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CLoSES:一个用于人类闭环颅内刺激的平台。

CLoSES: A platform for closed-loop intracranial stimulation in humans.

机构信息

Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.

Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.

出版信息

Neuroimage. 2020 Dec;223:117314. doi: 10.1016/j.neuroimage.2020.117314. Epub 2020 Sep 1.

DOI:10.1016/j.neuroimage.2020.117314
PMID:32882382
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7805582/
Abstract

Targeted interrogation of brain networks through invasive brain stimulation has become an increasingly important research tool as well as therapeutic modality. The majority of work with this emerging capability has been focused on open-loop approaches. Closed-loop techniques, however, could improve neuromodulatory therapies and research investigations by optimizing stimulation approaches using neurally informed, personalized targets. Implementing closed-loop systems is challenging particularly with regard to applying consistent strategies considering inter-individual variability. In particular, during intracranial epilepsy monitoring, where much of this research is currently progressing, electrodes are implanted exclusively for clinical reasons. Thus, detection and stimulation sites must be participant- and task-specific. The system must run in parallel with clinical systems, integrate seamlessly with existing setups, and ensure safety features are in place. In other words, a robust, yet flexible platform is required to perform different tests with a single participant and to comply with clinical requirements. In order to investigate closed-loop stimulation for research and therapeutic use, we developed a Closed-Loop System for Electrical Stimulation (CLoSES) that computes neural features which are then used in a decision algorithm to trigger stimulation in near real-time. To summarize CLoSES, intracranial electroencephalography (iEEG) signals are acquired, band-pass filtered, and local and network features are continuously computed. If target features are detected (e.g. above a preset threshold for a certain duration), stimulation is triggered. Not only could the system trigger stimulation while detecting real-time neural features, but we incorporated a pipeline wherein we used an encoder/decoder model to estimate a hidden cognitive state from the neural features. CLoSES provides a flexible platform to implement a variety of closed-loop experimental paradigms in humans. CLoSES has been successfully used with twelve patients implanted with depth electrodes in the epilepsy monitoring unit. During cognitive tasks (N=5), stimulation in closed loop modified a cognitive hidden state on a trial by trial basis. Sleep spindle oscillations (N=6) and sharp transient epileptic activity (N=9) were detected in near real-time, and stimulation was applied during the event or at specified delays (N=3). In addition, we measured the capabilities of the CLoSES system. Total latency was related to the characteristics of the event being detected, with tens of milliseconds for epileptic activity and hundreds of milliseconds for spindle detection. Stepwise latency, the actual duration of each continuous step, was within the specified fixed-step duration and increased linearly with the number of channels and features. We anticipate that probing neural dynamics and interaction between brain states and stimulation responses with CLoSES will lead to novel insights into the mechanism of normal and pathological brain activity, the discovery and evaluation of potential electrographic biomarkers of neurological and psychiatric disorders, and the development and testing of patient-specific stimulation targets and control signals before implanting a therapeutic device.

摘要

通过侵入性脑刺激对大脑网络进行靶向询问已经成为一种越来越重要的研究工具和治疗方式。这项新兴能力的大多数工作都集中在开环方法上。然而,通过使用神经信息的个性化目标来优化刺激方法,闭环技术可以改善神经调节疗法和研究调查。实现闭环系统具有挑战性,特别是在考虑个体间变异性时应用一致的策略。特别是在颅内癫痫监测中,目前这项研究正在进行,植入电极纯粹是出于临床原因。因此,检测和刺激部位必须针对参与者和任务进行特定设计。该系统必须与临床系统并行运行,与现有设置无缝集成,并确保安全功能到位。换句话说,需要一个强大而灵活的平台来对单个参与者执行不同的测试,并满足临床要求。为了研究闭环刺激的研究和治疗用途,我们开发了一种用于电刺激的闭环系统 (CLoSES),该系统计算神经特征,然后使用决策算法在近实时触发刺激。为了总结 CLoSES,采集颅内脑电图 (iEEG) 信号,进行带通滤波,并连续计算局部和网络特征。如果检测到目标特征(例如,在特定持续时间内超过预设阈值),则触发刺激。系统不仅可以在检测实时神经特征时触发刺激,还可以使用一个管道,其中我们使用编码器/解码器模型从神经特征中估计隐藏的认知状态。CLoSES 为在人类中实现各种闭环实验范式提供了一个灵活的平台。CLoSES 已经成功地用于在癫痫监测单元中植入深度电极的十二名患者。在认知任务中(N=5),闭环刺激根据每个试验修改了认知隐藏状态。在近实时检测到睡眠纺锤波振荡(N=6)和尖锐瞬态癫痫活动(N=9),并在事件期间或指定延迟时施加刺激(N=3)。此外,我们测量了 CLoSES 系统的能力。总延迟与被检测事件的特征有关,癫痫活动的延迟为数十毫秒,纺锤波检测的延迟为数百毫秒。逐步延迟,即每个连续步骤的实际持续时间,在指定的固定步长内,并随通道和特征数量呈线性增加。我们预计,使用 CLoSES 探测神经动力学以及大脑状态与刺激反应之间的相互作用,将为正常和病理性大脑活动的机制、发现和评估神经和精神障碍的潜在电生理生物标志物以及开发和测试提供新的见解。在植入治疗设备之前,针对特定患者的刺激目标和控制信号。

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