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A Cortical Surface-Based Meta-Analysis of Human Reasoning

Title
A Cortical Surface-Based Meta-Analysis of Human Reasoning
Author(s)
Shin, MinhoJeon, Hyeon-Ae
Issued Date
2021-12
Citation
Cerebral Cortex, v.31, no.12, pp.5497 - 5510
Type
Article
Author Keywords
log-Gaussian Cox processBayesian meta-analysis of the cortical surface (BMACS)functional magnetic resonance imaginginductive and deductive reasoningintegrated nested Laplace approximation (INLA)
Keywords
FUNCTIONAL NEUROIMAGING DATACOORDINATE-BASED METAANALYSISPREFRONTAL CORTEXINFERENCELANGUAGEFMRIINTELLIGENCENEUROANATOMYSYSTEMMNI
ISSN
1047-3211
Abstract
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. © The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
URI
http://hdl.handle.net/20.500.11750/13812
DOI
10.1093/cercor/bhab174
Publisher
Oxford University Press
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Department of Brain Sciences Laboratory of Cognitive Neuroscience 1. Journal Articles

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