The topology, stability, and instability of learning-induced brain network repertoires in schizophrenia

Author:

Meram Emmanuel D.1,Baajour Shahira1,Chowdury Asadur1,Kopchick John1,Thomas Patricia1,Rajan Usha1,Khatib Dalal1,Zajac-Benitez Caroline1,Haddad Luay1,Amirsadri Alireza1,Stanley Jeffrey A.1,Diwadkar Vaibhav A.1

Affiliation:

1. Department of Psychiatry and Behavioral Neurosciences, Brain Imaging Research Division, Wayne State University School of Medicine, Detroit, MI, USA

Abstract

AbstractThere is a paucity of graph theoretic methods applied to task-based data in schizophrenia (SCZ). Tasks are useful for modulating brain network dynamics, and topology. Understanding how changes in task conditions impact inter-group differences in topology can elucidate unstable network characteristics in SCZ. Here, in a group of patients and healthy controls (n = 59 total, 32 SCZ), we used an associative learning task with four distinct conditions (Memory Formation, Post-Encoding Consolidation, Memory Retrieval, and Post-Retrieval Consolidation) to induce network dynamics. From the acquired fMRI time series data, betweenness centrality (BC), a metric of a node’s integrative value was used to summarize network topology in each condition. Patients showed (a) differences in BC across multiple nodes and conditions; (b) decreased BC in more integrative nodes, but increased BC in less integrative nodes; (c) discordant node ranks in each of the conditions; and (d) complex patterns of stability and instability of node ranks across conditions. These analyses reveal that task conditions induce highly variegated patterns of network dys-organization in SCZ. We suggest that the dys-connection syndrome that is schizophrenia, is a contextually evoked process, and that the tools of network neuroscience should be oriented toward elucidating the limits of this dys-connection.

Funder

National Institute of Mental Health

Ethel and James Flinn Foundation

DMC Foundation

Cohen Neuroscience Endowment

Jack Dorsey Endowment

Lycaki-Young Funds from the State of Michigan

Publisher

MIT Press

Subject

Applied Mathematics,Artificial Intelligence,Computer Science Applications,General Neuroscience

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