At the core of reasoning: Dissociating deductive and non-deductive load

Intuitive physical reasoning is not mediated by linguistic nor exclusively domain-general abstract representations

The ability to reason about the physical world is a critical tool in the human cognitive toolbox, but the nature of the representations that mediate physical reasoning remains debated. Here, we use fMRI to illuminate this question by investigating the relationship between the physical-reasoning system and two well-characterized systems: a) the domain-general Multiple Demand (MD) system, which supports abstract reasoning, including mathematical and logical reasoning, and b) the language system, which supports linguistic computations and has been hypothesized to mediate some forms of thought. We replicate prior findings of a network of frontal and parietal areas that are robustly engaged by physical reasoning and identify an additional physical-reasoning area in the left frontal cortex, which also houses components of the MD and language systems. Critically, direct comparisons with tasks that target the MD and the language systems reveal that the physical-reasoning system overlaps with the MD system, but is dissociable from it in fine-grained activation patterns, which replicates prior work. Moreover, the physical-reasoning system does not overlap with the language system. These results suggest that physical reasoning does not rely on linguistic representations, nor exclusively on the domain-general abstract reasoning that the MD system supports.

Reorienting psychological science

Psychological phenomena occur across a wide range of scales, ranging from small, quick events of neurology and biology, to broader, more prolonged unfoldings typical of extended cultural practices. Although theories deployed by psychologists of different stripes have tended to incorporate these different scales, this is typically done in a manner that is implicit, and often unsystematic. That is, typical psychological research is conducted in a manner that is 'scale-blind'. In this article, I explore some of the historical and more recent recognition of this scale-blindness and place it in the context of recent work on the concept and implications of scale. I conclude by elucidating some of the important ways in which behaviour settings theory, and the researchers who developed it, are explicit and disciplined in their approach to scale, and how such scale-aware work promises practical value in improving scientific practice. This article is part of the theme issue 'People, places, things, and communities: expanding behaviour settings theory in the 21st century'.

Natural language instructions induce compositional generalization in networks of neurons

A fundamental human cognitive feat is to interpret linguistic instructions in order to perform novel tasks without explicit task experience. Yet, the neural computations that might be used to accomplish this remain poorly understood. We use advances in natural language processing to create a neural model of generalization based on linguistic instructions. Models are trained on a set of common psychophysical tasks, and receive instructions embedded by a pretrained language model. Our best models can perform a previously unseen task with an average performance of 83% correct based solely on linguistic instructions (that is, zero-shot learning). We found that language scaffolds sensorimotor representations such that activity for interrelated tasks shares a common geometry with the semantic representations of instructions, allowing language to cue the proper composition of practiced skills in unseen settings. We show how this model generates a linguistic description of a novel task it has identified using only motor feedback, which can subsequently guide a partner model to perform the task. Our models offer several experimentally testable predictions outlining how linguistic information must be represented to facilitate flexible and general cognition in the human brain.

The language network is not engaged in object categorization

The relationship between language and thought is the subject of long-standing debate. One claim states that language facilitates categorization of objects based on a certain feature (e.g. color) through the use of category labels that reduce interference from other, irrelevant features. Therefore, language impairment is expected to affect categorization of items grouped by a single feature (low-dimensional categories, e.g. "Yellow Things") more than categorization of items that share many features (high-dimensional categories, e.g. "Animals"). To test this account, we conducted two behavioral studies with individuals with aphasia and an fMRI experiment with healthy adults. The aphasia studies showed that selective low-dimensional categorization impairment was present in some, but not all, individuals with severe anomia and was not characteristic of aphasia in general. fMRI results revealed little activity in language-responsive brain regions during both low- and high-dimensional categorization; instead, categorization recruited the domain-general multiple-demand network (involved in wide-ranging cognitive tasks). Combined, results demonstrate that the language system is not implicated in object categorization. Instead, selective low-dimensional categorization impairment might be caused by damage to brain regions responsible for cognitive control. Our work adds to the growing evidence of the dissociation between the language system and many cognitive tasks in adults.

