Zakharov, Ilya; Tabueva, Anna; Adamovich, Timofey; Kovas, Yulia and Malykh, Sergey. 2020. Alpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence. Frontiers in Human Neuroscience, 14(10), ISSN 1662-5161 [Article]

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Abstract or Description

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.

Item Type:	Article
Identification Number (DOI):	https://doi.org/10.3389/fnhum.2020.00010
Additional Information:	The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnhum.2020.00010/full#supplementary-material
Keywords:	EEG, resting state, connectivity, intelligence, neural efficiency, graph theory
Departments, Centres and Research Units:	Psychology
Dates:	Date Event 13 January 2020 Accepted 4 February 2020 Published Online
Item ID:	28438
Date Deposited:	11 May 2020 14:18
Last Modified:	11 May 2020 14:18
Peer Reviewed:	Yes, this version has been peer-reviewed.
URI:	https://research.gold.ac.uk/id/eprint/28438

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