The brain network for deductive reasoning: a quantitative meta-analysis of 28 neuroimaging studies

Trail making test - black & white (TMT B&W): Normative study for the Chilean population

The trailmaking test (TMT) has an educational bias that makes it inapplicable to people with low levels of education due to its dependence on the alphabet. The TMT standardization is the only one available in Chile, and there is a need for alternative ways of using the TMT that do not depend on the level of education for its applicability. To determine the normative scores of the TMT - black & white (TMT B&W), considering sociodemographic factors in adult and elderly Chilean population. A total sample of 227 participants (133 healthy, 94 cognitively impaired) from the Ageing Mets cohort were recruited from three areas in Chile (Antofagasta, Santiago, and Puerto Montt). The TMT B&W was administered to all participants. A multiple regression model was used to generate normative data only in the cognitively healthy group, considering the effect of age, education and sex. A significant effect of age was found in the score of the TMT B&W Parts A and B. The level of education influenced the part B of the test; however, the completion rate of the TMT B&W parts A and B was over 90% in cognitively healthy people. Norms for the number of errors were obtained, and differences between groups were found after controlling for the effect of age and education. This study is the first to provide normative data for the Chilean version of the TMT B&W and will benefit clinical neuropsychologists by improving the procedures for more accurately assessing executive functions and its impairments.

Semantic and Visuospatial Fluid Reasoning in School-Aged Autistic Children

In light of the known visuoperceptual strengths and altered language skills in autism, we investigated the impact of problem content (semantic/visuospatial) combined with complexity and presence of lures on fluid reasoning in 43 autistic and 41 typical children (6-13 years old). Increased complexity and presence of lures diminished performance, but less so as the children's age increased. Typical children were slightly more accurate overall, whereas autistic children were faster at solving complex visuospatial problems. Thus, reasoning could rely more extensively on visuospatial strategies in autistic versus typical children. A combined speed-accuracy measure revealed similar performance in both groups, suggesting a similar pace in fluid reasoning development. Visual presentation of conceptual information seems to suit the reasoning processes of autistic children.

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.

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.

Classification of autism based on short-term spontaneous hemodynamic fluctuations using an adaptive graph neural network

BACKGROUND

Short-term spontaneous hemodynamic fluctuations were collected by the functional near-infrared spectroscopy (fNIRS) system to classify children with autism spectrum disorder (ASD) and typical development (TD), and to explore abnormalities in the left inferior frontal gyrus in ASD.

METHODS

Using the fNIRS data of 25 children with ASD and 22 children with TD, a graph neural network combined with the temporal convolution module and the graph convolution module was used, to extract the spatio-temporal features of the data and achieve accurate classification of ASD.

RESULTS

The graph neural network was used to obtain a good classification result in the left inferior frontal gyrus, with an accuracy of 97.1%, precision of 95.1%, and specificity of 93.4%. It was found that the 5th channel (which is located in BA 10) and the 8th channel (which is located in BA 47) in the left inferior frontal gyrus were closely correlated with ASD.

COMPARISON WITH PREVIOUSLY USED METHOD(S)

Compared with the previous deep learning model using the same input, the accuracy of our model has increased by up to 13%, and the correlation between channels in the left inferior frontal gyrus area with the best classification effect was explored through the graph neural network.

CONCLUSION

The adaptive graph neural network (AGNN) model may be able to mine more valuable information to distinguish ASD from TD and in addition, the left inferior frontal gyrus may have greater investigative value.

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.

Deficits in Analytic and Common-Sense Reasoning in Schizophrenia

ABSTRACT

Human rationality has a dual nature including analytic and common-sense thinking. Symptoms of schizophrenia have been suggested to be related to deficits in these aspects of logical reasoning. However, empirical studies investigating logical reasoning errors in schizophrenia and their clinical and neurocognitive correlates are scarce. Formal thought disorder and theory of mind (ToM) might be particularly important for understanding logical reasoning errors in schizophrenia. The current study compared the performances of 80 patients with schizophrenia with those of 49 healthy controls on syllogistic and counterfactual reasoning tasks and investigated clinical, neuropsychological, and social cognitive correlates of logical reasoning in schizophrenia. Patients with schizophrenia were impaired in both analytic and common-sense thinking. ToM impairment was a significant predictor of analytic reasoning abilities in schizophrenia. Executive functions and verbal memory were also significantly associated with analytic reasoning in schizophrenia. Further studies investigating logical reasoning errors in the early phases of the illness are needed.

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.

