TOPICAL REVIEW A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces <s> Neural Networks <s> Electroencephalography (EEG) pattern-recognition studies were carried out using EEG topography (readiness potential, or RP, spatiotemporal patterns) generated the moment before voluntary movements of muscles. RPs generated prior to pronouncing syllables and controlling a joystick were studied by experiments and simulation. The spatiotemporal patterns of RPs were measured by multichannel surface electrodes pasted on the subject's scalp. Backpropagation neural networks were used for RP pattern recognition. The results show that RPs generated prior to syllable pronouncement contain some information about those syllables, and that RPs generated prior to joy stick movements contain information on the direction of intended movement. They also show that neural networks can be used to recognize EEG information and so create a new type of man-machine interface for data input. > <s> BIB001 </s> TOPICAL REVIEW A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces <s> Neural Networks <s> Neural networks are trained to classify half-second segments of six-channel, EEG data into one of five classes corresponding to five cognitive tasks performed by four subjects. Two and three-layer feedforward neural networks are trained using 10-fold cross-validation and early stopping to control over-fitting. EEG signals were represented as autoregressive (AR) models. The average percentage of test segments correctly classified ranged from 71% for one subject to 38% for another subject. Cluster analysis of the resulting neural networks’ hidden-unit weight vectors identifies which EEG channels are most relevant to this discrimination problem. <s> BIB002
Neural Networks (NN) are, together with linear classifiers, the category of classifiers mostly used in BCI research (see, e.g., BIB001 BIB002 ). Let us recall that a NN is an assembly of several artificial neurons which enables to produce nonlinear decision boundaries  .