Time-delay neural networks and independent component analysis for EEG-based prediction of epileptic seizures propagation

Authors:
Piotr W. Mirowski;Deepak Madhavan;Yann LeCun
Affiliations:
Courant Institute of Mathematical Sciences, New York University, New York, NY;Courant Institute of Mathematical Sciences, New York University, New York, NY;Courant Institute of Mathematical Sciences, New York University, New York, NY
Venue:
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Year:
2007

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Abstract

This research focuses on the development of a machine learning technique based on Time-Delay Neural Networks (TDNN) and Independent Component Analysis (ICA), to analyze EEG signal dynamics related to the initiation and propagation of epileptic seizures. We aim at designing a generative model to simulate EEG time-series after alteration of specific localized channels (electrodes) in order to explore the effects of brain surgery ex-vivo.