Brain activations time locked to slow wave-coupled sleep spindles correlates with intellectual abilities

Sleep spindles (SP) are one of the few known electrophysiological neuronal biomarkers of interindividual differences in cognitive abilities and aptitudes. Recent simultaneous electroencephalography with functional magnetic resonance imaging (EEG-fMRI) studies suggest that the magnitude of the activation of brain regions recruited during spontaneous spindle events is specifically related to Reasoning abilities. However, it is not known if the relationship with cognitive abilities differs between uncoupled spindles, uncoupled slow waves (SW), and coupled SW–SP complexes, nor have the functional-neuroanatomical substrates that support this relationship been identified. Here, we investigated the functional significance of activation of brain areas recruited during SW-coupled spindles, uncoupled spindles, and uncoupled slow waves. We hypothesize that brain activations time locked to SW-coupled spindle complexes will be primarily associated to Reasoning abilities, especially in subcortical areas. Our results provide direct evidence that the relationship between Reasoning abilities and sleep spindles depends on spindle coupling status. Specifically, we found that the putamen and thalamus, recruited during coupled SW–SP events were positively correlated with Reasoning abilities. In addition, we found a negative association between Reasoning abilities and hippocampal activation time-locked to uncoupled SWs that might reflect a refractory mechanism in the absence of new, intensive hippocampal-dependent memory processing.

The Age of Reason: Functional Brain Network Development during Childhood

Human childhood is characterized by dramatic changes in the mind and brain. However, little is known about the large-scale intrinsic cortical network changes that occur during childhood because of methodological challenges in scanning young children. Here, we overcome this barrier by using sophisticated acquisition and analysis tools to investigate functional network development in children between the ages of 4 and 10 years ([Formula: see text]; 50 female, 42 male). At multiple spatial scales, age is positively associated with brain network segregation. At the system level, age was associated with segregation of systems involved in attention from those involved in abstract cognition, and with integration among attentional and perceptual systems. Associations between age and functional connectivity are most pronounced in visual and medial prefrontal cortex, the two ends of a gradient from perceptual, externally oriented cortex to abstract, internally oriented cortex. These findings suggest that both ends of the sensory-association gradient may develop early, in contrast to the classical theories that cortical maturation proceeds from back to front, with sensory areas developing first and association areas developing last. More mature patterns of brain network architecture, controlling for age, were associated with better visuospatial reasoning abilities. Our results suggest that as cortical architecture becomes more specialized, children become more able to reason about the world and their place in it.SIGNIFICANCE STATEMENT Anthropologists have called the transition from early to middle childhood the "age of reason", when children across cultures become more independent. We employ cutting-edge neuroimaging acquisition and analysis approaches to investigate associations between age and functional brain architecture in childhood. Age was positively associated with segregation between cortical systems that process the external world and those that process abstract phenomena like the past, future, and minds of others. Surprisingly, we observed pronounced development at both ends of the sensory-association gradient, challenging the theory that sensory areas develop first and association areas develop last. Our results open new directions for research into how brains reorganize to support rapid gains in cognitive and socioemotional skills as children reach the age of reason.

Transfer from spatial education to verbal reasoning and prediction of transfer from learning-related neural change

Current debate surrounds the promise of neuroscience for education, including whether learning-related neural changes can predict learning transfer better than traditional performance-based learning assessments. Longstanding debate in philosophy and psychology concerns the proposition that spatial processes underlie seemingly nonspatial/verbal reasoning (mental model theory). If so, education that fosters spatial cognition might improve verbal reasoning. Here, in a quasi-experimental design in real-world STEM classrooms, a curriculum devised to foster spatial cognition yielded transfer to improved verbal reasoning. Further indicating a spatial basis for verbal transfer, students' spatial cognition gains predicted and mediated their reasoning improvement. Longitudinal fMRI detected learning-related changes in neural activity, connectivity, and representational similarity in spatial cognition-implicated regions. Neural changes predicted and mediated learning transfer. Ensemble modeling demonstrated better prediction of transfer from neural change than from traditional measures (tests and grades). Results support in-school "spatial education" and suggest that neural change can inform future development of transferable curricula.

Neural correlates of transitive inference: An SDM meta-analysis on 32 fMRI studies

Transitive inference (TI) is a critical capacity involving the integration of relevant information into prior knowledge structure for drawing novel inferences on unobserved relationships. To date, the neural correlates of TI remain unclear due to the small sample size and heterogeneity of various experimental tasks from individual studies. Here, the meta-analysis on 32 fMRI studies was performed to detect brain activation patterns of TI and its three paradigms (spatial inference, hierarchical inference, and associative inference). We found the hippocampus, prefrontal cortex (PFC), putamen, posterior parietal cortex (PPC), retrosplenial cortex (RSC), supplementary motor area (SMA), precentral gyrus (PreCG), and median cingulate cortex (MCC) were engaged in TI. Specifically, the RSC was implicated in the associative inference, whereas PPC, SMA, PreCG, and MCC were implicated in the hierarchical inference. In addition, the hierarchical inference and associative inference both evoked activation in the hippocampus, medial PFC, and PCC. Although the meta-analysis on spatial inference did not generate a reliable result due to insufficient amount of investigations, the present work still offers a new insight for better understanding the neural basis underlying TI.

