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Bayesian adaptive dual control of deep brain stimulation in a computational model of Parkinson’s disease
In this paper, we present a novel Bayesian adaptive dual controller (ADC) for autonomously programming deep brain stimulation devices. We evaluated the Bayesian ADC’s performance in the context of reducing beta power in a computational model of Parkinson’s disease, in which it was tasked with findin...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298687/ https://www.ncbi.nlm.nih.gov/pubmed/30521519 http://dx.doi.org/10.1371/journal.pcbi.1006606 |