INVESTIGADORES
MATO German
artículos
Título:
Mechanisms for pattern specificity of deep-brain stimulation in Parkinson’s disease
Autor/es:
VELARDE, OSVALDO MATÍAS; MATO, GERMÁN; DELLAVALE, DAMIÁN
Revista:
PLOS ONE
Editorial:
PUBLIC LIBRARY SCIENCE
Referencias:
Año: 2017 vol. 12
ISSN:
1932-6203
Resumen:
Deep brain stimulation (DBS) has become a widely used technique for treating advanced stages of neurological and psychiatric illness. In the case of motor disorders related to basal ganglia (BG) dysfunction, several mechanisms of action for the DBS therapy have been identified which might be involved simultaneously or in sequence. However, the identifica-tion of a common key mechanism underlying the clinical relevant DBS configurations has remained elusive due to the inherent complexity related to the interaction between the electrical stimulation and the neural tissue, and the intricate circuital structure of the BG- thalamocortical network. In this work, it is shown that the clinically relevant range for both, the frequency and intensity of the electrical stimulation pattern, is an emergent property of the BG anatomy at the system-level that can be addressed using mean-field descriptivemodels of the BG network. Moreover, it is shown that the activity resetting mechanism elicited by electrical stimulation provides a natural explanation to the ineffectiveness of irregular (i.e., aperiodic) stimulation patterns, which has been commonly observed in previouslyreported pathophysiology models of Parkinson?s disease. Using analytical and numerical techniques, these results have been reproduced in both cases: 1) a reduced mean-field model that can be thought as an elementary building block capable to capture the underlyingfundamentals of the relevant loops constituting the BG-thalamocortical network, and 2) a detailed model constituted by the direct and hyperdirect loops including one-dimensional spatial structure of the BG nuclei. We found that the optimal ranges for the essential param-eters of the stimulation patterns can be understood without taking into account biophysical details of the relevant structures.