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

JUAN M. DIAZ; DIEGO M. MATEOS; BOYALLIAN CARINA; P.W.LAMBERTI

Santiago de Chile

Workshop; Neurobiology of Consciousness and the Altered States of Consciousness; 2017

Different techniques originated in Information Theory and tools used innonlinear systems have been applied to electroneurophysiological analysis in time series. Clinically relevant results have emerged from the use of concepts such as Entropy, Chaos and Complexity in the analysis ofelectroencephalography (EEG) and magnetoencephalography (MEG). In this paper we develop a model based on the Permutation Entropy (HPE) and Lempel Ziv Complexity (LZC) method. The results were expressed in a LZC- HPE plane for two clinical neurophysiological and clinical psychiatric patients.The first case is an adult who is 22 years old with an Idiopathic Generalized Epilepsy diagnosis, with a retrospective follow-up of 2 years of evolution. The second case corresponds to an adult patient, 54 years old, with a Generalized Anxiety Disorder (GAD) together with a mild cognitive impairment and severe traumatic brain injury (TBI) in adolescence as personal antecedent. Our results show that the above mentioned processing tools are useful for evolutionary retrospective clinical monitoring of pharmacological interventions in the patient with epilepsy and also for following the clinical response to the proposed treatment. On the other hand, the same tool is usedfor the patient of the second case with GAD and TBI antecedent, in order to assess the starting condition of the first consultation and the impact of the therapeutic interventions in the evolution of the electroneurophysiological activity using prospective monitoring .