Independent Components of Magnetoencephalography: Localization


We applied second-order blind identification (SOBI), an independent component analysis method, to MEG data collected during cognitive tasks. We explored SOBI's ability to help isolate underlying neuronal sources with relatively poor signal-to-noise ratios, allowing their identification and localization. We compare localization of the SOBI-separated components to localization from unprocessed sensor signals, using an equivalent current dipole modeling method. For visual and somatosensory modalities, SOBI preprocessing resulted in components that can be localized to physiologically and anatomically meaningful locations. Furthermore, this preprocessing allowed the detection of neuronal source activations that were otherwise undetectable. This increased probability of neuronal source detection and localization can be particularly beneficial for MEG studies of higher-level cognitive functions, which often have greater signal variability and degraded signal-to-noise ratios than sensory activation tasks.

DOI: 10.1162/089976602760128036

Extracted Key Phrases

8 Figures and Tables


Citations per Year

180 Citations

Semantic Scholar estimates that this publication has 180 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@article{Tang2002IndependentCO, title={Independent Components of Magnetoencephalography: Localization}, author={Akaysha C. Tang and Barak A. Pearlmutter and Natalie A. Malaszenko and Dan B. Phung and Bethany C. Reeb}, journal={Neural computation}, year={2002}, volume={14 8}, pages={1827-58} }