Closed-Loop Modulation of the Pathological Disorders of the Basal Ganglia Network

IEEE Transactions on Neural Networks and Learning Systems
Chen LiuKenneth A Loparo

Abstract

A generalized predictive closed-loop control strategy to improve the basal ganglia activity patterns in Parkinson's disease (PD) is explored in this paper. Based on system identification, an input-output model is established to reveal the relationship between external stimulation and neuronal responses. The model contributes to the implementation of the generalized predictive control (GPC) algorithm that generates the optimal stimulation waveform to modulate the activities of neuronal nuclei. By analyzing the roles of two critical control parameters within the GPC law, optimal closed-loop control that has the capability of restoring the normal relay reliability of the thalamus with the least stimulation energy expenditure can be achieved. In comparison with open-loop deep brain stimulation and traditional static control schemes, the generalized predictive closed-loop control strategy can optimize the stimulation waveform without requiring any particular knowledge of the physiological properties of the system. This type of closed-loop control strategy generates an adaptive stimulation waveform with low energy expenditure with the potential to improve the treatments for PD.

Citations

Mar 21, 2018·Wiley Interdisciplinary Reviews. Systems Biology and Medicine·Sabato SantanielloSridevi V Sarma
Apr 26, 2018·Neurodegenerative Disease Management·Ameer MohammedAndreas Demosthenous
May 6, 2017·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Yulin ZhuChen Liu
Jun 12, 2018·International Journal of Neural Systems·Michael Caiola, Mark H Holmes
Apr 7, 2021·Journal of Neural Engineering·Benoit DuchetRafal Bogacz
Aug 18, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Mahboubeh AhmadipourSaeid R Seydnejad

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