Author's personal copy Reasoning and Problem Solving: Models 35 Reasoning and Problem Solving: Models A K Barbey and L W Barsalou, Emory University, which in turn can cause an avalanche, supports the Atlanta, GA, USA prediction that an avalanche is possible during winter. ã Finally, new predictions and explanations can be 2009 Elsevier Ltd. All rights reserved. generated by analogical reasoning, whereby relations from one domain are mapped onto another domain. For example, students can conceptualize particle Introduction motion in an atom through an analogy to the solar Neuroscience research has increasingly provided evi- system. dence that informs theories of reasoning. We begin by defining classic forms of reasoning; and summariz- Theoretical Perspectives on Reasoning ing psychological contemporary theories. We then in the Psychological Literature review empirical evidence from neuroscience that The psychological literature contains various theories bears on these theories. Finally, we summarize cur- rent challenges and identify promising areas for that address the cognitive architecture and symbolic future research. representations that underlie reasoning. After review- ing these theories, we turn to neuroscience evidence that bears on them. Definition and Types of Reasoning Cognitive Architecture Reasoning is a hallmark of human thought, support- ing the process of discovery that leads from what is One major distinction can be drawn between theories known or hypothesized, to what is unknown or that view the mind as containing specialized rea- implicit in one’s thinking. Reasoning can take the soning modules, versus theories that view the mind form ofdeductive inference, whereby the evidence as containing general-purpose reasoning systems. guarantees the truth of the conclusion. Alternatively, According to the modular view, the mind consists when reasoning depends on conditions of uncertainty, of specialized modules that are unavailable to con- it takes the form of inductive inference, whereby the scious awareness and deliberate control (cognitively evidence provides only limited support for the truth impenetrable), and that are only able to process of the conclusion. The deductive inference that a specific types of information (information encapsula- storm has emerged is supported by evidence that it is tion). Advocates of this view have proposed a diversity raining, whereas observing lightning clouds provides of modules that underlie reasoning, including modules only limited support for the inductive inference that for semantic inference, communicative pragmatics, it will rain. Many forms of reasoning typically depend social exchange, intuitive numbers, spatial relations, on conditions of uncertainty, including problem naive physics, and biomechanical motion. If cogni- solving, causal reasoning, and analogical inference. tive architecture emerges from an underlying neural Problem solving refers broadly to the inferential architecture, then strong modular views predict that steps that lead from a given state of affairs to a desired the neural systems for reasoning should be relatively goal state. For example, deciding who to vote for in a localized, implementing modules that are cognitively presidential election, diagnosing a patient on the basis impenetrable and informationally encapsulated. of observed symptoms, or preparing for a mountain Alternatively, dual-process theorists propose that climbing expedition all depend on problem solving. reasoning is based on two general-purpose systems: an Problem solving often requires the process of planning, associative system and a rule-based system. The asso- namely, formulating a method for attaining a desired ciative system uses basic cognitive operations such as goal state. Planning a mountain climbing expedition, association, similarity, and memory retrieval to pro- for example, requires scheduling the season of the duce primitive judgments quickly and unconsciously. expedition by predicting the consequences of taking The rule-based system reflects more evolutionarily the trip during different seasons. This is accomplished advanced mechanisms that implement reasoning pro- by modeling the situation and observing the conse- cedures deliberately and consciously. For example, quences of possible actions (e.g., the occurrence of inductive reasoning largely depends on the retrieval snow in winter introduces new challenges). and evaluation of world knowledge, whereas deductive Prediction and explanation further depend on causal reasoning depends on rule-based, formal procedures. reasoning (i.e., the ability to infer causal relations). For The dual-process theory further motivates the example, knowledge that cold winter weather can cognitive demand hypothesis: when people have little cause an accumulation of snow in the mountains, time and limited processing resources, incentives, Encyclopedia of Neuroscience (2009), vol. 8, pp. 35-43 Author's personal copy 36 Reasoning and Problem Solving: Models and/or external aids available for making a judgment, of a chair into amodal representations (e.g., feature they only use the associative system when reasoning. lists, semantic nets), processed by classic symbolic Conversely, when people have more time and greater mechanisms (e.g., predication, argument binding). processing resources, incentives, and/or external aids Thus, amodal theories predict that conceptual proces- available, they also use the rule-based system. The sing will recruit brain regions outside sensorimotor dual-process model predicts that reasoning recruits areas that underlie language and rules, including left different neural systems, depending on cognitive prefrontal and superior temporal regions implicated demand. When tasks are easy, the associative system in formal, rule-based operations. is sufficient for correct reasoning and primarily In contrast, embodied theories of knowledge pro- recruits left inferior frontal gyrus, especially Broca’s pose that knowledge and meaning are grounded in area, in addition to the temporal lobes and posterior modality-specific representations. Increasing empirical parietal association cortex. As tasks become more evidence from both the cognitive and the neuroscience difficult, the rule-based system becomes required for literatures suggests that modality-specific representa- correctreasoning and recruits the prefrontal cortex, tions underlie higher level cognition. According to this especially the ventrolateral subregion, which has been framework, concepts are represented by simulating implicated in rule maintenance. the modality-specific states that were initially acti- A second theory that provides a general-purpose vated during perception, action, and interoception. account of reasoning is grounded in a somewhat Embodied theories propose that simulations are different pair of systems: the linguistic system and organized at a higher level by simulators that inte- the conceptual system. According to this view, the grate information across a category’s instances. Over brain’s language system initially produces relatively time, for example, visual information about how superficial information about a reasoning problem, cakes look becomes integrated in a ‘cake’ simulator, such as word associates, syntactic structures, etc. As along with gustatory information about how cakes linguistic forms become generated, their meanings taste, somatosensory information about how they become increasingly represented in the conceptual feel, motor programs for interacting with them, emo- system. A key assumption of this approach is that tional responses to experiencing them, and so forth. superficial processing based on linguistic representa- The result is a distributed system throughout the tions may often be sufficient for adequate reasoning brain’s modality-specific areas that establishes con- performance. When it is not sufficient, conceptual ceptual content for the general category of ‘cake.’ representations must be generated to produce more Thus, embodied theories predict that conceptual sophisticated reasoning. Thus, consistent with the processing will recruit a broadly distributed system dual-process model, this view predicts that differ- of modality-specific brain regions. ences in the cognitive demands of a reasoning task Embodied theories further motivate the task speci- (i.e., superficial vs. deep processing) will differentially ficity hypothesis. According to this hypothesis, the engage neural systems. neural areas underlying a particular type of reasoning, In general, both dual coding frameworks predict such as deduction, may show little in common, as the that reasoning will recruit neural systems that sup- specific materials and tasks vary. Because different port two forms of coding. One important set of sys- materials and tasks produce different patterns of tems underlies language processing, including the left modality-specific activation, the same general form frontotemporal language system. A second set of of reasoning does not show a single, stable pattern, important systems underlies conceptual processing, and no common areas may emerge. In contrast to the mental simulation, and imagery, including bilateral ‘cognitive demand hypothesis,’ this view predicts that sensorimotor areas. significant differences in the task and/or materials – even those that do not affect cognitive demand – are likely to dominate neural activation more than the Representation in Reasoning type of reasoning performed. A second major distinction can be