evoke activation in the dorsolateral r e g i ~ n . ' . ~ , ~ ~ Further, based on evidence of topographical distribution of working memory function for different kinds of content (serial order, spatial, and object identity) across subareas of dorsolateral cortex,I6 we might expect to find neurological correlates that are

HOLYOAK & KROGER: FORMS OF REASONING 255

selective for specific types of reasoning content. It is certainly the case that content can have dramatic effects on reasoning and problem solving.”

Similarly, attention is almost certainly required for focusing on the various items reasoned about; some of the neural structures associated with attention have been Carefully designed reasoning experiments should produce activation of some or all of the brain regions responsible for such basic cognitive functions as working memory and attention. By systematically varying the task, it may be possible to learn the role each component plays in reasoning, and how the ability to reason results from the cooperative operation of the components.

Nonetheless, the details of how component mechanisms yield complex thought remain to be specified. Understanding the interaction of systems of specialized brain regions is an essential step, but ultimately we need to know not only that a particular brain region is responsible for a certain cognitive component, but also how it performs its specialization in concert with other regions. At the present time we have only a sketchy understanding of either the system level of brain organization or the neurophysiological underpinnings of component mechanisms.

Thinking is an adaptive evolutionary response to the challenges of survival, incorporating the ability to apprehend the environment and to mediate representations of it in an organized and purposeful manner. At the more abstract level of cognitive theories, work has focused on describing such representations and on revealing the mechanisms of their manipulation. In the remainder of this paper we will consider some general properties of human thinking and how they might be connected to frontal functioning.

SOME COGNITIVE COMPONENTS OF HUMAN THINKING

Symbols and Variables

Robin and Holyoak” argued that the diverse tasks that reveal impairment after frontal damage, including planning, sequencing of actions, using context to modu- late social behavior, learning contingencies between spatiotemporally separate stimuli and responses, and forming flexible categories, all share a common requirement: the need to bind independently varying elements to specific roles with respect to relations. This point of view suggests that the frontal cortex plays an important role in the development of explicit representations of knowledge, which allow systematic manipulation of symbols. The acquisition of explicit knowledge appears to be based on slow, effortful, and conscious processing that is directly dependent on working memory, and contrasts with implicit knowledge based on relatively rapid, effortless, and unconscious processing.

One of the key contributions of modern connectionism has been demonstrations that many varieties of intelligent behavior do not necessarily depend on either symbols or rules.22 However, these demonstrations have led to refined arguments that a subset of human (and possibly other primate) knowledge is indeed symbolic. The most fundamental argument for the necessity of symbolic representations in human cognition was presented by Fodor and Py ly~hyn ,*~ who pointed out that knowledge is systemutic in the sense that the ability to think particular thoughts


seems to imply the ability to think certain related thoughts. For example, if a person understands the meaning of the concepts “love,” “boy,“ and “girl,” and can understand the proposition “The boy loves the girl,” then it would seem extremely bizarre if the person were nonetheless unable to understand the proposition “The girl loves the boy.” Such systematic reasoning with composable constituents requires symbols. A “symbol,” fundamentally, is a locally available code that can provide access to distal information relevant to a task. In a symbol system, information acquired in one task context has the potential to be made available in a different task context. Knowledge is symbolic, in this sense, when it can be decoupled from a particular context. In our example above, we can understand both “the boy loves the girl” and “the girl loves the boy” because the concepts “girl” and “boy” are represented in a manner that keeps each distinct from both the “lover” and “beloved” contexts, and therefore potentially available for use in either context. This notion of a symbol being separate from, yet composable with, a given context may be related to evidence that frontal damage can impair both modulation of performance by the ~ o n t e x t ’ ~ and memory for the spatiotempo- raI context of events.25

Systematicity is related to the use of rules of inference, such as “If X sells Y to Z, then Z owns Y.” Smith rt cil.” argue that several empirical criteria can be used to demonstrate that some knowledge used in human reasoning is coded as abstract rules. One criterion is that it seems just as easy to draw inferences about unfamiliar instantiations-including nonsense ones-as about familiar ones. Thus if we are told that “Henry sold the floogle to Sam,” we conclude that Sam now owns the floogle (whatever that might be). The inference follows directly from the role that “floogle” plays in the argument structure of the rule, without any requirement that floogles somehow resemble familiar objects that have been sold and then owned by someone else.