Paradoxical Reasoning: An fMRI Study

Paradoxes are a special form of reasoning leading to absurd inferences in contrast to logical reasoning that is used to reach valid conclusions. A functional MRI (fMRI) study was conducted to investigate the neural substrates of paradoxical and deductive reasoning. Twenty-four healthy participants were scanned using fMRI, while they engaged in reasoning tasks based on arguments, which were either Zeno’s like paradoxes (paradoxical reasoning) or Aristotelian arguments (deductive reasoning). Clusters of significant activation for paradoxical reasoning were located in bilateral inferior frontal and middle temporal gyrus. Clusters of significant activation for deductive reasoning were located in bilateral superior and inferior parietal lobe, precuneus, and inferior frontal gyrus. These results confirmed that different brain activation patterns are engaged for paradoxical vs. deductive reasoning providing a basis for future studies on human physiological as well as pathological reasoning.

Can a fast thinker be a good thinker? The neural correlates of base-rate neglect measured using a two-response paradigm

Traditionally, it has been assumed that logical thinking requires deliberation. However, people can also make logical responses quickly, exhibiting logical intuitions. We examined the neural correlates of logical intuitions by administering base rate problems during fMRI scanning using a two-response paradigm where participants first responded quickly and then reflectively to problems that did or did not pit a normative response against an intuitively-cued stereotypical response (i.e., conflict vs. non-conflict problems). As predicted, participants were less likely to make judgments in accordance with base rates on conflict problems. Critically, in only 4% of cases did longer deliberation change an initially biased response to a normatively correct response. The fMRI data revealed that intuitively-made initial biased judgments nevertheless activate regions typically involved in cognitive control, executive functions and attention, including anterior, inferior, middle and superior frontal cortex, suggesting that even when errors are made, there might be very early awareness of conflict.

A Cortical Surface-Based Meta-Analysis of Human Reasoning

Recent advances in neuroimaging have augmented numerous findings in the human reasoning process but have yielded varying results. One possibility for this inconsistency is that reasoning is such an intricate cognitive process, involving attention, memory, executive functions, symbolic processing, and fluid intelligence, whereby various brain regions are inevitably implicated in orchestrating the process. Therefore, researchers have used meta-analyses for a better understanding of neural mechanisms of reasoning. However, previous meta-analysis techniques include weaknesses such as an inadequate representation of the cortical surface’s highly folded geometry. Accordingly, we developed a new meta-analysis method called Bayesian meta-analysis of the cortical surface (BMACS). BMACS offers a fast, accurate, and accessible inference of the spatial patterns of cognitive processes from peak brain activations across studies by applying spatial point processes to the cortical surface. Using BMACS, we found that the common pattern of activations from inductive and deductive reasoning was colocalized with the multiple-demand system, indicating that reasoning is a high-level convergence of complex cognitive processes. We hope surface-based meta-analysis will be facilitated by BMACS, bringing more profound knowledge of various cognitive processes.

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.

Left Frontal EEG Power Responds to Stock Price Changes in a Simulated Asset Bubble Market

Financial bubbles are a result of aggregate irrational behavior and cannot be explained by standard economic pricing theory. Research in neuroeconomics can improve our understanding of their causes. We conducted an experiment in which 28 healthy subjects traded in a simulated market bubble, while scalp EEG was recorded using a low-cost, BCI-friendly desktop device with 14 electrodes. Independent component (IC) analysis was performed to decompose brain signals and the obtained scalp topography was used to cluster the ICs. We computed single-trial time-frequency power relative to the onset of stock price display and estimated the correlation between EEG power and stock price across trials using a general linear model. We found that delta band (1-4 Hz) EEG power within the left frontal region negatively correlated with the trial-by-trial stock prices including the financial bubble. We interpreted the result as stimulus-preceding negativity (SPN) occurring as a dis-inhibition of the resting state network. We conclude that the combination between the desktop-BCI-friendly EEG, the simulated financial bubble and advanced signal processing and statistical approaches could successfully identify the neural correlate of the financial bubble. We add to the neuroeconomics literature a complementary EEG neurometric as a bubble predictor, which can further be explored in future decision-making experiments.

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.

