Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tuebingen, Tuebingen, Germany.
Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tuebingen, Tuebingen, Germany.
Neuroimage. 2023 Apr 1;269:119891. doi: 10.1016/j.neuroimage.2023.119891. Epub 2023 Jan 25.
The ratio between the input and output of neuronal populations, usually referred to as gain modulation, is rhythmically modulated along the oscillatory cycle. Previous research on spinal neurons, however, revealed contradictory findings: both uni- and bimodal patterns of increased responsiveness for synaptic input have been proposed for the oscillatory beta rhythm. In this study, we compared previous approaches of phase estimation directly on simulated data and empirically tested the corresponding predictions in healthy males and females. We applied single-pulse transcranial magnetic stimulation over the primary motor cortex at rest, and assessed the spinal output generated by this input. Specifically, the peak-to-peak amplitude of the motor evoked potential in the contralateral forearm was estimated as a function of the EMG phase at which the stimulus was applied. The findings indicated that human spinal neurons adhere to a unimodal pattern of increased responsiveness, and suggest that the rising phase of the upper beta band maximizes gain modulation. Importantly, a bimodal pattern of increased responsiveness was shown to result in an artifact during data analysis and filtering. This observation of invalid preprocessing could be generalized to other frequency bands (i.e., delta, theta, alpha, and gamma), different task conditions (i.e., voluntary muscle contraction), and EEG-based phase estimations. Appropriate analysis algorithms, such as broad-band filtering, enable us to accurately determine gain modulation of neuronal populations and to avoid erroneous phase estimations. This may facilitate novel phase-specific interventions for targeted neuromodulation.
神经元群体的输入和输出之间的比率，通常称为增益调制，沿着振荡周期呈节律性调制。然而，先前对脊髓神经元的研究得出了相互矛盾的发现：对于振荡β节律，已经提出了突触输入的响应增加的单峰和双峰模式。在这项研究中，我们直接在模拟数据上比较了先前的相位估计方法，并在健康男性和女性中对相应的预测进行了实证检验。我们在休息时将单次经颅磁刺激应用于初级运动皮层，并评估了该输入产生的脊髓输出。具体来说，将对侧前臂的运动诱发电位的峰峰值幅度作为施加刺激时肌电图相位的函数进行估计。研究结果表明，人类脊髓神经元遵循响应增加的单峰模式，并表明上β带的上升相位使增益调制最大化。重要的是，已经表明响应增加的双峰模式会在数据分析和滤波过程中产生伪影。这种无效预处理的观察结果可以推广到其他频带（即，δ、θ、α和γ）、不同的任务条件（即，自愿肌肉收缩）和基于 EEG 的相位估计。适当的分析算法，如宽带滤波，可以帮助我们准确确定神经元群体的增益调制，并避免错误的相位估计。这可能有助于针对特定神经元的新型相位特异性干预。