Electrophysiological connectivity of logical deduction: Early cortical MEG study

Complex human reasoning involves minimal abilities to extract conclusions implied in the available information. These abilities are considered "deductive" because they exemplify certain abstract relations among propositions or probabilities called deductive arguments. However, the electrophysiological dynamics which supports such complex cognitive processes has not been addressed yet. In this work we consider typically deductive logico-probabilistically valid inferences and aim to verify or refute their electrophysiological functional connectivity differences from invalid inferences with the same content (same relational variables, same stimuli, same relevant and salient features). We recorded the brain electrophysiological activity of 20 participants (age = 20.35 ± 3.23) by means of an MEG system during two consecutive reasoning tasks: a search task (invalid condition) without any specific deductive rules to follow, and a logically valid deductive task (valid condition) with explicit deductive rules as instructions. We calculated the functional connectivity (FC) for each condition and conducted a seed-based analysis in a set of cortical regions of interest. Finally, we used a cluster-based permutation test to compare the differences between logically valid and invalid conditions in terms of FC. As a first novel result we found higher FC for valid condition in beta band between regions of interest and left prefrontal, temporal, parietal, and cingulate structures. FC analysis allows a second novel result which is the definition of a propositional network with operculo-cingular, parietal and medial nodes, specifically including disputed medial deductive "core" areas. The experiment discloses measurable cortical processes which do not depend on content but on truth-functional propositional operators. These experimental novelties may contribute to understand the cortical bases of deductive processes.

Mentalizing and self-other distinction in visual perspective taking: the analysis of temporal neural processing using high-density EEG

This high density EEG report dissects the neural processing in the visual perspective taking using four experimental comparisons (Arrow, Avatar and Self, Other). Early activation differences occurred between the Avatar and the Arrow condition in primary visual pathways concomitantly with alpha and beta phase locked responses predominant in the Avatar condition. In later time points, brain activation was stronger for the Avatar condition in paracentral lobule of frontal lobe. When taking the other's perspective, there was an increased recruitment of generators in the occipital and temporal lobes and later on in mentalizing and salience networks bilaterally before spreading to right frontal lobe subdivisions. Microstate analysis further supported late recruitment of the medial frontal gyrus and precentral lobule in this condition. Other perspective for the Avatar only showed a strong beta response located first in left occipito-temporal and right parietal areas, and later on in frontal lobes. Our EEG data support distinct brain processes for the Avatar condition with an increased recruitment of brain generators that progresses from primary visual areas to the anterior brain. Taking the other's perspective needs an early recruitment of neural processors in posterior areas involved in theory of mind with later involvement of additional frontal generators.

Electrical analysis of logical complexity: an exploratory eeg study of logically valid/invalid deducive inference

INTRODUCTION

Logically valid deductive arguments are clear examples of abstract recursive computational procedures on propositions or on probabilities. However, it is not known if the cortical time-consuming inferential processes in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of inferential processes.

METHODS

In order to determine whether an electrical EEG discernible pattern of logical deduction exists or not, a new experimental paradigm is proposed contrasting logically valid and invalid inferences with exactly the same content (same premises and same relational variables) and distinct logical complexity (propositional truth-functional operators). Electroencephalographic signals from 19 subjects (24.2 ± 3.3 years) were acquired in a two-condition paradigm (100 trials for each condition). After the initial general analysis, a trial-by-trial approach in beta-2 band allowed to uncover not only evoked but also phase asynchronous activity between trials.

RESULTS

showed that (i) deductive inferences with the same content evoked the same response pattern in logically valid and invalid conditions, (ii) mean response time in logically valid inferences is 61.54% higher, (iii) logically valid inferences are subjected to an early (400 ms) and a late reprocessing (600 ms) verified by two distinct beta-2 activations (p-value < 0,01, Wilcoxon signed rank test).

CONCLUSION

We found evidence of a subtle but measurable electrical trait of logical validity. Results put forward the hypothesis that some logically valid deductions are recursive or computational cortical events.

Probabilistic and Deductive Reasoning in the Human Brain

Reasoning is a process of inference from given premises to new conclusions. Deductive reasoning is truth-preserving and conclusions can only be either true or false. Probabilistic reasoning is based on degrees of belief and conclusions can be more or less likely. While deductive reasoning requires people to focus on the logical structure of the inference and ignore its content, probabilistic reasoning requires the retrieval of prior knowledge from memory. Recently, however, some researchers have denied that deductive reasoning is a faculty of the human mind. What looks like deductive inference might actually also be probabilistic inference, only with extreme probabilities. We tested this assumption in an fMRI experiment with two groups of participants: one group was instructed to reason deductively, the other received probabilistic instructions. They could freely choose between a binary and a graded response to each problem. The conditional probability and the logical validity of the inferences were systematically varied. Results show that prior knowledge was only used in the probabilistic reasoning group. These participants gave graded responses more often than those in the deductive reasoning group and their reasoning was accompanied by activations in the hippocampus. Participants in the deductive group mostly gave binary responses and their reasoning was accompanied by activations in the anterior cingulate cortex, inferior frontal cortex, and parietal regions. These findings show that (1) deductive and probabilistic reasoning rely on different neurocognitive processes, (2) people can suppress their prior knowledge to reason deductively, and (3) not all inferences can be reduced to probabilistic reasoning.

