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Individual variation in brain network topology is linked to emotional intelligence

Authors :
Kathryn E. Lewandowski
Olivia Lutz
Dost Öngür
Shaun M. Eack
Neeraj Tandon
Synthia Guimond
George Ling
Uzma Nawaz
Ivy Lee
Matcheri S. Keshavan
Roscoe O. Brady
Source :
NeuroImage. 189
Publication Year :
2018

Abstract

Background Social cognitive ability is a significant determinant of functional outcome, and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits. Objective Using ‘resting state’ functional magnetic resonance imaging (rsfMRI) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition. Methods The study included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 45 healthy controls. All participants underwent a rsfMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis examined how each individual brain voxel's connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR). Results We identified a region in the left superior parietal lobule (SPL) where individual network topology is linked to emotional intelligence. Specifically, in high scoring individuals, this region is a node of the Default Mode Network and in low scoring individuals, it is a node of the Dorsal Attention Network. This relationship was observed in both schizophrenia and healthy comparison participants. Conclusion Prior studies have demonstrated individual variance in the topology of canonical resting state networks but the cognitive or behavioral relevance of these differences has largely been undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale resting-state networks and that network topology is linked to emotional intelligence.

Details

ISSN :
10959572
Volume :
189
Database :
OpenAIRE
Journal :
NeuroImage
Accession number :
edsair.doi.dedup.....1619de2f4f01e912874cfb9a5ced88c3