Brain computer interfaces: A recurrent neural network approach

Abstract

This paper explores the use of recurrent neural networks in the field of Brain Computer Interfaces(BCI). In particular it looks at a recurrent neural network, an echostate network and a CasPer neural network and attempts to use them to classify data from BCI competition III's dataset IVa. In addition it proposes a new method, EchoCasPer, which uses the CasPer training scheme in a recurrent neural network. The results showed that temporal information existed within the BCI data to be made use of, but further pre-processing and parameter exploration was needed to reach competitive classification rates. © 2010 Springer-Verlag.