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SUMMARY:Bridging brain and cognition: A multilayer network analysis of bra
 in structural covariance and general intelligence in a developmental sampl
 e of struggling learners - Ivan Simpson-Kent
DTSTART:20210602T150000Z
DTEND:20210602T160000Z
UID:TALK160864@talks.cam.ac.uk
CONTACT:Katharina Zuhlsdorff
DESCRIPTION:Network analytic methods that are ubiquitous in other areas\, 
 such as systems neuroscience\, have recently been used to test network the
 ories in psychology\, including intelligence research. The network or mutu
 alism theory of intelligence proposes that the statistical associations am
 ong cognitive abilities (e.g. specific abilities such as vocabulary or mem
 ory) stem from causal relations among them throughout development. In this
  study\, we used network models (specifically LASSO) of cognitive abilitie
 s and brain structural covariance (grey and white matter) to simultaneousl
 y model brain-behavior relationships essential for general intelligence in
  a large (behavioral\, N=805\; cortical volume\, N=246\; fractional anisot
 ropy\, N=165)\, developmental (ages 5-18) cohort of struggling learners (C
 ALM). We found that mostly positive\, small partial correlations pervade b
 oth our cognitive and neural networks. Moreover\, calculating node central
 ity (absolute strength and bridge strength) and using two separate communi
 ty detection algorithms (Walktrap and Clique Percolation)\, we found conve
 rgent evidence that subsets of both cognitive and neural nodes play an int
 ermediary role between brain and behavior. We discuss implications and pos
 sible avenues for future studies.
LOCATION:Zoom
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