Dynamics of task-related electrophysiological networks: a benchmarking study

Neuroimage. 2021 May 1:231:117829. doi: 10.1016/j.neuroimage.2021.117829. Epub 2021 Feb 5.

Abstract

Motor, sensory and cognitive functions rely on dynamic reshaping of functional brain networks. Tracking these rapid changes is crucial to understand information processing in the brain, but challenging due to the great variety of dimensionality reduction methods used at the network-level and the limited evaluation studies. Using Magnetoencephalography (MEG) combined with Source Separation (SS) methods, we present an integrated framework to track fast dynamics of electrophysiological brain networks. We evaluate nine SS methods applied to three independent MEG databases (N=95) during motor and memory tasks. We report differences between these methods at the group and subject level. We seek to help researchers in choosing objectively the appropriate SS method when tracking fast reconfiguration of functional brain networks, due to its enormous benefits in cognitive and clinical neuroscience.

Keywords: Dimensionality reduction; Dynamic functional connectivity; Electrophysiological brain networks; Magneto-encephalography (MEG); Source separation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Benchmarking / methods*
  • Brain / physiology*
  • Databases, Factual
  • Electrophysiological Phenomena / physiology
  • Female
  • Humans
  • Magnetoencephalography / methods
  • Male
  • Memory, Short-Term / physiology*
  • Movement / physiology*
  • Nerve Net / physiology*
  • Psychomotor Performance / physiology*
  • Young Adult