Alpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence

Ilya Zakharov; Anna Tabueva; Timofey Adamovich; Yulia Kovas; Sergey Malykh

doi:10.3389/fnhum.2020.00010

Alpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence

Front Hum Neurosci. 2020 Feb 4:14:10. doi: 10.3389/fnhum.2020.00010. eCollection 2020.

Authors

Ilya Zakharov¹, Anna Tabueva¹, Timofey Adamovich¹, Yulia Kovas^{2

3}, Sergey Malykh¹

Affiliations

¹ Developmental Behavioral Genetics Laboratory, Psychological Institute of the Russian Academy of Education, Moscow, Russia.
² Department of Psychology, Goldsmiths University of London, London, United Kingdom.
³ International Centre for Research in Human Development, Tomsk State University, Tomsk, Russia.

Abstract

The aim of the present study was to investigate whether EEG resting state connectivity correlates with intelligence. One-hundred and sixty five participants took part in the study. Six minutes of eyes closed EEG resting state was recorded for each participant. Graph theoretical connectivity metrics were calculated separately for two well-established synchronization measures [weighted Phase Lag Index (wPLI) and Imaginary Coherence (iMCOH)] and for sensor- and source EEG space. Non-verbal intelligence was measured with Raven's Progressive Matrices. In line with the Neural Efficiency Hypothesis, path lengths characteristics of the brain networks (Average and Characteristic Path lengths, Diameter and Closeness Centrality) within alpha band range were significantly correlated with non-verbal intelligence for sensor space but no for source space. According to our results, variance in non-verbal intelligence measure can be mainly explained by the graph metrics built from the networks that include both weak and strong connections between the nodes.

Keywords: EEG; connectivity; graph theory; intelligence; neural efficiency; resting state.