Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality.

Full Abstract

Event-related potentials (ERPs) induced by visual perception and cognitive tasks have been extensively studied in neuropsychological experiments. ERP activities time-locked to stimulus presentation and task performance are often observed separately at individual scalp channels based on averaged time series across epochs and experimental subjects. An analysis using averaged EEG dynamics could discount information regarding interdependency between ongoing EEG and salient ERP features. Advanced tools such as independent component analysis (ICA) have been developed for decomposing collections of single-trial EEG records into separate features. Those features (or independent components) can then be mapped onto the cortical surface using source localization algorithms to visualize brain activation maps and to study between-subject consistency. In this study, we propose a statistical framework for estimating the time course of spatiotemporally independent EEG components simultaneously with their cortical distributions. Within this framework, we implemented Bayesian spatiotemporal analysis for imaging the sources of EEG features on the cortical surface. The framework allows researchers to include prior knowledge regarding spatial locations as well as spatiotemporal independence of different EEG sources. The use of the Electromagnetic Spatiotemporal ICA (EMSICA) method is illustrated by mapping event-related EEG dynamics induced by events in a visual two-back continuous performance task. The proposed method successfully identified several interesting components with plausible corresponding cortical activation topographies, including processes contributing to the late positive complex (LPC) located in central parietal, frontal midline, and anterior cingulate cortex, to atypical mu rhythms associated with the precentral gyrus, and to the central posterior alpha activity in the precuneus.

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Author information

Author/s: Tsai, Arthur C (AC); Liou, Michelle (M); Jung, Tzyy-Ping (TP); Onton, Julie A (JA); Cheng, Philip E (PE); Huang, Chien-Chih (CC); Duann, Jeng-Ren (JR); Makeig, Scott (S);

Affiliation: Institute of Statistical Science, Academia Sinica, Taipei 115, Taiwan. arthur(-atsign-)stat.sinica.edu.tw

Grants: R01 MH/RR 61619-01 (Agency:NIMH NIH HHS) ; R01 NS 047293 (Agency:NINDS NIH HHS)

Journal and publication information

Publication Type: Comparative Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't

Journal: NeuroImage (Neuroimage), published in United States. (Language: eng)

Reference: 2006-Aug; vol 32 (issue 1) : pp 195-207

Dates: Created 2006/07/24; Completed 2006/09/15; Revised 2007/11/14;

PMID: 16730194, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Artifacts
Brain Mapping
Cerebral Cortex - anatomy & histology; physiology
Electroencephalography
Evoked Potentials - physiology

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