Neurophysiological Evolution with Complexity-Entropy Plane in Patient with Psychiatric Disorders

DIAZ JUAN; DIEGO M. MATEOS; BOYALLIAN CARINA; LAMBERTI PEDRO WALTER

Cordoba

Encuentro; IX Encuentro de J ovenes Investigadores en Neurociencias de C ordoba.; 2017

Different techniques originated in Information Theory and tools used innonlinear systems have been applied to the analysis ofelectroneurophysiological time series. Clinically relevant results have emerged from the use of concepts such as Entropy, Chaos and Complexity in the analysis of electroencephalograms (EEG) and magnetoencephalograms (MEG). In this work we developed a model based on the Permutation Entropy (HPE) and the Lempel Ziv Complexity (LZC). The results were expressed in a LZC-HPE plane for two clinical neurophysiological and clinical psychiatric patients. The first case is a 22 years old adult who is with an Idiopathic Generalized Epilepsy diagnosis, with a retrospective follow-up of 2 years of evolution. The second case corresponds to a 41 years old patient, with Narcolepsy and morbid obesity as a health condition. Our results show that the proposed processing tools are useful for doing an evolutionary retrospectiveclinical effects of pharmacological interventions in both patients, and from these, to follow the clinical response to the proposed treatment.