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.

中文翻译：

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观点：使用双向深脑计算机接口对帕金森病进行闭环深脑刺激的控制变量和策略的演变

能够闭环神经调节的深部脑刺激系统是一种双向深部脑机接口（dBCI），其中神经信号被记录、解码，然后用作大脑中同一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在刺激期间跟踪的稳定、稳健和可靠的神经输入，并优化神经刺激模式和参数（控制策略）以用于运动行为大脑接口，这是为个人定制的。从这个角度来看，我们将概述我们实验室所做的关于发现与 PD 相关的神经和行为控制变量的演变的工作，