Neurophysiological evolution using a Complexity-Entropy Plane in patient with Psychiatric Disorder

JUAN M. DIAZ; DIEGO M. MATEOS; PEDRO W. LAMBERTI; CARINA BOYARIAN

Valparaiso

Simposio; International Symposium Biology of Neuropsychiatric Disorder; 2016

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 of EEG and 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 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 used for the patient of the second case with GAD and TBI antecedent, in order to assess the starting condition of the firstconsultation and the impact of the therapeutic interventions in the evolution of the electroneurophisiological activity using prospective monitoring.