Emotional intelligence is associated with connectivity within and between resting state networks

William D.S. Killgore, Ryan Smith, Elizabeth A. Olson, Mareen Weber, Scott L. Rauch, Lisa D. Nickerson

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Emotional intelligence (EI) is defined as an individual's capacity to accurately perceive, understand, reason about, and regulate emotions, and to apply that information to facilitate thought and achieve goals. Although EI plays an important role in mental health and success in academic, professional and social realms, the neurocircuitry underlying this capacity remains poorly characterized, and no study to date has yet examined the relationship between EI and intrinsic neural network function. Here, in a sample of 54 healthy individuals (28 women, 26 men), we apply independent components analysis (ICA) with dual regression to functional magnetic resonance imaging (fMRI) data acquired while subjects were resting in the scanner to investigate brain circuits (intrinsic resting state networks) whose activity is associated with greater self-reported (i.e. Trait) and objectively measured (i.e. Ability) EI. We show that higher Ability EI, but not Trait EI, is associated with stronger negatively correlated spontaneous fMRI signals between the basal ganglia/limbic network (BGN) and posterior default mode network (DMN), and regions involved in emotional processing and regulation. Importantly, these findings suggest that the functional connectivity within and between intrinsic networks associated with mentation, affective regulation, emotion processing, and reward are strongly related to ability EI.

Original languageEnglish (US)
Pages (from-to)1624-1636
Number of pages13
JournalSocial cognitive and affective neuroscience
Volume12
Issue number10
DOIs
StatePublished - Oct 1 2017

Keywords

  • Emotional intelligence
  • FMRI
  • FSL
  • Neuroimaging
  • Resting state functional connectivity

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience

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