University of Cambridge > Talks.cam > CamBRAIN Virtual Journal Club > Bridging brain and cognition: A multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners

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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  • UserIvan Simpson-Kent
  • ClockWednesday 02 June 2021, 16:00-17:00
  • HouseZoom.

If you have a question about this talk, please contact Katharina Zuhlsdorff.

https://us02web.zoom.us/j/85395342039

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 both our cognitive and neural networks. Moreover, calculating node centrality (absolute strength and bridge strength) and using two separate community detection algorithms (Walktrap and Clique Percolation), 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.

This talk is part of the CamBRAIN Virtual Journal Club series.

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