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实现真正的闭环神经调节:刺激过程中的无伪迹记录。

Toward true closed-loop neuromodulation: artifact-free recording during stimulation.

机构信息

Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, 2108 Allston Way, Suite 200, Berkeley, CA 94704, United States.

Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, 2108 Allston Way, Suite 200, Berkeley, CA 94704, United States.

出版信息

Curr Opin Neurobiol. 2018 Jun;50:119-127. doi: 10.1016/j.conb.2018.01.012. Epub 2018 Feb 20.

Abstract

Closed-loop and responsive neuromodulation systems improve open-loop neurostimulation by responding directly to measured neural activity and providing adaptive, on-demand therapy. To be effective, these systems must be able to simultaneously record and stimulate neural activity, a task made difficult by persistent stimulation artifacts that distort and obscure underlying biomarkers. To enable simultaneous stimulation and recording, several techniques have been proposed. These techniques involve artifact-preventing system configurations, resilient recording front-ends, and back-end signal processing for removing recorded artifacts. Co-designing and integrating these artifact cancellation techniques will be key to enabling neuromodulation systems to stimulate and record at the same time. Here, we review the state-of-the-art for these techniques and their role in achieving artifact-free neuromodulation.

摘要

闭环和响应式神经调节系统通过直接响应测量到的神经活动并提供自适应的按需治疗来改善开环神经刺激。为了有效,这些系统必须能够同时记录和刺激神经活动,但是持续的刺激伪影会干扰和模糊潜在的生物标志物,这使得这项任务变得困难。为了实现同时刺激和记录,已经提出了几种技术。这些技术涉及防止伪影的系统配置、弹性记录前端以及后端信号处理,用于去除记录的伪影。这些去伪影技术的协同设计和集成将是实现神经调节系统同时刺激和记录的关键。在这里,我们回顾了这些技术的最新进展及其在实现无伪影神经调节中的作用。

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