Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany; Department of Informatics, Bioengineering, Robotics and System Engineering, University of Genoa, Genoa, Italy.
Department of Neurology, University Hospital and Julius Maximilian University, Würzburg, Germany.
Brain Stimul. 2020 Nov-Dec;13(6):1743-1752. doi: 10.1016/j.brs.2020.09.006. Epub 2020 Sep 19.
Abnormal beta band activity in the subthalamic nucleus (STN) is known to be exaggerated in patients with Parkinson's disease, and the amplitude of such activity has been associated with akinetic rigid symptoms. New devices for deep brain stimulation (DBS) that operate by adapting the stimulation parameters generally rely on the detection of beta activity amplitude modulations in these patients. Movement-related frequency modulation of beta oscillatory activity has been poorly investigated, despite being an attractive variable for extracting information about basal ganglia activity.
We studied the STN oscillatory activity associated with locomotion and proposed a new approach to extract movement related information from beta band activity.
We recorded bilateral local field potential of the STN in eight parkinsonian patients implanted with DBS electrodes during upright quiet standing and unperturbed walking. Neurophysiological recordings were combined with kinematic measurements and individual molecular brain imaging studies. We then determined the information carried by the STN oscillatory activity about locomotion and we identified task-specific biomarkers.
We found a gait-related peak frequency modulation of the beta band of STN recordings of parkinsonian patients. This novel biomarker and the associated power modulations were highly informative to detect the walking state (with respect to standing) in each single patient.
Frequency modulation in the human STN represents a fundamental aspect of information processing of locomotion. Our information-driven approach could significantly enrich the spectrum of Parkinson's neural markers, with input signals encoding ongoing tasks execution for an appropriate online tuning of DBS delivery.
已知帕金森病患者的丘脑底核（STN）中的异常β频带活动被夸大，并且这种活动的幅度与运动不能僵硬的症状有关。用于深部脑刺激（DBS）的新设备通常通过适应这些患者的刺激参数来操作，这些设备一般依赖于检测β活动幅度调制。尽管β振荡活动的运动相关频率调制是提取基底神经节活动信息的一种有吸引力的变量，但对其的研究仍很少。
我们研究了与运动有关的 STN 振荡活动，并提出了一种从β频带活动中提取运动相关信息的新方法。
我们在 8 名植入 DBS 电极的帕金森病患者进行直立静息和不受干扰的行走时，记录双侧 STN 的局部场电位。神经生理记录与运动学测量和个体分子脑成像研究相结合。然后，我们确定了 STN 振荡活动对运动的携带信息，并确定了特定于任务的生物标志物。
我们发现帕金森病患者的 STN 记录的β频带存在与步态相关的峰值频率调制。这种新的生物标志物和相关的功率调制在每个患者中都非常有助于检测行走状态（相对于站立状态）。
人类 STN 中的频率调制代表了运动信息处理的一个基本方面。我们的信息驱动方法可以极大地丰富帕金森氏神经标志物的范围，通过输入信号编码正在执行的任务，为 DBS 传递的适当在线调谐提供输入。
