脑深部刺激
丘脑底核
局部场电位
脑磁图
神经科学
刺激
BETA(编程语言)
电生理学
联轴节(管道)
疾病
功能连接
医学
心理学
神经生理学
β节律
中枢神经系统疾病
大脑定位
神经网络
队列
神经影像学
帕金森病
磁共振成像
退行性疾病
运动前神经元活动
生物神经网络
功能磁共振成像
网络动力学
铅(地质)
运动症状
方差分析
神经调节
脑电图
心脏病学
作者
Bahne H. Bahners,Lukas L. Goede,Patricia Zvarova,Garance M. Meyer,Konstantin Butenko,Roxanne Lofredi,Nanditha Rajamani,Frédéric Schaper,Clemens Neudorfer,Barbara Hollunder,Julianna Pijar,Savir Madan,Lauren A. Hart,Matthias Sure,Alexandra Steina,Fayed Rassoulou,Christian J Hartmann,Markus Butz,J. Hirschmann,Jan Vesper
出处
期刊:Brain
[Oxford University Press]
日期:2025-11-25
卷期号:149 (7): 2395-2408
标识
DOI:10.1093/brain/awaf445
摘要
Deep brain stimulation (DBS) of the subthalamic nucleus improves motor symptoms in patients with Parkinson's disease. Using functional MRI, optimal DBS response networks have been characterized. However, neural activity associated with Parkinsonian symptoms is magnitudes faster than what can be resolved by this method. Although both spatial and temporal domains of these networks appear crucial, no single study has yet investigated both domains simultaneously. Here, we aimed at closing this gap by analysing electrophysiological data from a total of n = 127 hemispheres. Using subthalamic local field potentials that were recorded concurrently alongside whole-brain magnetoencephalography in a multi-centre cohort of patients who underwent subthalamic DBS for the treatment of Parkinson's disease (n = 100 hemispheres), we analysed the DBS response network in both spatial and temporal domains. In every cortical vertex, cortico-subthalamic coupling was correlated with stimulation outcomes. This network spatially resembled functional MRI-based findings (R = 0.40, P = 0.039) and explained significant amounts of variance in clinical outcomes (βstd = 0.30, P = 0.002), whereas theta-alpha and low beta coupling did not show significant associations with DBS response (theta-alpha: βstd = -0.02, P = 0.805; low beta: βstd = -0.08, P = 0.426). The 'optimal' high beta coupling map was robust when subjected to various cross-validation designs (10-fold cross-validation: R = 0.29, P = 0.009; split-half design: R = 0.31, P = 0.026) and was able to predict outcomes across DBS centres [R = 0.74; P(1) = 8.9 × 10-5]. We identified a DBS response network that resembles the previously defined MRI network and operates in the high beta band. Maximal connectivity to this network was associated with optimal DBS outcomes and was able to cross-predict clinical improvements across DBS surgeons and centres.
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