Patterns of multiple brain network activation in dot perspective task

In this functional MRI (fMRI) study on 82 healthy adults using the dot perspective task, inconsistency of perspectives was associated with a significant increase of the mean reaction time and number of errors both in Self and Other conditions. Unlike the Arrow (non-mentalizing), the Avatar (mentalizing) paradigm was characterized by the recruitment of parts of the mentalizing and salience networks. These data provide experimental evidence supporting the fMRI distinction between mentalizing and non-mentalizing stimuli. A widespread activation of classical theory of mind (ToM) areas but also of salience network and decision making areas was observed in the Other compared to Self-conditions. Compared to Self-Consistent, Self-Inconsistent trials were related to increased activation in the lateral occipital cortex, right supramarginal and angular gyrus as well as inferior, superior and middle frontal gyri. Compared to the Other-Consistent, Other-Inconsistent trials yielded strong activation in the lateral occipital cortex, precuneus and superior parietal lobule, middle and superior precentral gyri and left frontal pole. These findings reveal that altercentric interference relies on areas involved in self-other distinction, self-updating and central executive functions. In contrast, egocentric interference needs the activation of the mirror neuron system and deductive reasoning, much less related to pure ToM abilities.

Seeing inferences: brain dynamics and oculomotor signatures of non-verbal deduction

We often express our thoughts through words, but thinking goes well beyond language. Here we focus on an elementary but basic thinking process, disjunction elimination, elicited by elementary visual scenes deprived of linguistic content, describing its neural and oculomotor correlates. We track two main components of a nonverbal deductive process: the construction of a logical representation (A or B), and its simplification by deduction (not A, therefore B). We identify the network active in the two phases and show that in the latter, but not in the former, it overlaps with areas known to respond to verbal logical reasoning. Oculomotor markers consistently differentiate logical processing induced by the construction of a representation, its simplification by deductive inference, and its maintenance when inferences cannot be drawn. Our results reveal how integrative logical processes incorporate novel experience in the flow of thoughts induced by visual scenes.

Dissociating Language and Thought in Human Reasoning

What is the relationship between language and complex thought? In the context of deductive reasoning there are two main views. Under the first, which we label here the language-centric view, language is central to the syntax-like combinatorial operations of complex reasoning. Under the second, which we label here the language-independent view, these operations are dissociable from the mechanisms of natural language. We applied continuous theta burst stimulation (cTBS), a form of noninvasive neuromodulation, to healthy adult participants to transiently inhibit a subregion of Broca's area (left BA44) associated in prior work with parsing the syntactic relations of natural language. We similarly inhibited a subregion of dorsomedial frontal cortex (left medial BA8) which has been associated with core features of logical reasoning. There was a significant interaction between task and stimulation site. Post hoc tests revealed that performance on a linguistic reasoning task, but not deductive reasoning task, was significantly impaired after inhibition of left BA44, and performance on a deductive reasoning task, but not linguistic reasoning task, was decreased after inhibition of left medial BA8 (however not significantly). Subsequent linear contrasts supported this pattern. These novel results suggest that deductive reasoning may be dissociable from linguistic processes in the adult human brain, consistent with the language-independent view.

Structural neuroplasticity in computer programming beginners

We examined the structural neuroplastic changes associated with the learning of computer programming in university students with no previous programming experience. They participated in a 15-week course (26 lessons) on the “Processing” computer programming language. We have conducted a longitudinal analysis of gray matter volume (GMV) in the magnetic resonance images obtained before and after learning computer programming. Significant neuroplastic changes appeared in the following 8 sites: the left frontal pole; the right frontal pole; the right medial frontal gyrus; the left cuneus; the left lateral cerebellum (posterior lobule and tuber); the medial cerebellum (uvula and tonsil); the right pallidum; and the left pallidum. The amount of change in the GMV of the right frontal pole correlated positively with the final product score. Furthermore, the amount of change in the GMV of the right medial frontal gyrus and the bilateral pallidum correlated positively with the test scores. Thus, the right frontal pole was presumably associated with the function of persistent attempts to accomplish tasks (goal achievement-related function). The right medial frontal gyrus and the bilateral pallidum were presumably related to deduction and reward functions, respectively. Therefore, multiple brain regions appear to be involved in programming learning through different functions.

