Spatiotemporal analysis of multichannel EEG: CARTOOL
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TLDR
Methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and their implementation in the software CARTOOL, designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images.Abstract:
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.read more
Citations
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Towards the utilization of EEG as a brain imaging tool
TL;DR: It is shown that many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies, which is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals.
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Microstates in resting-state EEG: Current status and future directions
TL;DR: It is suggested that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease.
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Electroencephalographic source imaging: a prospective study of 152 operated epileptic patients
Verena Brodbeck,Laurent Spinelli,Agustina M. Lascano,Michael Wissmeier,Maria Vargas,Serge Vulliemoz,Claudio Pollo,Karl Lothard Schaller,Christoph M. Michel,Margitta Seeck +9 more
TL;DR: It is concluded that electric source imaging is a highly valuable tool in pre-surgical epilepsy evaluation given the low cost and high flexibility of electroencephalographic systems even with high channel counts.
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EEG Source Imaging: A Practical Review of the Analysis Steps.
Christoph M. Michel,Denis Brunet +1 more
TL;DR: This review explains several steps needed to pass from the recording of the EEG to 3-dimensional images of neuronal activity and illustrates them in a comprehensive analysis pipeline integrated in a stand-alone freely available academic software: Cartool.
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EEG source localization: Sensor density and head surface coverage.
Jasmine Song,Colin Davey,Catherine Poulsen,Phan Luu,Sergei Turovets,Erik Anderson,Kai Li,Don M. Tucker +7 more
TL;DR: The most accurate source localization is obtained when the voltage surface is densely sampled over both the superior and inferior surfaces, as well as across all sampling density and inverse methods.
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