Brain Topography

, Volume 23, Issue 2, pp 119–127 | Cite as

Comparing ICA-based and Single-Trial Topographic ERP Analyses

  • Marzia De Lucia
  • Christoph M. Michel
  • Micah M. Murray
Original Paper

Abstract

Single-trial analysis of human electroencephalography (EEG) has been recently proposed for better understanding the contribution of individual subjects to a group-analyis effect as well as for investigating single-subject mechanisms. Independent Component Analysis (ICA) has been repeatedly applied to concatenated single-trial responses and at a single-subject level in order to extract those components that resemble activities of interest. More recently we have proposed a single-trial method based on topographic maps that determines which voltage configurations are reliably observed at the event-related potential (ERP) level taking advantage of repetitions across trials. Here, we investigated the correspondence between the maps obtained by ICA versus the topographies that we obtained by the single-trial clustering algorithm that best explained the variance of the ERP. To do this, we used exemplar data provided from the EEGLAB website that are based on a dataset from a visual target detection task. We show there to be robust correpondence both at the level of the activation time courses and at the level of voltage configurations of a subset of relevant maps. We additionally show the estimated inverse solution (based on low-resolution electromagnetic tomography) of two corresponding maps occurring at approximately 300 ms post-stimulus onset, as estimated by the two aforementioned approaches. The spatial distribution of the estimated sources significantly correlated and had in common a right parietal activation within Brodmann’s Area (BA) 40. Despite their differences in terms of theoretical bases, the consistency between the results of these two approaches shows that their underlying assumptions are indeed compatible.

Keywords

Single-trial Independent Component Analysis (ICA) Event-Related Potential (ERP) 

Notes

Acknowledgements

This work has been supported by the Swiss National Science Foundation (grant #K-33K1_122518/1). We thank Athina Tzovara for comments on previous versions of this manuscript.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Marzia De Lucia
    • 1
  • Christoph M. Michel
    • 2
  • Micah M. Murray
    • 1
    • 3
    • 4
    • 5
  1. 1.Electroencephalography Brain Mapping Core of the Lemanic, Center for Biomedical Imaging, CHUV 07.081LausanneSwitzerland
  2. 2.The Functional Brain Mapping LaboratoryUniversity of GenevaGenevaSwitzerland
  3. 3.Neuropsychology and Neurorehabilitation Service, Department of Clinical NeuroscienceVaudois University Hospital Center University of LausanneLausanneSwitzerland
  4. 4.Radiology DepartmentVaudois University Hospital Center University of LausanneLausanneSwitzerland
  5. 5.Department of Hearing and Speech SciencesVanderbilt UniversityNashvilleUSA

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