Neural correlates of recursive thinking during interpersonal strategic interactions

To navigate the complex social world, individuals need to represent others' mental states to think strategically and predict their next move. Strategic mentalizing can be classified into different levels of theory of mind according to its order of mental state attribution of other people's beliefs, desires, intentions, and so forth. For example, reasoning people's beliefs about simple world facts is the first-order attribution while going further to reason people's beliefs about the minds of others is the second-order attribution. The neural substrates that support such high-order recursive reasoning in strategic interpersonal interactions are still unclear. Here, using a sequential-move interactional game together with functional magnetic resonance imaging (fMRI), we showed that recursive reasoning engaged the frontal-subcortical regions. At the stimulus stage, the ventral striatum was more activated in high-order reasoning as compared with low-order reasoning. At the decision stage, high-order reasoning activated the medial prefrontal cortex (mPFC) and other mentalizing regions. Moreover, functional connectivity between the dorsomedial prefrontal cortex (dmPFC) and the insula/hippocampus was positively correlated with individual differences in high-order social reasoning. This work delineates the neural correlates of high-order recursive thinking in strategic games and highlights the key role of the interplay between mPFC and subcortical regions in advanced social decision-making.

Age-related differences in structural and functional prefrontal networks during a logical reasoning task

In logical reasoning, difficulties in inhibition of currently-held beliefs may lead to unwarranted conclusions, known as belief bias. Aging is associated with difficulties in inhibitory control, which may lead to deficits in inhibition of currently-held beliefs. No study to date, however, has investigated the underlying neural substrates of age-related differences in logical reasoning and the impact of belief load. The aim of the present study was to delineate age differences in brain activity during a syllogistic logical reasoning task while the believability load of logical inferences was manipulated. Twenty-nine, healthy, younger and thirty, healthy, older adults (males and females) completed a functional magnetic resonance imaging experiment in which they were asked to determine the logical validity of conclusions. Unlike younger adults, older adults engaged a large-scale network including anterior cingulate cortex and inferior frontal gyrus during conclusion stage. Our functional connectivity results suggest that while older adults engaged the anterior cingulate network to overcome their intuitive responses for believable inferences, the inferior frontal gyrus network contributed to higher control over responses during both believable and unbelievable conditions. Our functional results were further supported by structure-function-behavior analyses indicating the importance of cingulum bundle and uncinate fasciculus integrity in rejection of believable statements. These novel findings lend evidence for age-related differences in belief bias, with potentially important implications for decision making where currently-held beliefs and given assumptions are in conflict.

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 Creative Brain Under Stress: Considerations for Performance in Extreme Environments

Over the last 2 decades, we have begun to gain traction on the neural systems that support creative cognition. Specifically, a converging body of evidence from various domains has demonstrated that creativity arises from the interaction of two large-scale systems in the brain: Whereas the default network (DN) is involved in internally-oriented generation of novel concepts, the executive control network (ECN) exerts top-down control over that generative process to select task-appropriate output. In addition, the salience network (SN) regulates switching between those networks in the course of creative cognition. In contrast, we know much less about the workings of these large-scale systems in support of creativity under extreme conditions, although that is beginning to change. Specifically, there is growing evidence from systems neuroscience to demonstrate that the functioning and connectivity of DN, ECN, and SN are influenced by stress - findings that can be used to improve our understanding of the behavioral effects of stress on creativity. Toward that end, we review findings from the neuroscience of creativity, behavioral research on the impact of stress on creativity, and the systems-level view of the brain under stress to suggest ways in which creativity might be affected under extreme conditions. Although our focus is largely on acute stress, we also touch on the possible impact of chronic stress on creative cognition.

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 Shared Genetic Basis of Educational Attainment and Cerebral Cortical Morphology

Individual differences in educational attainment are linked to differences in intelligence, and predict important social, economic, and health outcomes. Previous studies have found common genetic factors that influence educational achievement, cognitive performance and total brain volume (i.e., brain size). Here, in a large sample of participants from the UK Biobank, we investigate the shared genetic basis between educational attainment and fine-grained cerebral cortical morphological features, and associate this genetic variation with a related aspect of cognitive ability. Importantly, we execute novel statistical methods that enable high-dimensional genetic correlation analysis, and compute high-resolution surface maps for the genetic correlations between educational attainment and vertex-wise morphological measurements. We conduct secondary analyses, using the UK Biobank verbal-numerical reasoning score, to confirm that variation in educational attainment that is genetically correlated with cortical morphology is related to differences in cognitive performance. Our analyses relate the genetic overlap between cognitive ability and cortical thickness measurements to bilateral primary motor cortex as well as predominantly left superior temporal cortex and proximal regions. These findings extend our understanding of the neurobiology that connects genetic variation to individual differences in educational attainment and cognitive performance.

