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Optimized temporal pattern of brain stimulation designed by computational evolution.

Authors :
Brocker DT
Swan BD
So RQ
Turner DA
Gross RE
Grill WM
Source :
Science translational medicine [Sci Transl Med] 2017 Jan 04; Vol. 9 (371).
Publication Year :
2017

Abstract

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson's disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We varied the temporal pattern of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson's disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in a parkinsonian rat model and in patients. Both optimized and standard high-frequency stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution of temporal patterns to increase the efficiency of brain stimulation in treating Parkinson's disease and thereby reduce the energy required for successful treatment below that of current brain stimulation paradigms.<br /> (Copyright © 2017, American Association for the Advancement of Science.)

Details

Language :
English
ISSN :
1946-6242
Volume :
9
Issue :
371
Database :
MEDLINE
Journal :
Science translational medicine
Publication Type :
Academic Journal
Accession number :
28053151
Full Text :
https://doi.org/10.1126/scitranslmed.aah3532