Perhaps, then, the human frontal cortex is selectively involved in encoding and manipulating explicit symbolic knowledge, which is based o n a predicate-argument (or slot-filler) structure. A key requirement for representing a proposition with a systematic slot-filler structure is that its constituents must be kept distinct, yet interrelated, by creating a set of bindings between the arguments of the proposition and the case roles they fill. Although controversial, there is some neurophysiological evidence that some aspects of perception, as well as the representation and manipulation of information in the frontal lobes, may be accomplished via synchro- nized neural o~c i l l a t ions .~~-~’ Particular components of the total representation may consist of groups of distributed neurons with phase-locked firing oscillations. A representation held in working memory involves not only dorsolateral prefrontal cortex, but also the modality-specific sensory areas and association areas that enable perception of such One may envision a distributed network of frontal and sensory brain regions, the activation of which is controlled by area 46, such that their collective activity would constitute the construction and maintenance of propositional representations.

Hummel and colleague^^^^^' have used a synchrony-based computational model to represent abstract propositions. Their model allows units representing roles to be temporarily bound to units representing the arguments of those roles by synchrony relations. The essential idea is that two or more units can indicate a binding


of the properties they represent (i.e., that the properties belong to the same entity or otherwise stand in correspondence) by firing in synchrony with one another. For example, love (boy, girl) could be represented by units for “boy” firing in synchrony with units for the agent role of “love,” with units for “girl” firing in synchrony with units for the patent role. The agentiboy units must fire out of synchrony with the patientigirl set. This simple mechanism provides a way to distinguish the representation of love (boy, girl) from the representation of love (girl, boy) without requiring separate units to represent the meaning of boy-us- agent-of-love and boy-as-patient-oj-low.

Relational Complexity and Analogical Mapping

It remains to be seen whether neural synchrony involving the frontal cortex plays a role in forming and manipulating propositions. However, regardless of the specific neural mechanisms, good grounds exist for supposing that the human brain is capable of distinguishing roles from their fillers. Robin and Holyoak,” adapting a taxonomy proposed by H a l f ~ r d , ~ ~ argued that the human frontal cortex has evolved to cope with role-filler relationships at increasing levels of complexity. Similar complexity analyses have been proposed both in work on primate intelligence” and human analogical reasoning.” One version of the complexity hierarchy distinguishes holistic representations, which do not involve representations of variables and presumably do not depend on frontal functions, from a series of levels of complexity based on predicate-argument structure. An attribute requires abstraction of a single dimension of variation, the minimal requirement for differ- entiating a role from its filler, as in

A relation connects two fillers to each other, as in

A higher-order relation takes a lower-order proposition as a filler, which makes it possible to define a relation between relations, as in

brown (dog) .

chase (dog, cat).

cause [chase (dog, cat) , r u n - w a y ( ca t ) ] . Holyoak and Thagard” have argued that these levels of relational complexity

are related to progressive increases in the abstraction of analogical mapping, both in evolution and in human cognitive development. Evidence from variations of the match-to-sample task suggests that language-trained chimpanzees can solve analogies on the basis of correspondences at the relational level, but probably not on the basis of higher-order relations.’’ Adult humans can readily find mappings based on higher-order relations.3x Mappings at this level are primarily constrained by consistency of role correspondences. For example, Aesop’s “sour grapes” fable (“A fox wanted some grapes, but couldn’t reach them, so announced to his friends that the grapes were sour anyway”) can be compared to the tale of a disgruntled job-seeker (“Harry hoped to get the new position of marketing man- ager, but was passed over, so he told his wife the job would have been boring”). The resulting correspondences are: fox (--) Harry, grapes (--)job, friends (--) wife. It is noteworthy that comprehension of fables at an abstract level appears to depend on brain regions that include part of the right prefrontal ~ o r t e x . ~ ’


