预印本:非周期神经活动可预测TMS-EEG中的皮层兴奋性
Aperiodic neural activity predicts cortical excitability in TMS-EEG
一项尚未经同行评审的bioRxiv预印本摘要报告,刺激前非周期神经活动的指数(1/f样活动的斜率)与TMS-EEG早期局部诱发电位幅度呈强负相关,斜率越陡,诱发电位幅度越小。
依据预印本摘要,该研究把刺激前非周期脑电成分与TMS诱发早期电位联系起来,为TMS-EEG的脑状态依赖方案提供了一个可实时提取的候选特征,但样本量小且尚未经同行评审。
Background: Fluctuating cortical excitability states are inherent to and critical for brain function. They can be probed non-invasively using transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) by measuring early local TMS-evoked potentials (EL-TEPs). Pre-stimulus periodic neural activity can predict fluctuating excitability states. To what extent aperiodic neural activity represents a marker of cortical excitability has not been explored. Objectives: We investigated the relationship between pre-stimulus aperiodic and periodic neural activity and EL-TEP amplitude in both the primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC). Methods: Single-pulse TMS was delivered to the left M1 or left DLPFC in 29 and 11 healthy adults, respectively, while EEG was recorded simultaneously. Pre-stimulus EEG was parameterized into aperiodic and periodic components to extract the aperiodic exponent (slope of 1/f-like activity), alpha power (8-13 Hz), and beta power (13-30 Hz). EL-TEP peak-to-peak amplitudes were extracted from approximately 20-65 ms after the TMS pulse. Results: Aperiodic exponent showed a strong negative relationship with EL-TEP amplitude in both M1 and DLPFC, with steeper 1/f-like slopes associated with smaller EL-TEP amplitudes. Inconsistent relationships were found between alpha and beta power with EL-TEP amplitude across the two regions. Conclusions: These findings indicate that pre-stimulus aperiodic neural activity influences cortical excitability in both motor and prefrontal areas. Notably, the aperiodic exponent exhibited stronger associations with cortical excitability compared to periodic alpha or beta power. Brain-state-dependent protocols may benefit from real-time extraction of aperiodic exponent as a target feature to improve the precision and efficacy of TMS.
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来源:bioRxiv · Neuroscience · biorxiv.org