Investigation of the dynamics underlying periodic complexes in the EEG

Periodic complexes (PC), occurring lateralised or diffuse, are relatively r are EEG phenomena which reflect acute severe brain disease. The pathophysio logy is still incompletely understood. One hypothesis suggested by the alph a rhythm model of Lopes da Silva is that periodic complexes reflect limit c ycle dynamics of cortical networks caused by excessive excitatory feedback. We examined this hypothesis by applying a recently developed technique to EEGs displaying periodic complexes and to periodic complexes generated by t he model. The technique, non-linear cross prediction, characterises how wel l a time series can be predicted: and how much amplitude and time asymmetry is present. Amplitude and time asymmetry are indications of non-linearity. In accordance with the model, most EEG channels with PC showed clear evide nce of amplitude and time asymmetry, pointing to non-linear dynamics. Howev er, the non-linear predictability of true PC was substantially lower than t hat of PC generated by the model. Furthermore, no finite value for the corr elation dimension could be obtained for the real EEG data, whereas the mode l time series had a dimension slighter higher than one, consistent with a l imit cycle attractor. Thus we can conclude that PC reflect nonlinear dynami cs, but a limit cycle attractor is too simple an explanation. The possibili ty of more complex (high dimensional and spatio-temporal) non-linear dynami cs should be investigated.