Table of Contents Author Guidelines Submit a Manuscript
Computational Intelligence and Neuroscience
Volume 2011, Article ID 813870, 15 pages
Review Article

Spatiotemporal Analysis of Multichannel EEG: CARTOOL

1Functional Brain Mapping Laboratory, Departments of Fundamental and Clinical Neurosciences, University Medical School, University of Geneva, 1 rue Michel-Servet, 1211 Geneva, Switzerland
2EEG Brain Mapping Core, Center for Biomedical Imaging (CIBM), 1211 Geneva, Switzerland
3The Functional Electrical Neuroimaging Laboratory, Department of Clinical Neurosciences and Department of Radiology, Vaudois University Hospital Center, University of Lausanne, 1011 Lausanne, Switzerland

Received 7 September 2010; Accepted 10 November 2010

Academic Editor: Sylvain Baillet

Copyright © 2011 Denis Brunet et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way.