Chaos, Continuous EEG, and Cognitive Mechanisms: A Future for Clinical Neurophysiology

With the advent of the modern theory of nonlinear dynamic systems (chaos theory), new concepts and analytical tools have become available to extract more information from complex signals such as the EEG. This paper gives a brief introduction to the main ideas and basic principles of chaos theory. Additionally, application of nonlinear analysis to EEG is illustrated with examples from two fields: 1) prediction and detection of epileptic seizures; 2) characterization of functional interactions between brain regions in normal and disturbed cognition. While the prediction of seizures with nonlinear EEG analysis is currently the cause of much excitement, there are still many controversies. The more modest goal of detecting seizures in patients in neonatal and adult intensive care wards, however, has been shown to be much closer to practical clinical implementation. Nonlinear analysis of functional interactions between brain regions with the synchronization likelihood shows how optimal information processing may depend upon a delicate balance between coupling and uncoupling. Finally it is suggested how the notion of synchronization between dynamic systems can be used to formulate a general concept ("fragile binding") of normal and abnormal brain function.