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

Impact of corpus callosum integrity on functional interhemispheric connectivity and cognition in healthy subjects

To examine the corpus callosum's (CC) integrity in terms of fractional anisotropy (FA) and how it affects resting-state hemispheric connectivity (rs-IHC) and cognitive function in healthy individuals. Sixty-eight healthy individuals were recruited for the study. The global FA (gFA) and FA values of each CC tract (forceps minor, body, tapetum, and forceps major) were evaluated using diffusion-weighted imaging (DWI) sequences. The homotopic functional connectivity technique was used to quantify the effects of FA in the CC tracts on bilateral functional connectivity, including the confounding effect of gFA. Brain regions with higher or lower rs-IHC were identified using the threshold-free cluster enhancement family-wise error-corrected p-value of 0.05. The null hypothesis was rejected if the p-value was ≤ 0.05 for the nonparametric partial correlation technique. Several clusters of increased rs-IHC were identified in relation to the FA of individual CC tracts, each with a unique topographic distribution and extension. Only forceps minor FA values correlated with cognitive scores. The integrity of CC influences rs-IHC differently in healthy subjects. Specifically, forceps minor anisotropy impacts rs-IHC and cognition more than other CC tracts do.

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.

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.

Motor imagery and engagement favour spatial reasoning

Based on the assumption that spatial reasoning relies on the construction of mental models of the states of affairs described in the premises, and on evidence that sensory-motor imagery can enhance cognitive abilities, we hypothesised that imagining moving the objects mentioned in the premises to the specific spatial locations should favour spatial reasoning. The results of Experiment 1 confirmed the prediction: when participants imagined moving the objects mentioned in the premises (dynamic-engagement condition), they drew accurate inferences faster compared with participants who merely read the premises (static-non-engagement condition). Experiment 2 was in part a replication of Experiment 1 but included two additional experimental conditions to control for possible effects of self-engagement in reasoning: in one condition, participants imagined that someone else was moving the objects (dynamic-non-engagement condition), and in the other condition, participants imagined that they were observing the objects (static-engagement condition). The results revealed an interaction between motor imagery and engagement in decreasing response times to spatial problems. We discuss the practical implications of the current results.

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 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.

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.