Analysis of the sleep EEG using a multilayer network with spatial organisation

Since its discovery some 50 years ago, the electroencephalogram (EEG) has formed the basis for the classification of sleep into several stages. Such classification has been laboriously performed by visual examination of the EEG and related signals, or, more recently, by automated techniques. Both visual scoring and most automated analyses rely on the application of a predefined set of rules. The authors have proposed a method of sleep analysis using a Kohonen self-organising feature map, that requires no such application of rules and aims to give some indication of the dynamics of sleep in humans