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Resolving the connectome – Spectrally-specific functional connectivity networks and their distinct contributions to behaviour

Becker, Robert; Hervais-Adelman, Alexis (2019). Resolving the connectome – Spectrally-specific functional connectivity networks and their distinct contributions to behaviour. bioRxiv 700278, Cold Spring Harbor Laboratory.

Abstract

In the absence of a task, the brain at rest spontaneously displays activity that reflects features of the underlying neural substrate. Examination of inter-areal coupling of resting state oscillatory activity reveals that the brain’s resting activity is composed of functionally connected networks, which differ depending upon oscillatory frequency, suggesting a role for carrier frequency as a means of creating multiplexed, or functionally segregated, communication channels between brain areas. In a group of 89 participants we examined spectrally-resolved resting-state connectivity patterns derived from MEG recordings to determine the relationship between connectivity intrinsic to different frequency channels and a battery of over a hundred behavioural and demographic indicators, using canonical correlation analysis. We demonstrate that each of the classical frequency bands in the range 1-40Hz (delta, theta, alpha, beta and gamma) delineates a subnetwork that is behaviourally relevant, spatially distinct, and whose expression is predictive of either positive or negative individual traits.

Additional indexing

Item Type:Working Paper
Communities & Collections:06 Faculty of Arts > Institute of Psychology
Dewey Decimal Classification:150 Psychology
Language:English
Date:2019
Deposited On:31 Oct 2019 09:37
Last Modified:29 May 2024 10:55
Series Name:bioRxiv
ISSN:2164-7844
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1101/700278
Project Information:
  • Funder: SNSF
  • Grant ID: PP00P1_163726
  • Project Title: Exploring audio-motor integration: a novel approach to overcoming hearing impairment
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  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

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