Brain connectivity at different time-scales measured with EEG.

Philos Trans R Soc Lond B Biol Sci

Department of Psychiatric Neurophysiology, University Hospital of Clinical Psychiatry Bern, Bolligenstr. 111, 3000 Bern 60, Switzerland.

Published: May 2005

AI Article Synopsis

  • The text provides an overview of methods for analyzing multichannel EEG data, focusing on how to break it down into temporal patterns and spatial distributions.
  • These methods examine the scalp electric field, using various time resolutions for analysis, highlighting that much of the EEG data can be explained by a few topographic distributions.
  • The findings suggest that when multiple brain regions are active simultaneously, they tend to synchronize their activity, forming transient functional networks that could facilitate neurocognitive processes.

Article Abstract

We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1854932PMC
http://dx.doi.org/10.1098/rstb.2005.1649DOI Listing

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