Automated detection of low-dimensional EEG ?-episodes. An example of application to psychopharmacological data
This paper addresses the practical problems raised by the fact that correlation integrals computed from electroencephalographic signals do not scale. An automated procedure is described for ?-waves, which is based on the known method of determining the correlation dimension from scaled structures that appear in diagrams of slope-curves. Automation, which is achieved using a moving window that detects the minima of slope-curves, and the density of minima makes it possible to vary the numerous parameters, and to implement tests. The potentialities of the automatic procedure are illustrated by results of psychopharmacological interest, based on the analysis of 22103 ?-signals, and the computation of 32106 correlation integrals. Previous results concerning the existence of low-dimensional ?-episodes, lasting in general not more than 56 s, are confirmed. Opposing effects upon the correlation dimension are described, at their pharmacological peak, for a dopaminergic agonist (apomorphine) and an atypical antipsychotic, a ?-receptor ligand. The results also confirm that time reparametrization is a vital check in searches of low-dimensional attractor-ruled dynamics, and they suggest that subjects exhibiting high-?, i.e. whose ?-waves are of amplitude A>30 ?V, be selected for such investigations.
automated detection apomorphine electroencephalography alpha-waves non-linear dynamics low-dimensional attractor haloperidol