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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 700278v1, University of Zurich.

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.

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.

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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 Jul 2020 11:36
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
Official URL:https://www.biorxiv.org/content/10.1101/700278v1
Project Information:
  • : FunderSNSF
  • : Grant IDPP00P1_163726
  • : Project TitleExploring audio-motor integration: a novel approach to overcoming hearing impairment

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