Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks

19 Nov 2015Pouya BashivanIrina RishMohammed YeasinNoel Codella

One of the challenges in modeling cognitive events from electroencephalogram (EEG) data is finding representations that are invariant to inter- and intra-subject differences, as well as to inherent noise associated with such data. Herein, we propose a novel approach for learning such representations from multi-channel EEG time-series, and demonstrate its advantages in the context of mental load classification task... (read more)

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