Systematic relational correspondences also play a role in judgments of perceptual ~ i m i l a r i t y . ~ ~ - ~ ~ For example, suppose people are shown three pairs of geomet- ric shapes, with each pair arranged vertically. One pair consists of two identical triangles, one of identical squares, and one of identical circles. People tend to evaluate the pair of triangles as more similar to the pair of squares than to the pair of circles. But if a square is now added as a third form below the two items in each of the pairs, the relative similarity reverses: two triangles and a square are viewed as less similar to three squares than to two circles and a square. This similarity reversal reflects differences in relational correspondences: both the first and the third triad can readily be represented as “two same forms plus a square,” whereas the middle triad is most naturally represented as “three squares.” Thus, the first and third triads have a better match in terms of relational correspondences.

The evidence for relational influences on human analogical mapping and similarity judgments thus spans very different content and tasks, suggesting the possibility that the brain may support a “relational mapping module” based on explicit, structured representations. Although the possibility remains speculative, the prefrontal cortex may play an important role in the neural substrate for such a mechanism.

Human Conditional and Social Reasoning

Many forms of human reasoning appear to involve the representation and manipulation of contingencies (see ref. 17 for a review). In the area of deductive reasoning, the W a ~ o n ~ ~ selection task has been employed for almost three decades to investigate the factors affecting subjects’ success at solving a problem requiring manipulation of a conditional rule (e.g., refs. 43-45). In the standard “arbitrary” version of this task, subjects view four cards. They are also given a rule, such as, “If there is a vowel on one side of the card, then there must be an even number on the other side.” This rule has the logical form “If p then q.” Only the fronts of the cards are showing; in this example, either a number or a letter is on the face of each card. Subjects must choose, based on the rule and what is showing on each card, which cards need to be turned over in order to determine if the rule is violated. Only two of the cards need to be turned over: the cases corresponding to vowel (p) and odd number (not 9). However, only around 15% of subjects are successful in choosing these two cards; most select either the p case only, or the p and q cases.43

The Wason task is of particular interest for models of prefrontal functions because performance is greatly enhanced when the content taps into types of knowledge closely related to everyday social interactions, a type of knowledge that appears to depend on the integrity of ventromedial cortex, the medial portion of Brodmann’s area 11.4h.47 People are much more likely to select the “correct” alternatives for conditional rules that tap into knowledge about social regulations based on permission or ~ b l i g a t i o n . ~ ~ , ~ ~ - ” Cheng and H ~ l y o a k ~ ~ attributed the facil- itation due to social-regulation content to the application of pragmatic reasoning schemas, which are generalized sets of rules for assessing violation of and con- formity with social regulations. The application of such schemas may be expected


to be mediated by the frontal lobes, because making correct responses depends on fitting the correct rule from the schema to each card. The rules that comprise the schemas are in the form of contingencies; each card must be turned over only when what shows on its front indicates that it may match one of the relevant contingency rules. Successful performance depends on subjects’ correctly using these contingencies in relation to unobserved aspects of the environment (i.e., the hidden sides of the cards). It is possible that social regulations tap into portions of the frontal cortex specialized for making social inferences.