Neural Correlates of Causal Inferences in Discourse Understanding and Logical Problem-Solving: A Meta-Analysis Study

In discourse comprehension, we need to draw inferences to make sense of discourse. Previous neuroimaging studies have investigated the neural correlates of causal inferences in discourse understanding. However, these findings have been divergent, and how these types of inferences are related to causal inferences in logical problem-solving remains unclear. Using the activation likelihood estimation (ALE) approach, the current meta-analysis analyzed 19 experiments on causal inferences in discourse understanding and 20 experiments on those in logical problem-solving to identify the neural correlates of these two cognitive processes and their shared and distinct neural correlates. We found that causal inferences in discourse comprehension recruited a left-lateralized frontotemporal brain system, including the left inferior frontal gyrus, the left middle temporal gyrus (MTG), and the bilateral medial prefrontal cortex (MPFC), while causal inferences in logical problem-solving engaged a nonoverlapping brain system in the frontal and parietal cortex, including the left inferior frontal gyrus, the bilateral middle frontal gyri, the dorsal MPFC, and the left inferior parietal lobule (IPL). Furthermore, the pattern similarity analyses showed that causal inferences in discourse understanding were primarily related to the terms about language processing and theory-of-mind processing. Both types of inferences were found to be related to the terms about memory and executive function. These findings suggest that causal inferences in discourse understanding recruit distinct neural bases from those in logical problem-solving and rely more on semantic knowledge and social interaction experiences.

Neurocognitive basis of deductive reasoning in children varies with parental education

The neurocognitive basis of elementary academic skills varies with parental socioeconomic status (SES). Little is known, however, about SES‐related differences underlying higher‐order cognitive skills that are critical for school success, such as reasoning. Here we used fMRI to examine how the neurocognitive basis of deductive reasoning varies as a function of parental education in school‐aged children. Higher parental education was associated with greater reliance on the left inferior frontal gyrus when solving set‐inclusion problems, consistent with other work suggesting that these problems might more heavily rely on verbal systems in the brain. In addition, children who are at the lower end of the parental education continuum, but have higher nonverbal skills relied on right parietal areas to a greater degree than their peers for solving set‐inclusion problems. Finally, lower parental education children with higher verbal or nonverbal skill engaged dorsolateral prefrontal regions to a greater degree for set‐inclusion and linear‐order relations than their peers. These findings suggest that children with lower parental education rely on spatial and cognitive control mechanisms to achieve parity with their peers with parents who have more education. Better understanding variability in the neurocognitive networks that children recruit as a function of their parental factors might benefit future individualized interventions that best match children's characteristics.

Brain electrical traits of logical validity

Neuroscience has studied deductive reasoning over the last 20 years under the assumption that deductive inferences are not only de jure but also de facto distinct from other forms of inference. The objective of this research is to verify if logically valid deductions leave any cerebral electrical trait that is distinct from the trait left by non-valid deductions. 23 subjects with an average age of 20.35 years were registered with MEG and placed into a two conditions paradigm (100 trials for each condition) which each presented the exact same relational complexity (same variables and content) but had distinct logical complexity. Both conditions show the same electromagnetic components (P3, N4) in the early temporal window (250-525 ms) and P6 in the late temporal window (500-775 ms). The significant activity in both valid and invalid conditions is found in sensors from medial prefrontal regions, probably corresponding to the ACC or to the medial prefrontal cortex. The amplitude and intensity of valid deductions is significantly lower in both temporal windows (p = 0.0003). The reaction time was 54.37% slower in the valid condition. Validity leaves a minimal but measurable hypoactive electrical trait in brain processing. The minor electrical demand is attributable to the recursive and automatable character of valid deductions, suggesting a physical indicator of computational deductive properties. It is hypothesized that all valid deductions are recursive and hypoactive.

Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network

Despite the importance of programming to modern society, the cognitive and neural bases of code comprehension are largely unknown. Programming languages might 'recycle' neurocognitive mechanisms originally developed for natural languages. Alternatively, comprehension of code could depend on fronto-parietal networks shared with other culturally-invented symbol systems, such as formal logic and symbolic math such as algebra. Expert programmers (average 11 years of programming experience) performed code comprehension and memory control tasks while undergoing fMRI. The same participants also performed formal logic, symbolic math, executive control, and language localizer tasks. A left-lateralized fronto-parietal network was recruited for code comprehension. Patterns of activity within this network distinguish between 'for' loops and 'if' conditional code functions. In terms of the underlying neural basis, code comprehension overlapped extensively with formal logic and to a lesser degree math. Overlap with executive processes and language was low, but laterality of language and code covaried across individuals. Cultural symbol systems, including code, depend on a distinctive fronto-parietal cortical network.

Deductive-reasoning brain networks: A coordinate-based meta-analysis of the neural signatures in deductive reasoning

OBJECTIVE

Deductive reasoning is a complex and poorly understood concept in the field of psychology. Many cognitive neuroscience studies have been published on deductive reasoning but have yielded inconsistent findings.

METHODS

In this study, we analyzed collected data from 38 articles using a recently proposed activation likelihood estimation (ALE) approach and used conjunction analysis to better determine the intersection of the results of meta-analyses.

RESULTS

First, the left hemispheres in the inferior parietal lobule (Brodmann area 40 [BA40]), middle frontal gyrus (BA6), medial frontal gyrus (BA8), inferior frontal gyrus (BA45/46), caudate, and insula (BA47) were revealed to be significant brain regions via simple-effect analysis (deductive reasoning versus baseline). Furthermore, IFG, insula, and cingulate (the key neural hubs of the cingulo-opercular network) were highlighted in overlapped functional connectivity maps.

CONCLUSION

The findings of the current study are consistent with the view that deductive reasoning requires a succession of stages, which included decoding of linguistic information, conversion and correction of rules, and transformation of inferential results into conclusive outputs, all of which are putatively processed via a distributed network of brain regions encompassing frontal/parietal cortices, as well as the caudate and other subcortical structures, which suggested that in the process of deductive reasoning, the coding and integration of premise information is indispensable, and it is also crucial to the execution and monitoring of the cognitive processing of reasoning.

The neural bases of argumentative reasoning

Most reasoning tasks used in behavioral and neuroimaging studies are abstract, triggering slow, effortful processes. By contrast, most of everyday life reasoning is fast and effortless, as when we exchange arguments in conversation. Recent behavioral studies have shown that reasoning tasks with the same underlying logic can be solved much more easily if they are embedded in an argumentative context. In the present article, we study the neural bases of this type of everyday, argumentative reasoning. Such reasoning is both a social and a metarepresentational process, suggesting it should share some mechanisms, and thus some neural bases, with other social, metarepresentational process such as pragmatics, metacognition, or theory of mind. To isolate the neural bases of argumentative reasoning, we measured fMRI activity of participants who read the same statement presented either as the conclusion of an argument, or as an assertion. We found that conclusions of arguments, compared to assertions, were associated with greater activity in a region of the medial prefrontal cortex that was identified in quantitative meta-analyses of studies on theory of mind. This study shows that it is possible to use more ecologically valid tasks to study the neural bases of reasoning, and that using such tasks might point to different neural bases than those observed with the more abstract and artificial tasks typically used in the neuroscience of reasoning. Specifically, we speculate that reasoning in an argumentative context might rely on mechanisms supporting metarepresentational processes in the medial prefrontal cortex.

Relational Integration in the Human Brain: A Review and Synthesis

Relational integration is required when multiple explicit representations of relations between entities must be jointly considered to make inferences. We provide an overview of the neural substrate of relational integration in humans and the processes that support it, focusing on work on analogical and deductive reasoning. In addition to neural evidence, we consider behavioral and computational work that has informed neural investigations of the representations of individual relations and of relational integration. In very general terms, evidence from neuroimaging, neuropsychological, and neuromodulatory studies points to a small set of regions (generally left lateralized) that appear to constitute key substrates for component processes of relational integration. These include posterior parietal cortex, implicated in the representation of first-order relations (e.g., A:B); rostrolateral pFC, apparently central in integrating first-order relations so as to generate and/or evaluate higher-order relations (e.g., A:B::C:D); dorsolateral pFC, involved in maintaining relations in working memory; and ventrolateral pFC, implicated in interference control (e.g., inhibiting salient information that competes with relevant relations). Recent work has begun to link computational models of relational representation and reasoning with patterns of neural activity within these brain areas.

