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运动控制网络中瞬时伽马频率的不规则性表征了视觉运动和本体感觉信息的处理。

Irregularity of instantaneous gamma frequency in the motor control network characterize visuomotor and proprioceptive information processing.

机构信息

Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, United States of America.

Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX 75390, United States of America.

出版信息

J Neural Eng. 2024 Mar 12;21(2). doi: 10.1088/1741-2552/ad2e1d.

Abstract

The study aims to characterize movements with different sensory goals, by contrasting the neural activity involved in processing proprioceptive and visuo-motor information. To accomplish this, we have developed a new methodology that utilizes the irregularity of the instantaneous gamma frequency parameter for characterization.In this study, eight essential tremor patients undergoing an awake deep brain stimulation implantation surgery repetitively touched the clinician's finger (forward visually-guided/FV movement) and then one's own chin (backward proprioceptively-guided/BP movement). Neural electrocorticographic recordings from the motor (M1), somatosensory (S1), and posterior parietal cortex (PPC) were obtained and band-pass filtered in the gamma range (30-80 Hz). The irregularity of the inter-event intervals (IEI; inverse of instantaneous gamma frequency) were examined as: (1) auto-information of the IEI time series and (2) correlation between the amplitude and its proceeding IEI. We further explored the network connectivity after segmenting the FV and BP movements by periods of accelerating and decelerating forces, and applying the IEI parameter to transfer entropy methods.Conceptualizing that the irregularity in IEI reflects active new information processing, we found the highest irregularity in M1 during BP movement, highest in PPC during FV movement, and the lowest during rest at all sites. Also, connectivity was the strongest from S1 to M1 and from S1 to PPC during FV movement with accelerating force and weakest during rest.. We introduce a novel methodology that utilize the instantaneous gamma frequency (i.e. IEI) parameter in characterizing goal-oriented movements with different sensory goals, and demonstrate its use to inform the directional connectivity within the motor cortical network. This method successfully characterizes different movement types, while providing interpretations to the sensory-motor integration processes.

摘要

本研究旨在通过对比处理本体感觉和视动信息所涉及的神经活动,来描绘具有不同感觉目标的运动。为了实现这一目标,我们开发了一种新的方法,利用瞬时伽马频率参数的不规则性进行特征描述。

在这项研究中,8 名患有特发性震颤的患者在清醒的深部脑刺激植入手术中反复触摸医生的手指(向前视觉引导/FV 运动)和自己的下巴(向后本体感觉引导/BP 运动)。从运动皮层(M1)、躯体感觉皮层(S1)和后顶叶皮层(PPC)获取神经脑电皮质电图记录,并在伽马频带(30-80 Hz)内进行带通滤波。检查了事件间间隔(IEI;瞬时伽马频率的倒数)的不规则性,作为:(1)IEI 时间序列的自信息,和(2)振幅与其前导 IEI 之间的相关性。我们还通过加速和减速力对 FV 和 BP 运动进行分段,并将 IEI 参数应用于转移熵方法,进一步探索了网络连接。

我们的概念是,IEI 的不规则性反映了主动的新信息处理,我们发现 BP 运动时 M1 的不规则性最高,FV 运动时 PPC 的不规则性最高,所有部位休息时的不规则性最低。此外,在 FV 运动中,力加速时,从 S1 到 M1 和 S1 到 PPC 的连接最强,而在休息时最弱。我们提出了一种新的方法,利用瞬时伽马频率(即 IEI)参数来描述具有不同感觉目标的目标导向运动,并展示了它如何用于告知运动皮质网络内的方向连接。该方法成功地对不同的运动类型进行了特征描述,同时为感觉-运动整合过程提供了解释。

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