通过脉冲刺激对兴奋-抑制网络同步进行相位和幅度依赖的控制
Phase- and amplitude-dependent control of synchronization in excitatory-inhibitory networks via pulsed stimulation
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中文总结 AI 辅助
该研究针对兴奋-抑制EIF神经元网络，建立了基于nPRC、nARC和同步性变化的表征框架，揭示了脉冲相位对同步性的调控作用，为振荡网络的状态依赖控制提供了通用原则。
中文摘要 AI 辅助
振荡神经元网络对外部扰动表现出复杂的集体响应，这种响应既取决于网络的内在动力学，也取决于刺激的时机。尽管相位响应曲线（PRC）已成为表征这些响应的标准工具，但仅相位重置无法完整描述瞬时扰动如何重塑集体活动。本文研究了受相位靶向电流脉冲作用的平衡型兴奋-抑制指数积分放电（EIF）神经元网络的动力学，通过联合分析网络相位响应曲线（nPRC）、网络幅度响应曲线（nARC）以及群体同步性的变化，建立了一个从相位、幅度和同步性角度表征网络集体响应的框架。研究表明，相同的刺激脉冲可根据其在振荡周期内的相位，分别实现增强、抑制或不改变网络同步性，揭示了不同的同步和去同步窗口；nARC进一步识别出可最大化抑制振荡活动的鲁棒相位区间，为重复刺激提供了最优靶点。连续扰动会逐步使网络活动去同步，同时持续重塑相位、幅度和同步性响应景观，使网络进入修正后的动力学状态，且不改变最优刺激相位。这些累积效应在刺激强度、抑制性突触时间常数和独立网络实现中均保持鲁棒性。研究结果表明，相位、幅度和同步性是振荡神经元网络互补的动力学维度，为通过相位靶向扰动实现集体动力学的状态依赖控制提供了通用原则。
英文摘要
Oscillatory neuronal networks exhibit complex collective responses to external perturbations that depend on both the intrinsic network dynamics and the timing of stimulation. Although phase response curves (PRCs) have become a standard tool for characterizing these responses, phase resetting alone provides an incomplete description of how transient perturbations reshape collective activity. Here, we investigate the dynamics of a balanced excitatory-inhibitory network of exponential integrate-and-fire (EIF) neurons subjected to phase-targeted current pulses. By jointly analyzing the network phase response curve (nPRC), network amplitude response curve (nARC), and changes in the population synchrony, we establish a framework for characterizing collective network responses in terms of phase, amplitude, and synchronization. We show that identical stimulation pulses can either enhance, suppress, or leave network synchronization unchanged depending solely on their phase within the oscillation cycle, revealing distinct synchronizing and desynchronizing windows. The nARC further identifies robust phase intervals that maximize suppression of oscillatory activity and provide optimal targets for repeated stimulation. Successive perturbations progressively desynchronize the network activity while continuously reshaping the phase, amplitude, and synchrony response landscapes, driving the network toward a modified dynamical state without altering the optimal stimulation phase. These cumulative effects remain robust across stimulation intensities, inhibitory synaptic time constants, and independent network realizations. Our results demonstrate that phase, amplitude, and synchronization represent complementary dynamical dimensions of oscillatory neuronal networks and provide general principles for the state-dependent control of collective dynamics through phase-targeted perturbations.
