Modeling Brain Wave Data By Using Artificial Neural Networks

Abstract

Artificial neural networks can successfully model time series in real life. Because of their success, they have been widely used in various fields of application. In this paper, artificial neural networks are used to model brain wave data which has been recorded during the Wisconsin Card Sorting Test. The forecasting performances of different artificial neural network models, such as feed forward and recurrent neural networks, using both linear and nonlinear activation functions in the output neuron, are examined. As a result of the analysis, it is found that artificial neural networks model the data successfully and all the models employed produce very accurate forecasts.