Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.
Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; Center for Mind/Brain Sciences - CIMeC, University of Trento, Italy.
Brain Stimul. 2022 Jan-Feb;15(1):167-178. doi: 10.1016/j.brs.2021.12.002. Epub 2021 Dec 8.
Brain responses to external stimuli vary with fluctuating states of neuronal activity. Previous work has demonstrated effects of phase and power of the ongoing local sensorimotor μ-alpha-oscillation on responses to transcranial magnetic stimulation (TMS) of motor cortex (M1). However, M1 is part of a distributed network, and the effects of oscillatory activity in this network on TMS-evoked EEG responses (TEPs) have not been explored.
To determine the effects of oscillatory activity in the bihemispheric sensorimotor network on TEPs.
31 healthy subjects received single-pulse TMS of the left M1 hand area during EEG recording. Ongoing bihemispheric sensorimotor cortex oscillatory states were reconstructed from the EEG directly preceding TMS, and inferred by a data-driven method combining a multivariate autoregressive model and a Hidden Markov model. TEP amplitudes (P25, N45, P70, N100 and P180) were then compared between different bihemispheric sensorimotor cortex oscillatory states.
Four bihemispheric sensorimotor cortex oscillatory states were identified, with different interhemispheric expressions of theta and alpha oscillations. High alpha-power states in the stimulated sensorimotor cortex increased P25 amplitude. Alpha power in the alpha-alpha state (stimulated - non-stimulated hemisphere) correlated in both hemispheres with N45 amplitude. Theta power in the alpha-theta state correlated in the non-stimulated hemisphere with P70 amplitude.
Bihemispheric sensorimotor cortex oscillatory states contribute to TEPs, with a relevance shift from stimulated to non-stimulated M1 from P25 over N45 to P70. This significantly extends previous findings: not only ongoing local oscillations but distributed network oscillatory states determine cortical responsiveness to external stimuli.
大脑对外界刺激的反应随神经元活动的波动状态而变化。先前的研究表明,运动皮层(M1)经颅磁刺激(TMS)的反应受感觉运动μ-α 振荡的相位和功率的影响。然而,M1 是分布式网络的一部分,该网络中的振荡活动对 TMS 诱发的脑电图反应(TEP)的影响尚未被探索。
确定双侧感觉运动网络中的振荡活动对 TEP 的影响。
31 名健康受试者在脑电图记录期间接受左 M1 手部区域的单次脉冲 TMS。在 TMS 之前直接从 EEG 重建双侧感觉运动皮质的振荡状态,并通过结合多元自回归模型和隐马尔可夫模型的数据驱动方法进行推断。然后比较不同双侧感觉运动皮质振荡状态之间的 TEP 振幅(P25、N45、P70、N100 和 P180)。
确定了四种双侧感觉运动皮质的振荡状态,其θ和α振荡的半球间表达不同。刺激感觉运动皮质的高α功率状态增加了 P25 振幅。α-α状态(刺激-非刺激半球)中的α功率在两个半球中均与 N45 振幅相关。α-θ状态中的θ功率在非刺激半球中与 P70 振幅相关。
双侧感觉运动皮质的振荡状态对 TEP 有贡献,从 P25 到 N45 再到 P70,从刺激的 M1 到非刺激的 M1 的相关性发生了转变。这一发现显著扩展了先前的研究结果:不仅是局部的持续振荡,而且分布式网络的振荡状态决定了皮质对外部刺激的反应性。