Munot Saachi, Kim Naryeong, Huang Yuhao, Keller Corey J
Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, CA, USA.
Wu Tsai Neuroscience Institute, Stanford University, Stanford, CA, USA.
bioRxiv. 2023 Nov 17:2023.11.15.567302. doi: 10.1101/2023.11.15.567302.
Patterned brain stimulation is commonly employed as a tool for eliciting plasticity in brain circuits and treating neuropsychiatric disorders. Although widely used in clinical settings, there remains a limited understanding of how stimulation-induced plasticity influences neural oscillations and their interplay with the underlying baseline functional architecture. To address this question, we applied 15 minutes of 10Hz focal electrical simulation, a pattern identical to 'excitatory' repetitive transcranial magnetic stimulation (rTMS), to 14 medically-intractable epilepsy patients undergoing intracranial electroencephalographic (iEEG). We quantified the spectral features of the cortico-cortical evoked potential (CCEPs) in these patients before and after stimulation. We hypothesized that for a given region the temporal and spectral components of the CCEP predicted the location and degree of stimulation-induced plasticity. Across patients, low frequency power (alpha and beta) showed the broadest change, while the magnitude of change was stronger in high frequencies (beta and gamma). Next we demonstrated that regions with stronger baseline evoked spectral responses were more likely to undergo plasticity after stimulation. These findings were specific to a given frequency in a specific temporal window. Post-stimulation power changes were driven by the interaction between direction of change in baseline power and temporal window of change. Finally, regions exhibiting early increases and late decreases in evoked baseline power exhibited power changes after stimulation and were independent of stimulation location. Together, these findings that time-frequency baseline features predict post-stimulation plasticity effects demonstrate properties akin to Hebbian learning in humans and extend this theory to the temporal and spectral window of interest. These findings can help improve our understanding of human brain plasticity and lead to more effective brain stimulation techniques.
模式化脑刺激通常被用作一种工具，以诱发脑回路的可塑性并治疗神经精神疾病。尽管在临床环境中广泛使用，但对于刺激诱导的可塑性如何影响神经振荡及其与潜在基线功能结构的相互作用，人们的了解仍然有限。为了解决这个问题，我们对14名接受颅内脑电图（iEEG）监测的药物难治性癫痫患者施加了15分钟的10Hz局灶性电刺激，这一模式与“兴奋性”重复经颅磁刺激（rTMS）相同。我们量化了这些患者在刺激前后皮质-皮质诱发电位（CCEPs）的频谱特征。我们假设，对于给定区域，CCEPs的时间和频谱成分可预测刺激诱导的可塑性的位置和程度。在所有患者中，低频功率（α和β）变化最为广泛，而高频（β和γ）的变化幅度更大。接下来我们证明，具有较强基线诱发频谱反应的区域在刺激后更有可能发生可塑性变化。这些发现特定于特定时间窗口内的给定频率。刺激后的功率变化是由基线功率变化方向与变化时间窗口之间的相互作用驱动的。最后，在诱发基线功率上表现出早期增加和晚期降低的区域在刺激后出现了功率变化，且与刺激位置无关。总之，这些时频基线特征预测刺激后可塑性效应的发现证明了人类中类似于赫布学习的特性，并将这一理论扩展到了感兴趣的时间和频谱窗口。这些发现有助于增进我们对人类脑可塑性的理解，并带来更有效的脑刺激技术。
