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

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.

Keywords: FSL; emotional intelligence; fMRI; neuroimaging; resting state functional connectivity.

Fig. 1.

3D views and several axial slices are shown for the: (A) Anterior default mode network (A-DMN): ventral and dorsal medial prefrontal cortex (PFC), anterior and posterior cingulate (A/PCC), precuneus, caudate and posterior parietal regions, (B) Basal ganglia/limbic network: limbic-paralimbic-striatal regions including inferior insula, basal ganglia (striatum, pallidum, NAcc, subthalamic nucleus, and substantia nigra), amygdala, and thalamus, (C) Posterior default mode network (P-DMN): precuneus/PCC, posterior parietal, and frontal cortex (including Brodmann area 8), (D) Reward learning network: ventromedial and orbital PFC, caudate, and nucleus accumbens. RSNs shown in red-yellow and overlaid onto the MNI 152 2 mm standard brain (Z > 2.6).

Fig. 2.

Basal ganglia/limbic network. (A) Three orthogonal slices showing regions whose functional connectivity with the basal ganglia network (green) is negatively linearly associated with MSCEIT scores (i.e. reflecting Ability EI; red–yellow, P < 0.05 corrected). The crosshairs show one region in the medial PFC. (B) 3D view to better illustrate the spatial extent/pattern. (C) Functional connectivity values (regression coefficients averaged over voxels in red–yellow) plotted against MSCEIT: Total and MSCEIT subscales for Facilitating, Managing, Perceiving, and Understanding. Partial correlation coefficients (PCC) between functional connectivity values and MSCEIT scores are shown for each subscale.

Fig. 3.

Posterior DMN network. Two orthogonal slices for two different x locations showing regions whose functional connectivity with the DMN is negatively linearly related to MSCEIT scores (i.e. reflecting Ability EI; red–yellow, P < 0.05, corrected). Crosshairs in (A) bisect the amygdala and crosshairs in (B), the nucleus accumbens. (C) 3D view to better illustrate the spatial extent/pattern. (D) Functional connectivity values plotted against MSCEIT scores (PCCs are shown for each subscale).

Fig. 4.

(Left) Hierarchical clustering shows between-network correlations. The dendrogram is shown in the top of the figure, the RSNs in the middle, and the correlation matrix at the bottom (correlation coefficients shown in the bottom triangular portion and partial correlations shown in the top triangular portion). (Right) Scatterplots showing the significant association between Ability EI (MSCEIT) scales and the major network connectivity (represented as z-transformed partial correlation coefficients in the y-axis). A-DMN, anterior default mode network; BGN, basal ganglia/limbic network; P-DMN, posterior default mode network; PCC, partial correlation coefficient; RLN, reward learning network.