Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, Sahlgrenska Academy at University of Gothenburg, 413 45, Gothenburg, Sweden.
Department of Clinical Neurophysiology, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden.
Sci Rep. 2023 Jun 12;13(1):9507. doi: 10.1038/s41598-023-36753-6.
Sudden, unexpected stimuli can induce a transient inhibition of sympathetic vasoconstriction to skeletal muscle, indicating a link to defense reactions. This phenomenon is relatively stable within, but differs between, individuals. It correlates with blood pressure reactivity which is associated with cardiovascular risk. Inhibition of muscle sympathetic nerve activity (MSNA) is currently characterized through invasive microneurography in peripheral nerves. We recently reported that brain neural oscillatory power in the beta spectrum (beta rebound) recorded with magnetoencephalography (MEG) correlated closely with stimulus-induced MSNA inhibition. Aiming for a clinically more available surrogate variable reflecting MSNA inhibition, we investigated whether a similar approach with electroencephalography (EEG) can accurately gauge stimulus-induced beta rebound. We found that beta rebound shows similar tendencies to correlate with MSNA inhibition, but these EEG data lack the robustness of previous MEG results, although a correlation in the low beta band (13-20 Hz) to MSNA inhibition was found (p = 0.021). The predictive power is summarized in a receiver-operating-characteristics curve. The optimum threshold yielded sensitivity and false-positive rate of 0.74 and 0.33 respectively. A plausible confounder is myogenic noise. A more complicated experimental and/or analysis approach is required for differentiating MSNA-inhibitors from non-inhibitors based on EEG, as compared to MEG.
突然的、意外的刺激会导致骨骼肌交感神经血管收缩短暂抑制，表明其与防御反应有关。这种现象在个体内部相对稳定，但在个体之间存在差异。它与血压反应性相关，而血压反应性与心血管风险有关。目前，通过外周神经的微创神经生理学可以对肌肉交感神经活动（MSNA）抑制进行特征描述。我们最近报道，通过脑磁图（MEG）记录的β频谱（β反弹）中的脑神经振荡功率与刺激诱导的 MSNA 抑制密切相关。为了寻找一种更适用于临床的反映 MSNA 抑制的替代变量，我们研究了脑电图（EEG）是否可以准确地测量刺激诱导的β反弹。我们发现，β反弹与 MSNA 抑制的相关性也具有相似的趋势，但这些 EEG 数据缺乏之前 MEG 结果的稳健性，尽管在低β波段（13-20 Hz）发现了与 MSNA 抑制的相关性（p=0.021）。预测能力总结在一个接收器操作特性曲线中。最佳阈值的敏感性和假阳性率分别为 0.74 和 0.33。肌源性噪声是一个可能的混杂因素。与 MEG 相比，基于 EEG 区分 MSNA 抑制剂和非抑制剂需要更复杂的实验和/或分析方法。
