Individual variation in brain network topology is linked to emotional intelligence

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. HIGHLIGHTSLarge, distributed brain networks show significant individual variation in topology.The cognitive or behavior significance of this variation is largely undetermined.We observe that network topology is strongly linked to emotional intelligence.This network‐cognition link is trans‐diagnostic and observed in schizophrenia.

[1]  William D S Killgore,et al.  Highways of the emotional intellect: white matter microstructural correlates of an ability-based measure of emotional intelligence , 2017, Social neuroscience.

[2]  R. Cameron Craddock,et al.  A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics , 2013, NeuroImage.

[3]  Mark W. Woolrich,et al.  The relationship between spatial configuration and functional connectivity of brain regions , 2017 .

[4]  John H Krystal,et al.  Functional hierarchy underlies preferential connectivity disturbances in schizophrenia , 2015, Proceedings of the National Academy of Sciences.

[5]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[6]  D. Barch,et al.  Fronto‐temporal connectivity predicts cognitive empathy deficits and experiential negative symptoms in schizophrenia , 2017, Human brain mapping.

[7]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[8]  C. Kohler,et al.  Facial emotion perception in schizophrenia: a meta-analytic review. , 2010, Schizophrenia bulletin.

[9]  P. Salovey,et al.  Measuring emotional intelligence with the MSCEIT V2.0. , 2003, Emotion.

[10]  L. DeLisi,et al.  The relationship between default mode network connectivity and social functioning in individuals at familial high-risk for schizophrenia , 2014, Schizophrenia Research.

[11]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[12]  Karl J. Friston,et al.  Movement‐Related effects in fMRI time‐series , 1996, Magnetic resonance in medicine.

[13]  Katie L. McMahon,et al.  A multivariate distance-based analytic framework for connectome-wide association studies , 2014, NeuroImage.

[14]  G. Strauss,et al.  Factor analytic support for social cognition as a separable cognitive domain in schizophrenia , 2007, Schizophrenia Research.

[15]  Michael F. Green,et al.  Social cognition in schizophrenia: an NIMH workshop on definitions, assessment, and research opportunities. , 2008, Schizophrenia bulletin.

[16]  R. Haier,et al.  The Parieto-Frontal Integration Theory (P-FIT) of intelligence: Converging neuroimaging evidence , 2007, Behavioral and Brain Sciences.

[17]  David C. Van Essen,et al.  Application of Information Technology: An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex , 2001, J. Am. Medical Informatics Assoc..

[18]  J. Kable,et al.  Common Dimensional Reward Deficits Across Mood and Psychotic Disorders: A Connectome-Wide Association Study. , 2017, The American journal of psychiatry.

[19]  Timothy Edward John Behrens,et al.  Diffusion-Weighted Imaging Tractography-Based Parcellation of the Human Parietal Cortex and Comparison with Human and Macaque Resting-State Functional Connectivity , 2011, The Journal of Neuroscience.

[20]  M. Chun,et al.  Functional connectome fingerprinting: Identifying individuals based on patterns of brain connectivity , 2015, Nature Neuroscience.

[21]  Rodrigo M. Braga,et al.  Parallel Interdigitated Distributed Networks within the Individual Estimated by Intrinsic Functional Connectivity , 2017, Neuron.

[22]  J. R. Hays,et al.  Concurrent Validity of the Wechsler Abbreviated Scale of Intelligence and the Kaufman Brief Intelligence Test among Psychiatric Inpatients , 2002, Psychological reports.

[23]  Efstathios D. Gennatas,et al.  Common and Dissociable Mechanisms of Executive System Dysfunction Across Psychiatric Disorders in Youth. , 2016, The American journal of psychiatry.

[24]  M. Green,et al.  The causal relationships between neurocognition, social cognition and functional outcome over time in schizophrenia: a latent difference score approach , 2012, Psychological Medicine.

[25]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[26]  Ellen Vos,et al.  Theory of mind in schizophrenia: meta-analysis. , 2007, The British journal of psychiatry : the journal of mental science.

[27]  Evan M. Gordon,et al.  Individual-specific features of brain systems identified with resting state functional correlations , 2017, NeuroImage.

[28]  Michael F. Green,et al.  The MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and validity. , 2008, The American journal of psychiatry.

