Wei Kunzhou, Ping Hang, Tang Xiaochen, Li Dianyou, Zhan Shikun, Sun Bomin, Kong Xiangyan, Cao Chunyan
School of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China; The Institute for Future Wireless Research (iFWR), Ningbo University, Ningbo 315211, China.
Shanghai Mental Health Center, Shanghai, China.
Neuroimage. 2025 Jan;305:120992. doi: 10.1016/j.neuroimage.2024.120992. Epub 2024 Dec 30.
Parkinson's disease (PD) is a movement disorder caused by dopaminergic neurodegeneration. Both Levodopa (L-dopa) and Subthalamic Deep Brain Stimulation (STN-DBS) effectively alleviate symptoms, yet their cerebral effects remain under-explored. Understanding these effects is essential for optimizing treatment strategies and assessing disease severity. Magnetoencephalogram (MEG) data provide a continuous time series signal that reflects the dynamic changes in brain activity. The hidden Markov model (HMM) can capture and model the temporal features and underlying states of the MEG signal to extract potential brain states and monitor dynamic changes. In this study, we employed HMM to investigate the cortical mechanism underlying the treatment of PD patients using MEG recordings.
21 PD patients treated with medication underwent MEG recording in both L-dopa medoff and medon conditions. Additionally, 11 PD patients receiving STN-DBS treatment underwent MEG recording in both dbsoff and dbson conditions. The MEG data were segmented into four states by Time-delay embedded Hidden Markov Model (TDE-HMM) algorithm. The state parameters including Fractional Occupancy (FO), Interval Times (IT), and Life Time (LT) for each state and power spectrum of β band were analyzed to study the effects of L-dopa and STN-DBS treatment respectively.
L-dopa significantly increased the motor state of HMM and power in the motor area of both high β (21-35 Hz) and low β (13-20 Hz); the motor state of high β in medoff were correlated with the Unified Parkinson's Disease Rating Scale III (UPDRS III). Conversely, DBS significantly diminishes the motor state of HMM and power in motor area of high β oscillations. The score changes of tremor and limb rigidity after DBS treatment were significantly correlated with the changes of motor state of high β.
This study demonstrates that L-dopa and STN-DBS exert differing effects on β oscillations in the motor cortex of PD patients, primarily in high β band. Understanding these distinct neurophysiological impacts can provide valuable insights for refining therapeutic approaches in motor control for PD patients.
帕金森病(PD)是一种由多巴胺能神经元变性引起的运动障碍。左旋多巴(L - 多巴)和丘脑底核深部脑刺激(STN - DBS)都能有效缓解症状,但其对大脑的影响仍有待深入研究。了解这些影响对于优化治疗策略和评估疾病严重程度至关重要。脑磁图(MEG)数据提供了一个连续的时间序列信号,反映了大脑活动的动态变化。隐马尔可夫模型(HMM)可以捕捉和建模MEG信号的时间特征和潜在状态,以提取潜在的脑状态并监测动态变化。在本研究中,我们采用HMM利用MEG记录来研究PD患者治疗背后的皮质机制。
21名接受药物治疗的PD患者在L - 多巴停药和服药状态下均接受了MEG记录。此外,11名接受STN - DBS治疗的PD患者在刺激关闭和刺激开启状态下均接受了MEG记录。通过时延嵌入隐马尔可夫模型(TDE - HMM)算法将MEG数据分为四种状态。分析每种状态的状态参数,包括占有率(FO)、间隔时间(IT)和寿命(LT)以及β频段的功率谱,以分别研究L - 多巴和STN - DBS治疗的效果。
L - 多巴显著增加了HMM的运动状态以及高β(21 - 35Hz)和低β(13 - 20Hz)频段运动区域的功率;停药状态下高β频段的运动状态与统一帕金森病评定量表III(UPDRS III)相关。相反,DBS显著降低了HMM的运动状态以及高β振荡运动区域的功率。DBS治疗后震颤和肢体僵硬的评分变化与高β频段运动状态的变化显著相关。
本研究表明,L - 多巴和STN - DBS对PD患者运动皮层的β振荡有不同影响,主要在高β频段。了解这些不同的神经生理影响可为优化PD患者运动控制的治疗方法提供有价值的见解。