Role of the Hippocampus During Logical Reasoning and Belief Bias in Aging

Reasoning requires initial encoding of the semantic association between premises or assumptions, retrieval of these semantic associations from memory, and recombination of information to draw a logical conclusion. Currently-held beliefs can interfere with the content of the assumptions if not congruent and inhibited. This study aimed to investigate the role of the hippocampus and hippocampal networks during logical reasoning tasks in which the congruence between currently-held beliefs and assumptions varies. Participants of younger and older age completed a series of syllogistic reasoning tasks in which two premises and one conclusion were presented and they were required to decide if the conclusion logically followed the premises. The belief load of premises was manipulated to be either congruent or incongruent with currently-held beliefs. Our whole-brain results showed that older adults recruited the hippocampus during the premise integration stage more than their younger counterparts. Functional connectivity using a hippocampal seed revealed that older, but not younger, adults recruited a hippocampal network that included anterior cingulate and inferior frontal regions when premises were believable. Importantly, this network contributed to better performance in believable inferences, only in older adults group. Further analyses suggested that, in older adults group, the integrity of the left cingulum bundle was associated with the higher rejection of believable premises more than unbelievable ones. Using multimodal imaging, this study highlights the importance of the hippocampus during premise integration and supports compensatory role of the hippocampal network during a logical reasoning task among older adults.

Neural representations of transitive relations predict current and future math calculation skills in children

A large body of evidence suggests that math learning in children is built upon innate mechanisms for representing numerical quantities in the intraparietal sulcus (IPS). Learning math, however, is about more than processing quantitative information. It is also about understanding relations between quantities and making inferences based on these relations. Consistent with this idea, recent behavioral studies suggest that the ability to process transitive relations (A > B, B > C, therefore A > C) may contribute to math skills in children. Here we used fMRI coupled with a longitudinal design to determine whether the neural processing of transitive relations in children could predict their current and future math skills. At baseline (T₁), children (n = 31) processed transitive relations in an MRI scanner. Math skills were measured at T₁ and again 1.5 years later (T₂). Using a machine learning approach with cross-validation, we found that activity associated with the representation of transitive relations in the IPS predicted math calculation skills at both T₁ and T₂. Our study highlights the potential of neurobiological measures of transitive reasoning for forecasting math skills in children, providing additional evidence for a link between this type of reasoning and math learning.

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.

Neurocognitive processes underlying heuristic and normative probability judgments

Judging two events in combination (A&B) as more probable than one of the events (A) is known as a conjunction fallacy. According to dual-process explanations of human judgment and decision making, the fallacy is due to the application of a heuristic, associative cognitive process. Avoiding the fallacy has been suggested to require the recruitment of a separate process that can apply normative rules. We investigated these assumptions using functional magnetic resonance imaging (fMRI) during conjunction tasks. Judgments, whether correct or not, engaged a network of brain regions identical to that engaged during similarity judgments. Avoidance of the conjunction fallacy additionally, and uniquely, involved a fronto-parietal network previously linked to supervisory, analytic control processes. The results lend credibility to the idea that incorrect probability judgments are the result of a representativeness heuristic that requires additional neurocognitive resources to avoid.

A Neuroimaging Study of Personality Traits and Self-Reflection

This study examines the blood-oxygen level dependent (BOLD) activation of the brain associated with the four distinctive thinking styles associated with the four personality orientations of the Gountas Personality Orientations (GPO) survey: Emotion/Feeling-Action, Material/Pragmatic, Intuitive/Imaginative, and Thinking/Logical. The theoretical postulation is that each of the four personality orientations has a dominant (primary) thinking style and a shadow (secondary) thinking style/trait. The participants (N = 40) were initially surveyed to determine their dominant (primary) and secondary thinking styles. Based on participant responses, equal numbers of each dominant thinking style were selected for neuroimaging using a unique fMRI cognitive activation paradigm. The neuroimaging data support the general theoretical hypothesis of the existence of four different BOLD activation patterns, associated with each of the four thinking styles. The fMRI data analysis suggests that each thinking style may have its own cognitive activation system, involving the frontal ventromedial, posterior medial, parietal, motor, and orbitofrontal cortex. The data also suggest that there is a left hemisphere relationship for the Material/Pragmatic and Thinking/Logical styles and a right activation relationship for Emotional/Feeling and Intuitive/Imaginative styles. Additionally, the unique self-reflection paradigm demonstrated that perception of self or self-image, may be influenced by personality type; a finding of potentially far-reaching implications.

