Oehrn Carina R, Cernera Stephanie, Hammer Lauren H, Shcherbakova Maria, Yao Jiaang, Hahn Amelia, Wang Sarah, Ostrem Jill L, Little Simon, Starr Philip A
Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.
Department of Neurology, University of California, San Francisco, San Francisco, California, USA.
medRxiv. 2023 Aug 8:2023.08.03.23293450. doi: 10.1101/2023.08.03.23293450.
Deep brain stimulation is a widely used therapy for Parkinson's disease (PD) but currently lacks dynamic responsiveness to changing clinical and neural states. Feedback control has the potential to improve therapeutic effectiveness, but optimal control strategy and additional benefits of "adaptive" neurostimulation are unclear. We implemented adaptive subthalamic nucleus stimulation, controlled by subthalamic or cortical signals, in three PD patients (five hemispheres) during normal daily life. We identified neurophysiological biomarkers of residual motor fluctuations using data-driven analyses of field potentials over a wide frequency range and varying stimulation amplitudes. Narrowband gamma oscillations (65-70 Hz) at either site emerged as the best control signal for sensing during stimulation. A blinded, randomized trial demonstrated improved motor symptoms and quality of life compared to clinically optimized standard stimulation. Our approach highlights the promise of personalized adaptive neurostimulation based on data-driven selection of control signals and may be applied to other neurological disorders.
深部脑刺激是一种广泛应用于帕金森病（PD）的治疗方法，但目前缺乏对不断变化的临床和神经状态的动态响应。反馈控制有可能提高治疗效果，但最佳控制策略和“自适应”神经刺激的额外益处尚不清楚。我们在三名帕金森病患者（五个脑半球）的日常生活中实施了由丘脑底核或皮质信号控制的自适应丘脑底核刺激。我们通过对宽频率范围和不同刺激幅度的场电位进行数据驱动分析，确定了残余运动波动的神经生理生物标志物。在刺激过程中，两个部位的窄带伽马振荡（65-70赫兹）成为最佳的传感控制信号。一项盲法随机试验表明，与临床优化的标准刺激相比，运动症状和生活质量得到了改善。我们的方法突出了基于数据驱动选择控制信号的个性化自适应神经刺激的前景，并且可能应用于其他神经系统疾病。
