论文标题
大型大脑连通性与区域刺激的影响之间的关系取决于集体动力学状态
Relations between large scale brain connectivity and effects of regional stimulation depend on collective dynamical state
论文作者
论文摘要
在宏观上,大脑充当互连神经元种群的网络,该网络显示出支持内外通信的节奏动力学。了解特定大脑区域的刺激如何影响这种一致的活动对于获得对大脑功能的基本见解和发展为治疗工具的基本见解很重要。但是,很难预测局灶性刺激的下游效应。具体而言,对于网络活动的集体振荡制度如何影响合作动力学的区域扰动结果,知之甚少。在这里,我们结合了连接组数据和生物物理建模,以开始填补这些空白。通过调整控制网络集体动力学的参数,我们确定了模拟大脑活动的不同状态,并研究了刺激的分布效应如何在不同状态中表现出来。当基线振荡较弱时,刺激的区域表现出增强的功率和频率,并且由于网络相互作用,附近地区会在激发频带中发展相位锁定活性。重要的是,我们发现局灶性刺激还会引起更多分布的修改,以使区域基线振荡频率在网络连贯性上,并且通过功能而不是结构连接性更好地预测了这些效果。相反,当网络以更强的内源性振荡状态运行时,刺激只会导致功率和频率的轻微移动,并且在刺激区域的选择中,网络平均相干性变化更加同质。总而言之,这项工作基于并扩展了以前的计算研究,研究了刺激的影响,并强调刺激位点,以及至关重要的是,脑网络动力学的制度都可以影响网络对局部扰动的广泛响应。
At the macroscale, the brain operates as a network of interconnected neuronal populations, which display rhythmic dynamics that support interareal communication. Understanding how stimulation of a particular brain area impacts such concerted activity is important for gaining basic insights into brain function and for developing neuromodulation as a therapeutic tool. However, it remains difficult to predict the downstream effects of focal stimulation. Specifically, little is known about how the collective oscillatory regime of network activity may affect the outcomes of regional perturbations on cooperative dynamics. Here, we combine connectome data and biophysical modeling to begin filling these gaps. By tuning parameters that control the collective dynamics of the network, we identify distinct states of simulated brain activity, and investigate how the distributed effects of stimulation manifest in different states. When baseline oscillations are weak, the stimulated area exhibits enhanced power and frequency, and due to network interactions, nearby regions develop phase locked activity in the excited frequency band. Importantly, we find that focal stimulation also causes more distributed modifications to network coherence at regions' baseline oscillation frequencies, and that these effects are better predicted by functional rather than structural connectivity. In contrast, when the network operates in a regime of stronger endogenous oscillations, stimulation causes only slight shifts in power and frequency, and network averaged changes in coherence are more homogenous across the choice of the stimulated area. In sum, this work builds upon and extends previous computational studies investigating the impacts of stimulation, and highlights that both the stimulation site, and, crucially, the regime of brain network dynamics, can influence the network wide responses to local perturbations.