TY - JOUR
T1 - Isolation of epileptiform discharges from unaveraged EEG by independent component analysis
AU - Kobayashi, K.
AU - James, C. J.
AU - Nakahori, T.
AU - Akiyama, T.
AU - Gotman, J.
N1 - Funding Information:
We thank Dr Makeig for providing a program of ICA for MATLAB on his web page. We translated his program to C++. This study was supported in part by grant MT-10189 of the Medical Research Council of Canada.
PY - 1999/10/1
Y1 - 1999/10/1
N2 - Objective: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different waveforms and spatial distributions. Methods: The separation employs independent component analysis (ICA) and is not based on any assumption regarding generator model. A simulation study was performed by generating ten EEG data matrices by computer: each matrix included real background activity from a normal subject to which was added an array of simulated unaveraged EDs. Each discharge was a summation of two transients having slightly different potential field distributions and small jitters in time and amplitude. Real EEG data were also obtained from three epileptic patients. Results: Through ICA, we could isolate the two epileptiform transients in every simulation matrix, and the retrieved transients were almost identical as the originals, especially in their spatial distributions. Two epileptic components were isolated by ICA in all patients. Each estimated epileptic component had a consistent time course. Conclusion: ICA appears promising for the separation of unaveraged spikes from the EEG background and their decomposition in independent spatio-temporal components.
AB - Objective: We propose a method that allows the separation of epileptiform discharges (EDs) from the EEG background, including the ED's waveform and spatial distribution. The method even allows to separate a spike in two components occurring at approximately the same time but having different waveforms and spatial distributions. Methods: The separation employs independent component analysis (ICA) and is not based on any assumption regarding generator model. A simulation study was performed by generating ten EEG data matrices by computer: each matrix included real background activity from a normal subject to which was added an array of simulated unaveraged EDs. Each discharge was a summation of two transients having slightly different potential field distributions and small jitters in time and amplitude. Real EEG data were also obtained from three epileptic patients. Results: Through ICA, we could isolate the two epileptiform transients in every simulation matrix, and the retrieved transients were almost identical as the originals, especially in their spatial distributions. Two epileptic components were isolated by ICA in all patients. Each estimated epileptic component had a consistent time course. Conclusion: ICA appears promising for the separation of unaveraged spikes from the EEG background and their decomposition in independent spatio-temporal components.
KW - EEG
KW - Epileptiform discharge
KW - Independent component analysis
KW - Principal component analysis
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U2 - 10.1016/S1388-2457(99)00134-0
DO - 10.1016/S1388-2457(99)00134-0
M3 - Article
C2 - 10574290
AN - SCOPUS:0032887366
VL - 110
SP - 1755
EP - 1763
JO - Electroencephalography and Clinical Neurophysiology - Electromyography and Motor Control
JF - Electroencephalography and Clinical Neurophysiology - Electromyography and Motor Control
SN - 1388-2457
IS - 10
ER -