Developmental frontal brain activation differences in overcoming heuristic bias

Since reasoning is often biased by intuitive heuristics, the development of sound reasoning has long been postulated to depend on successful bias monitoring and inhibition. The present fMRI study aimed to identify neural correlates of developmental changes in these processes. A group of adults and young adolescents were presented with ratio-bias problems in which an intuitively cued heuristic response could be incongruent (conflict item) or congruent (no-conflict item) with the correct response. Results showed that successfully avoiding biased responding on conflict items across both age groups was associated with increased activation in Anterior Cingulate Cortex (ACC) and the right Lateral Prefrontal Cortex (LPFC) regions of interest. Critically, the right LPFC activation decreased with age. Biased responding did not result in right LPFC or ACC modulation and failed to show any developmental activation changes. We discuss implications for ongoing debates on the nature of heuristic bias and its development.

Bilingual and Monolingual First Language Acquisition Experience Differentially Shapes Children's Property Term Learning: Evidence from Behavioral and Neurophysiological Measures

Studies of novel noun learning show bilingual children rely less on the Mutual Exclusivity Constraint (MEC) for word learning than monolinguals. Shifting the focus to learning novel property terms (adjectives), the present study compared 3.5- and five-year-old bilingual and monolingual preschoolers' adherence to the MEC. We found no bilingual-monolingual differences on a behavioral forced-choice task for the 3.5-year-olds, but five-year-old monolinguals adhered more to the MEC than bilinguals did. Older bilinguals adhered less to the MEC than younger ones, while there was no difference in MEC adherence between the younger and older monolinguals. In the 5-year-olds, we additionally acquired neurophysiological data using functional near-infrared spectroscopy (fNIRS) to allow for a first explorative look at potential neuronal underpinnings. The data show that, compared to bilinguals, monolinguals reveal higher activation over three brain regions (right frontal, left temporo-parietal, and left prefrontal) that may be involved in exploiting the MEC, building on conflict detection, inhibition, solution of a disjunction, and working memory processes. Taken together, our behavioral and neurophysiological findings reveal different paths towards novel property term learning depending on children's language acquisition context.

Hemispheric asymmetry in the prefrontal cortex for complex cognition

With the exception of language, hemispheric asymmetry has not historically been an important issue in the frontal lobe literature. Data generated over the past 20 years is forcing a reconsideration of this position. There is now considerable evidence to suggest that the left prefrontal cortex is an inference engine that automatically makes simple conceptual, logical, and causal connections to fill in missing information and eliminate uncertainty or indeterminacy. This is a fine-tuning of the "left hemisphere interpreter" account from the callosotomy patient literature. What is new is an understanding of the important contributions of the right prefrontal cortex to formal logical inference, conflict detection, and indeterminacy tolerance and maintenance. This chapter articulates these claims and reviews the data on which they are based. The chapter concludes by speculating that the inference capabilities of the left prefrontal cortex are built into the very fabric of language and can be accounted for by the left hemisphere dominance for language. The roles of the right PFC require multiple mechanisms for explanation. Its role in formal inference may be a function of its visual-spatial processing capabilities. Its role in conflict detection may be explained as a system for checking for consistency between existing beliefs and new information coming into the system and inferences drawn from beliefs and/or new information. There are at least three possible mechanisms to account for its role in indeterminacy tolerance. First, it could contain a representational system with properties very different from those of language, and an accompanying inference engine. Second, it could just contain this different representational system, and the information is at some point passed back to the left prefrontal cortex for inference. Third, the role of the right prefrontal cortex may be largely preventative. That is, it doesn't provide alternative representational and inference capabilities but simply prevents the left prefrontal cortex from settling on initial, local inferences. The current data do not allow differentiating between these possibilities. Successful real-world functioning requires the participation of both hemispheres.

Executive functions

Executive functions (EFs) include high-order cognitive abilities such as working memory, inhibitory control, cognitive flexibility, planning, reasoning, and problem solving. EFs enable humans to achieve goals, adapt to novel everyday life situations, and manage social interactions. Traditionally EFs have been associated with frontal lobe functioning. More recent evidence shows that posterior and subcortical regions also play a crucial role in EF processing, especially in the integration of sensory information and emotion. This chapter reviews the variety of EFs and their neural underpinning, based on lesion mapping and neuroimaging studies, as well as the evidence for rehabilitation interventions, neuropsychological assessment based on standard and ecologically valid tests, development, and genetic predisposition for recovery of executive functions after brain injury. Taken together, the EFs are critical for unique human abilities and more careful analyses of their subcomponents may help the development of targeted translational interventions to improve them.