[29]  M. Keshavan,et al.  Development of novel behavioral interventions in an experimental therapeutics world: Challenges, and directions for the future , 2017, Schizophrenia Research.

[30]  E. Bora,et al.  Cognitive endophenotypes of bipolar disorder: a meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives. , 2009, Journal of affective disorders.

[31]  Thomas E. Nichols,et al.  A positive-negative mode of population covariation links brain connectivity, demographics and behavior , 2015, Nature Neuroscience.

[32]  Seongho Kim ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients. , 2015, Communications for statistical applications and methods.

[33]  Matthew A. Zapala,et al.  Multivariate regression analysis of distance matrices for testing associations between gene expression patterns and related variables , 2006, Proceedings of the National Academy of Sciences.

[34]  Yufeng Zang,et al.  DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging , 2016, Neuroinformatics.

[35]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[36]  Tianzi Jiang,et al.  Convergent functional architecture of the superior parietal lobule unraveled with multimodal neuroimaging approaches , 2015, Human brain mapping.

[37]  B T Thomas Yeo,et al.  Disruption of cortical association networks in schizophrenia and psychotic bipolar disorder. , 2014, JAMA psychiatry.

[38]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[39]  Evan M. Gordon,et al.  Precision Functional Mapping of Individual Human Brains , 2017, Neuron.

[40]  W. Horan,et al.  Social Cognition in Schizophrenia , 2010 .

[41]  Michael F. Green,et al.  Social cognition in schizophrenia: Relationships with neurocognition and negative symptoms , 2007, Schizophrenia Research.

[42]  J. Os,et al.  The relationship between neurocognition and social cognition with functional outcomes in schizophrenia: A meta-analysis , 2011, Neuroscience & Biobehavioral Reviews.

[43]  R. Gunderman,et al.  Emotional intelligence. , 2011, Journal of the American College of Radiology : JACR.

[44]  Evan M. Gordon,et al.  Functional System and Areal Organization of a Highly Sampled Individual Human Brain , 2015, Neuron.

[45]  M. Fox,et al.  Individual Variability in Functional Connectivity Architecture of the Human Brain , 2013, Neuron.

[46]  M. First,et al.  Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research version (SCID-I RV) , 2002 .

[47]  S. Marder The NIMH-MATRICS project for developing cognition-enhancing agents for schizophrenia , 2006, Dialogues in clinical neuroscience.

[48]  D. Penn,et al.  Deficits in domains of social cognition in schizophrenia: a meta-analysis of the empirical evidence. , 2013, Schizophrenia bulletin.

[49]  M. Keshavan,et al.  Social and neuro-cognition as distinct cognitive factors in schizophrenia: A systematic review , 2013, Schizophrenia Research.

[50]  J. Csernansky,et al.  Default Mode Functional Connectivity Is Associated With Social Functioning in Schizophrenia , 2017, Journal of abnormal psychology.

[51]  M. Chun,et al.  A neuromarker of sustained attention from whole-brain functional connectivity , 2015, Nature Neuroscience.

[52]  M. Chun,et al.  Functional connectome fingerprinting: Identifying individuals based on patterns of brain connectivity , 2015, Nature Neuroscience.

[53]  Evan M. Gordon,et al.  Long-term neural and physiological phenotyping of a single human , 2015, Nature Communications.

[54]  M. Keshavan,et al.  Assessing social-cognitive deficits in schizophrenia with the Mayer-Salovey-Caruso Emotional Intelligence Test. , 2010, Schizophrenia bulletin.

[55]  U. Mehta,et al.  Neurocognitive predictors of social cognition in remitted schizophrenia , 2014, Psychiatry Research.

[56]  K. Amunts,et al.  Probabilistic maps, morphometry, and variability of cytoarchitectonic areas in the human superior parietal cortex. , 2008, Cerebral cortex.

[57]  Michael F. Green,et al.  Impact of cognitive and social cognitive impairment on functional outcomes in patients with schizophrenia. , 2016, The Journal of clinical psychiatry.

[58]  Ivan Toni,et al.  On the relationship between the “default mode network” and the “social brain” , 2012, Front. Hum. Neurosci..

[59]  R. Buckner,et al.  Parcellating Cortical Functional Networks in Individuals , 2015, Nature Neuroscience.