Analysis on EEG signals in visually and auditorily guided saccade task by FICAR

Authors:
Arao Funase;Yagi Tohru;Motoaki Mouri;Allan K. Barros;Andrzej Cichocki;Ichi Takumi
Affiliations:
Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan;Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan;Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan;Technological Center, Universidade Federal do Maranhão, Sao Luis, MA, Brazil;Brain Science Institute, RIKEN, Wako, Japan;Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Japan
Venue:
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Year:
2006

Citing 1
Cited 1

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Abstract

Recently an independent component analysis (ICA) becomes powerful tools to processing bio-signals. In our studies, the ICA is applied to processing on saccade-related EEG signals in order to predict saccadic eye movements because an ensemble averaging, which is a conventional processing method of EEG signals, is not suitable for real-time processing. We have already detected saccade-related independent components (ICs) by ICA. However, features of saccade-related EEG signals and saccade-related ICs were not compared. In this paper, saccade-related EEG signals and saccade-related ICs in visually and auditorily guided saccade task are compared in the point of the latency between starting time of a saccade and time when a saccade-related EEG signal or an IC has maximum value and in the point of the peak scale where a saccade-related EEG signal or an IC has maximum value.