A Similarity-Based Process for Human Judgment in the Parietal Cortex

One important distinction in psychology is between inferences based on associative memory and inferences based on analysis and rules. Much previous empirical work conceive of associative and analytical processes as two exclusive ways of addressing a judgment task, where only one process is selected and engaged at a time, in an either-or fashion. However, related work indicate that the processes are better understood as being in interplay and simultaneously engaged. Based on computational modeling and brain imaging of spontaneously adopted judgment strategies together with analyses of brain activity elicited in tasks where participants were explicitly instructed to perform similarity-based associative judgments or rule-based judgments (n = 74), we identified brain regions related to the two types of processes. We observed considerable overlap in activity patterns. The precuneus was activated for both types of judgments, and its activity predicted how well a similarity-based model fit the judgments. Activity in the superior frontal gyrus predicted the fit of a rule-based judgment model. The results suggest the precuneus as a key node for similarity-based judgments, engaged both when overt responses are guided by similarity-based and rule-based processes. These results are interpreted such that similarity-based processes are engaged in parallel to rule-based-processes, a finding with direct implications for cognitive theories of judgment.

The Neural Correlates of Relational Reasoning: A Meta-analysis of 47 Functional Magnetic Resonance Studies

It is a core cognitive ability of humans to represent and reason about relational information, such as “the train station is north of the hotel” or “Charles is richer than Jim.” However, the neural processes underlying the ability to draw conclusions about relations are still not sufficiently understood. Central open questions are as follows: (1) What are the neural correlates of relational reasoning? (2) Where can deductive and inductive reasoning be localized? (3) What is the impact of different informational types on cerebral activity? For that, we conducted a meta-analysis of 47 neuroimaging studies. We found activation of the frontoparietal network during both deductive and inductive reasoning, with additional activation in an extended network during inductive reasoning in the basal ganglia and the inferior parietal cortex. Analyses revealed a double dissociation concerning the lateral and medial Brodmann's area 6 during deductive and inductive reasoning, indicating differences in terms of processing verbal information in deductive and spatial information in inductive tasks. During semantic and symbolic tasks, the frontoparietal network was found active, whereas geometric tasks only elicited prefrontal activation, which can be explained by the reduced demand for the construction of a mental representation in geometric tasks. Our study provides new insights into the cognitive mechanisms underlying relational reasoning and clarifies previous controversies concerning involved brain areas.

Impaired neural processing of transitive relations in children with math learning difficulty

Math learning difficulty (i.e., MLD) is common in children and can have far-reaching consequences in personal and professional life. Converging evidence suggests that MLD is associated with impairments in the intraparietal sulcus (IPS). However, the role that these impairments play in MLD remains unclear. Although it is often assumed that IPS deficits affect core numerical abilities, the IPS is also involved in several non-numerical processes that may contribute to math skills. For instance, the IPS supports transitive reasoning (i.e., the ability to integrate relations such as A > B and B > C to infer that A > C), a skill that is central to many aspects of math learning in children. Here we measured fMRI activity of 8- to 12-year-olds with MLD and typically developing (TD) peers while they listened to stories that included transitive relations. Children also answered questions evaluating whether transitive inferences were made during story comprehension. Compared to non-transitive relations (e.g., A > B and C > D), listening to transitive relations (e.g., A > B and B > C) was associated with enhanced activity in the IPS in TD children. In children with MLD, the difference in activity between transitive and non-transitive relations in the IPS was (i) non-reliable and (ii) smaller than in TD children. Finally, children with MLD were less accurate than TD peers when making transitive inferences based on transitive relations. Thus, a deficit in the online processing of transitive relations in the IPS might contribute to math difficulties in children with MLD.

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Transitive reasoning is central to mathematical thinking.

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Transitive reasoning relies on the intra-parietal sulcus (IPS) in healthy children.

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Math learning difficulty (MLD) is associated with IPS impairments.

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Transitive reasoning is impaired in children with MLD.

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Transitive reasoning does not engage the IPS in children with MLD.

Eye gaze patterns reveal how reasoning skills improve with experience

Reasoning, our ability to solve novel problems, has been shown to improve as a result of learning experiences. However, the underlying mechanisms of change in this high-level cognitive ability are unclear. We hypothesized that possible mechanisms include improvements in the encoding, maintenance, and/or integration of relations among mental representations - i.e., relational thinking. Here, we developed several eye gaze metrics to pinpoint learning mechanisms that underpin improved reasoning performance. We collected behavioral and eyetracking data from young adults who participated in a Law School Admission Test preparation course involving word-based reasoning problems or reading comprehension. The Reasoning group improved more than the Comprehension group on a composite measure of four visuospatial reasoning assessments. Both groups improved similarly on an eyetracking paradigm involving transitive inference problems, exhibiting faster response times while maintaining high accuracy levels; nevertheless, the Reasoning group exhibited a larger change than the Comprehension group on an ocular metric of relational thinking. Across the full sample, individual differences in response time reductions were associated with increased efficiency of relational thinking. Accounting for changes in visual search and a more specific measure of relational integration improved the prediction accuracy of the model, but changes in these two processes alone did not adequately explain behavioral improvements. These findings provide evidence of transfer of learning across different kinds of reasoning problems after completing a brief but intensive course. More broadly, the high temporal precision and rich derivable parameters of eyetracking make it a powerful approach for probing learning mechanisms.

