文章基本信息

标题：Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners
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作者：Ivan L. Simpson-Kent ; Eiko I. Fried ; Danyal Akarca 等
期刊名称：Journal of Intelligence
电子版ISSN：2079-3200
出版年度：2021
卷号：9
期号：2
页码：32
DOI：10.3390/jintelligence9020032
出版社：MDPI Publishing
摘要：Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain–behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5–18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role ‘between’ brain and behavior. We discuss implications and possible avenues for future studies.
关键词：general intelligence; cortical volume; fractional anisotropy; brain structural covariance; cognitive network neuroscience; multilayer network analysis general intelligence ; cortical volume ; fractional anisotropy ; brain structural covariance ; cognitive network neuroscience ; multilayer network analysis