Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany.
Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany.
Handb Clin Neurol. 2022;184:273-284. doi: 10.1016/B978-0-12-819410-2.00015-1.
A brain-machine interface represents a promising therapeutic avenue for the treatment of many neurologic conditions. Deep brain stimulation (DBS) is an invasive, neuro-modulatory tool that can improve different neurologic disorders by delivering electric stimulation to selected brain areas. DBS is particularly successful in advanced Parkinson's disease (PD), where it allows sustained improvement of motor symptoms. However, this approach is still poorly standardized, with variable clinical outcomes. To achieve an optimal therapeutic effect, novel adaptive DBS (aDBS) systems are being developed. These devices operate by adapting stimulation parameters in response to an input signal that can represent symptoms, motor activity, or other behavioral features. Emerging evidence suggests greater efficacy with fewer adverse effects during aDBS compared with conventional DBS. We address this topic by discussing the basics principles of aDBS, reviewing current evidence, and tackling the many challenges posed by aDBS for PD.
脑机接口代表了一种有前途的治疗方法，可以治疗许多神经系统疾病。深部脑刺激（DBS）是一种侵入性的神经调节工具，可以通过向选定的大脑区域发送电刺激来改善不同的神经系统疾病。DBS 在晚期帕金森病（PD）中特别成功，它可以持续改善运动症状。然而，这种方法仍然缺乏标准化，临床效果也各不相同。为了达到最佳的治疗效果，正在开发新型自适应 DBS（aDBS）系统。这些设备通过响应输入信号来调整刺激参数，该输入信号可以代表症状、运动活动或其他行为特征。与传统 DBS 相比，aDBS 在治疗过程中具有更高的疗效和更少的不良反应。我们通过讨论 aDBS 的基本原理、回顾现有证据以及解决 aDBS 治疗 PD 面临的诸多挑战来探讨这个话题。
