Perspective: Evolution of Control Variables and Policies for Closed-Loop Deep Brain Stimulation for Parkinson's Disease Using Bidirectional Deep-Brain-Computer Interfaces
Perspective: Evolution of Control Variables and Policies for Closed-Loop Deep Brain Stimulation for Parkinson's Disease Using Bidirectional Deep-Brain-Computer Interfaces
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DOI：
10.3389/fnhum.2020.00353
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发表时间：
2020-08-31
影响因子：
2.9
通讯作者：
Hoffman, Shannon L.
中科院分区：
文献类型：
--
作者：
Bronte-Stewart, Helen M.;Petrucci, Matthew N.;Hoffman, Shannon L.
能够进行闭环神经调节的深部脑刺激系统是一种双向深部脑-计算机接口（dBCI），其中神经信号被记录、解码，然后用作大脑中相同部位的神经调节的输入命令。确保在帕金森病（PD）中成功实施双向dBCI的挑战是发现和解码可以在刺激期间跟踪的稳定，稳健和可靠的神经输入，并优化大脑接口处运动行为的神经刺激模式和参数（控制策略），这些都是为个人定制的。从这个角度来看，我们将概述我们实验室所做的工作，关于发现与PD相关的神经和行为控制变量的演变，与个人治疗窗口相关的新型个性化双阈值控制策略的开发，以及这些应用于神经或运动学输入驱动的闭环DBS的研究，使用第一代双向dBCI。
A deep brain stimulation system capable of closed-loop neuromodulation is a type of bidirectional deep brain-computer interface (dBCI), in which neural signals are recorded, decoded, and then used as the input commands for neuromodulation at the same site in the brain. The challenge in assuring successful implementation of bidirectional dBCIs in Parkinson's disease (PD) is to discover and decode stable, robust and reliable neural inputs that can be tracked during stimulation, and to optimize neurostimulation patterns and parameters (control policies) for motor behaviors at the brain interface, which are customized to the individual. In this perspective, we will outline the work done in our lab regarding the evolution of the discovery of neural and behavioral control variables relevant to PD, the development of a novel personalized dual-threshold control policy relevant to the individual's therapeutic window and the application of these to investigations of closed-loop STN DBS driven by neural or kinematic inputs, using the first generation of bidirectional dBCIs.