Is there a relation between the cognitive ability to perform relational mapping and the improvement of problem-solving efficacy when a logic problem is recast in terms of social rules of conduct for goal satisfaction? At one level, it is useful to ask how the components of a representation are bound together physically. At another level, it is useful to ask how the components of a representation are bound together functionally, because any representation that an organism bothers to maintain or manipulate likely has some functional significance. The structure of a representation can be guided by the goals or needs of the reasoner. A number of investigators have demonstrated that subjects will represent a problem differently depending on the perspective they are encouraged to take when reading the problem.”-54 For example, Holyoak and Cheng” administered a Wason selection task based on the rule, “If an employee works on the weekend, then that person gets a day off during the week.” The cards indicated people who had or had not worked on the weekend, and had or had not taken the day off. Subjects were to select cards representing people who might have violated the rule. The rule was presented in a context that encouraged the subject to view the problem from the perspective of either the employer or the employee. This particular rule is ambiguous with respect to which kind of deontic schema it corresponds: a permission or an obligation. The correct solution when the rule is viewed as an obligation is different from the solution when the problem is viewed as a permission. When the context favored viewing the problem from the employer’s point of view, the rule was interpreted as a conditional permission (if the employee worked on the weekend, the employee was permitted a day off); when viewed from the employee’s point of view, the same rule was best interpreted a s a conditional obligation (if the employee worked on the weekend, the employer was obliged to provide a day off). These different perspectives are correlated with different goals of the two actors, The employer’s goal is for his employees to work; the employee’s goal is to obtain time off. In both cases, the goals are defined by potential losses or benefits to one’s self. In this and similar experiments, the pattern of subjects’ card selections was reversed across the two perspective conditions.

Humans have a variety of needs that motivate their behavior. In acting to satisfy them, they must operate within a social milieu in which interactions are governed by rules of behavior. As mentioned, evidence suggests that damage to the basal forebrain interferes with patients’ ability to interact effectively in the social e n ~ i r o n m e n t . ~ ‘ - ~ ~ It is possible that this inability arises from difficulties in mapping one’s needs to a set of actions that would constitute an effective solution in conformance with rules of social interaction. We might expect patients with this type of damage to be deficient in the kind of reasoning that leads to the correct solution when a Wason selection task is presented in the form of a deontic


obligation or permission. The deficiency may lie in the failure to produce a relational mapping between the goal in the social context and the appropriate action- governing schema. Such a deficiency might be caused by an absence of a well- formulated goal, a lack of access to the action-governing schema, or a breakdown in the mapping process itself.

When a Wason selection task is presented that is not phrased in terms of a deontic permission or obligation, subjects’ poor performance may result from having no appropriate schemas in long-term memory to which the problem can be mapped. Conversely, clear social content may encourage binding the constituents of the rule to a relevant schema. It has been proposed that the frontal cortex and especially the basal forebrain give form to one’s needs and reactions to the environment, which are communicated from the limbic ~ y s t e m . ~ ~ , ~ ~ To the degree that we are social animals, it is sensible that reasoning about social interaction would be especially likely to bring these brain regions to bear on the problem. Not only might such activation make available schemas that permit problem solution, but it may also activate brain areas that support the binding process (e.g., dorsolateral prefrontal cortex). Emotional influences on ~ o g n i t i o n , ~ ~ . ~ ~ processing of social intera~tion,~’ and inhibition of incorrect responses12 have all been attributed to the basal forebrain. Perhaps these influences are functions of discrete cortical units within the larger area of inferior frontal cortex; however, it may be that different experimental paradigms have produced differing perspectives of what is a single contribution to higher cognitive function-the signifying of components of representations relevant to our goals. The resulting representation of a situation will constrain the solution which is mapped to it. However, the neurophysiological relation between the formulation of a problem representation and the mapping of its solution remains to be resolved.

CONCLUSION

Clearly, much remains to be learned about the neural underpinnings of complex human thought. We have pointed to a few aspects of human thinking-symbols and variables, relations and analogical mapping, and the content specificity of conditional reasoning-that may provide candidates for closer scrutiny of the role played by the prefrontal cortex. The promise of cognitive neuroscience is an understanding of how multiple cortical mechanisms act in concert to permit human behavior. Evidence from both behavioral and neural research will constrain future descriptions of higher cognitive function, so that our expanding ability to observe the brain in action will ultimately shape our understanding of human cognition.

ACKNOWLEDGMENT

We thank Franqois Boller for helpful comments on an earlier draft.

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Forms of Reasoning: Insight into Prefrontal Functions?a