Literature DB >> 30630078

Individual variation in brain network topology is linked to emotional intelligence.

George Ling1, Ivy Lee1, Synthia Guimond1, Olivia Lutz1, Neeraj Tandon1, Uzma Nawaz1, Dost Öngür2, Shaun Eack3, Kathryn E Lewandowski2, Matcheri Keshavan1, Roscoe Brady4.   

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.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Emotional intelligence; Magnetic resonance imaging; Network; Schizophrenia; Social cognition; Topography

Mesh:

Year:  2019        PMID: 30630078      PMCID: PMC6800254          DOI: 10.1016/j.neuroimage.2019.01.013

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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