The Neurocognitive Correlates of Human Reasoning: A Meta-analysis of Conditional and Syllogistic Inferences

Inferring knowledge is a core aspect of human cognition. We can form complex sentences connecting different pieces of information, such as in conditional statements like "if someone drinks alcohol, then they must be older than 18." These are relevant for causal reasoning about our environment and allow us to think about hypothetical scenarios. Another central aspect to forming complex statements is to quantify about sets, such as in "some apples are green." Reasoning in terms of the ability to form these statements is not yet fully understood, despite being an active field of interdisciplinary research. On a theoretical level, several conceptual frameworks have been proposed, predicting diverging brain activation patterns during the reasoning process. We present a meta-analysis comprising the results of 32 neuroimaging experiments about reasoning, which we subdivided by their structure, content, and requirement for world knowledge. In conditional tasks, we identified activation in the left middle and rostrolateral pFC and parietal regions, whereas syllogistic tasks elicit activation in Broca's complex, including the BG. Concerning the content differentiation, abstract tasks exhibit activation in the left inferior and rostrolateral pFC and inferior parietal regions, whereas content tasks are in the left superior pFC and parieto-occipital regions. The findings clarify the neurocognitive mechanisms of reasoning and exhibit clear distinctions between the task's type and content. Overall, we found that the activation differences clarify inconsistent results from accumulated data and serve as useful scaffolding differentiations for theory-driven interpretations of the neuroscientific correlates of human reasoning.

The language of music: Common neural codes for structured sequences in music and natural language

The ability to process structured sequences is a central feature of natural language but also characterizes many other domains of human cognition. In this fMRI study, we measured brain metabolic response in musicians as they generated structured and non-structured sequences in language and music. We employed a univariate and multivariate cross-classification approach to provide evidence that a common neural code underlies the production of structured sequences across the two domains. Crucially, the common substrate includes Broca's area, a region well known for processing structured sequences in language. These findings have several implications. First, they directly support the hypothesis that language and music share syntactic integration mechanisms. Second, they show that Broca's area is capable of operating supramodally across these two domains. Finally, these results dismiss the recent hypothesis that domain general processes of neighboring neural substrates explain the previously observed "overlap" between neuroimaging activations across the two domains.

TMS applied to V1 can facilitate reasoning

Visual mental imagery is the subjective experience of seeing objects or events in front of the 'inner eye', although they are not actually present. Previous research indicates that (1) visual images help to remember what has been experienced in the past or when objects need to be inspected or manipulated, and (2) visual images are correlated with neural activity in early visual cortices, demonstrating a possible overlap between visual imagery and visual perception. However, recent research revealed that visual imagery can also disrupt cognitive processes and impede thinking. In this transcranial magnetic stimulation (TMS) experiment, participants had to solve relational reasoning problems that varied in their imageability (easy or difficult to visualize as a mental image). While solving the problems, eight 10 Hz pulses were either applied to primary visual cortex (V1) or a control site (Vertex). Our findings suggest a causal link between mental imagery, primary visual cortex, and reasoning with visual problems. Moreover, participants exhibited much lower error rates when TMS was applied to V1. We conclude that the disruption of visual images in primary visual cortex can facilitate reasoning.

At the core of reasoning: Dissociating deductive and non-deductive load

In recent years, neuroimaging methods have been used to investigate how the human mind carries out deductive reasoning. According to some, the neural substrate of language is integral to deductive reasoning. According to others, deductive reasoning is supported by a language-independent distributed network including left frontopolar and frontomedial cortices. However, it has been suggested that activity in these frontal regions might instead reflect non-deductive factors such as working memory load and general cognitive difficulty. To address this issue, 20 healthy volunteers participated in an fMRI experiment in which they evaluated matched simple and complex deductive and non-deductive arguments in a 2 × 2 design. The contrast of complex versus simple deductive trials resulted in a pattern of activation closely matching previous work, including frontopolar and frontomedial "core" areas of deduction as well as other "cognitive support" areas in frontoparietal cortices. Conversely, the contrast of complex and simple non-deductive trials resulted in a pattern of activation that does not include any of the aforementioned "core" areas. Direct comparison of the load effect across deductive and non-deductive trials further supports the view that activity in the regions previously interpreted as "core" to deductive reasoning cannot merely reflect non-deductive load, but instead might reflect processes specific to the deductive calculus. Finally, consistent with previous reports, the classical language areas in left inferior frontal gyrus and posterior temporal cortex do not appear to participate in deductive inference beyond their role in encoding stimuli presented in linguistic format.