Developmental grey matter changes in superior parietal cortex accompany improved transitive reasoning

The neural basis of developmental changes in transitive reasoning in parietal regions was examined, using voxel-based morphometry. Young adolescents and adults performed a transitive reasoning task, subsequent to undergoing anatomical magnetic resonance imaging (MRI) brain scans. Behaviorally, adults reasoned more accurately than did the young adolescents. Neural results showed (i) less grey matter density in superior parietal cortex in the adults than in the young adolescents, possibly due to a developmental period of synaptic pruning; (ii) improved performance in the reasoning task was negatively correlated with grey matter density in superior parietal cortex in the adolescents, but not in the adult group; and (iii) the latter results were driven by the more difficult trials, requiring greater spatial manipulation. Taken together, the results support the idea that during development, regions in superior parietal cortex are fine-tuned, to support more robust spatial manipulation, resulting in greater accuracy and efficiency in transitive reasoning.

Executive Functions Brain System: An Activation Likelihood Estimation Meta-analytic Study

Background and objective

To characterize commonalities and differences between two executive functions: reasoning and inhibitory control.

Methods

A total of 5,974 participants in 346 fMRI experiments of inhibition or reasoning were selected. First level analysis consisted of Analysis of Likelihood Estimation (ALE) studies performed in two pooled data groups: (a) brain areas involved in reasoning and (b) brain areas involved in inhibition. Second level analysis consisted of two contrasts: (i) brain areas involved in reasoning but not in inhibition and (ii) brain areas involved in inhibition but not in reasoning. Lateralization Indexes were calculated.

Results

Four brain areas appear as the most critical: the dorsolateral aspect of the frontal lobes, the superior parietal lobules, the mesial aspect of the premotor area (supplementary motor area), and some subcortical areas, particularly the putamen and the thalamus. ALE contrasts showed significant differentiation of the networks, with the reasoning > inhibition-contrast showing a predominantly leftward participation, and the inhibition > reasoning-contrast, a clear right advantage.

Conclusion

Executive functions are mediated by sizable brain areas including not only cortical, but also involving subcortical areas in both hemispheres. The strength of activation shows dissociation between the hemispheres for inhibition (rightward) and reasoning (leftward) functions.

Autism and talent: the cognitive and neural basis of systemizing

In 2003, we proposed the hypersystemizing theory of autism. The theory proposes that the human mind possesses a systemizing mechanism (SM) that helps identify lawful regularities (often causal) that govern the input-operation-output workings of a system. The SM can be tuned to different levels, from low to high, with a normal distribution of individual differences in how strongly people search for such input-operation-out-put regularities in any data that is systemizable. Evidence suggests that people with autism are on average hypersystemizers, scoring higher than average on the systemizing quotient and on performance tests of systemizing. In this article, we consider the neural basis behind the SM, since there has been little consideration of the brain basis of systemizing. Finally, we discuss directions for future work in this field.

Meta-analytic evidence for a core problem solving network across multiple representational domains

Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development.

The neural development of pragmatic inference-making in natural discourse

Older interlocutors are more likely than younger ones to make pragmatic inferences, that is, inferences that go beyond the linguistically encoded meaning of a sentence. Here we ask whether pragmatic development is associated with increased activity in brain structures associated with inference-making or in those associated with Theory of Mind. We employed a reading task that presents vignettes in one of two versions, one of which is expected to prompt more pragmatic processing. Both versions present a major premise containing three possibilities (e.g., Xavier is considering Thursday, Friday or Saturday for inviting his girlfriend out). In the Fully-Deductive (control) condition, the major premise is followed by two disjunction-elimination premises through two separate lines (one indicating that Saturday is not convenient and another saying that Thursday is not convenient); this is followed by a valid conclusion (e.g., "I'll reserve Friday"). In the Implicated-Premise condition, the first disjunction-elimination premise is followed by a second similar one that eliminates the same disjunction (e.g., both lines explain why Saturday is not convenient). In this condition, readers may pragmatically enrich the conclusion (i.e., "I'll reserve Friday" pragmatically implicates that Xavier is also eliminating Thursday from consideration). Reading times in Experiment 1 showed that processing the speaker's conclusion in the Implicated-Premise condition becomes increasingly more effort-demanding as readers reach adolescence. Experiment 2 showed that this developmental pattern is related to age-related increases in fMRI activity in fronto-parietal regions typically involved in inference-making processes. We found no evidence indicating age effects related to Theory of Mind areas.