Neural activity and network analysis for understanding reasoning using the matrix reasoning task

Author:

Caudle M. M.ORCID,Spadoni A. D.,Schiehser D. M.,Simmons A. N.,Bomyea J.ORCID

Abstract

AbstractReasoning requires the ability to manipulate mental representations and understand relationships between objects. There is a paucity of research regarding the functional connections between multiple brain areas that may interact during commonly used reasoning tasks. The present study aimed to examine functional activation and connectivity of frontoparietal regions during a Matrix Decision Making Task, completed by twenty-one right-handed healthy participants while undergoing fMRI. Voxel-wise whole brain analysis of neural response to the task revealed activation spanning dorsal and lateral prefrontal, occipital, and parietal regions. Utilizing Group Iterative Multiple Model Estimation, a data-driven approach that estimates the presence and direction of connectivity between specific ROIs, connectivity between prefrontal and sensory processing regions were revealed. Moreover, the magnitude of connectivity strength between the left precentral gyrus and left dorsal cingulate (dACC) was positively correlated with MR behavioral performance. Taken together, results are consistent with earlier work demonstrating involvement of regions comprising the central executive network in relational reasoning. These data expand existing knowledge regarding communication of key brain regions during the task and demonstrate that understanding how key brain regions are interconnected can effectively predict the quality of behavioral output.

Funder

Center of Excellence for Stress and Mental Health

U.S. Department of Veterans Affairs

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Cognitive Neuroscience,Experimental and Cognitive Psychology,General Medicine

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1. In-Depth Application of Neural Network in Software Information Classification and Identification;2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE);2023-11-02

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