Highways of the emotional intellect: white matter microstructural correlates of an ability-based measure of emotional intelligence

Derek A. Pisner, Ryan Smith, Anna Alkozei, Aleksandra Klimova, William Killgore

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Individuals differ in their ability to understand emotional information and apply that understanding to make decisions and solve problems effectively – a construct known as Emotional Intelligence (EI). While considerable evidence supports the importance of EI in social and occupational functioning, the neural underpinnings of this capacity are relatively unexplored. We used Tract-Based Spatial Statistics (TBSS) to determine the white matter correlates of EI as measured by the ability-based Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT). Participants included 32 healthy adults (16 men; 16 women), aged 18–45 years. White matter integrity in key tracts was positively correlated with the Strategic Area branches of the MSCEIT (Understanding Emotions and Managing Emotions), but not the Experiential branches (Perceiving and Facilitating Emotions). Specifically, the Understanding Emotions branch was associated with greater fractional anisotropy (FA) within somatosensory and sensory-motor fiber bundles, particularly those of the left superior longitudinal fasciculus and corticospinal tract. Managing Emotions was associated with greater FA within frontal-affective association tracts including the anterior forceps and right uncinate fasciculus, along with frontal-parietal cingulum and interhemispheric corpus callosum tracts. These findings suggest that specific components of EI are directly related to the structural microarchitecture of major axonal pathways.

Original languageEnglish (US)
Pages (from-to)1-15
Number of pages15
JournalSocial Neuroscience
DOIs
Publication statusAccepted/In press - May 7 2016

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Keywords

  • diffusion tensor imaging
  • Emotional intelligence
  • tract-based spatial statistics

ASJC Scopus subject areas

  • Behavioral Neuroscience
  • Development
  • Social Psychology

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