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CLoSES: A platform for closed-loop intracranial stimulation in humans
NeuroImage ( IF 4.7 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.neuroimage.2020.117314
Rina Zelmann 1 , Angelique C Paulk 1 , Ishita Basu 2 , Anish Sarma 3 , Ali Yousefi 4 , Britni Crocker 5 , Emad Eskandar 6 , Ziv Williams 7 , G Rees Cosgrove 8 , Daniel S Weisholtz 9 , Darin D Dougherty 10 , Wilson Truccolo 3 , Alik S Widge 11 , Sydney S Cash 1
Affiliation  

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 hasbeen 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,inte-grate seamlessly with existing setups, and ensure safety features are in place. In other words, a robust, yetflexible 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.

中文翻译:


CLoSES:人类闭环颅内刺激平台



通过侵入性脑刺激对大脑网络进行有针对性的询问已成为越来越重要的研究工具和治疗方式。与这种新兴功能相关的大部分工作都集中在开环方法上。然而,闭环技术可以通过使用神经信息的个性化目标优化刺激方法来改善神经调节疗法和研究调查。实施闭环系统具有挑战性,特别是在应用考虑个体间差异的一致策略方面。特别是,在颅内癫痫监测期间,目前大部分研究正在进行中,电极的植入完全是出于临床原因。因此,检测和刺激部位必须针对参与者和任务。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,需要一个强大且灵活的平台来对单个参与者执行不同的测试并符合临床要求。为了研究用于研究和治疗用途的闭环刺激,我们开发了一种电刺激闭环系统 (CLoSES),该系统可计算神经特征,然后将其用于决策算法以近乎实时地触发刺激。总结一下 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,在特定持续时间内高于预设阈值),则会触发刺激。 系统不仅可以在检测实时神经特征时触发刺激,而且我们还整合了一个管道,其中我们使用编码器/解码器模型来根据神经特征估计隐藏的认知状态。 CLoSES 提供了一个灵活的平台来在人类身上实施各种闭环实验范例。 CLoSES 已成功应用于 12 名在癫痫监测装置中植入深度电极的患者。在认知任务期间(N = 5),闭环刺激在逐次尝试的基础上修改了认知隐藏状态。近乎实时地检测到睡眠纺锤波振荡 (N = 6) 和急剧的短暂性癫痫活动 (N = 9),并在事件期间或在指定的延迟时间 (N = 3) 施加刺激。此外,我们还测量了 CLoSES 系统的功能。总延迟与检测到的事件的特征有关,癫痫活动为数十毫秒,纺锤体检测为数百毫秒。逐步延迟,即每个连续步骤的实际持续时间,在指定的固定步骤持续时间内,并随着通道和特征的数量线性增加。我们预计,通过 CLoSES 探索神经动力学以及大脑状态和刺激反应之间的相互作用,将带来对正常和病理性大脑活动机制的新见解,发现和评估神经和精神疾病的潜在电图生物标志物,以及开发和测试在植入治疗设备之前,确定患者特定的刺激目标和控制信号。
更新日期:2020-12-01
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