Vedururu Srinivas Ananth, Canavier Carmen C
Louisiana State University Health Sciences Center, Department of Cell Biology and Anatomy, New Orleans, LA, 70112, USA.
Louisiana State University Health Sciences Center, Department of Cell Biology and Anatomy, New Orleans, LA, 70112, USA.
Math Biosci. 2024 Dec;378:109335. doi: 10.1016/j.mbs.2024.109335. Epub 2024 Nov 2.
Phase Response Curves (PRCs) have been useful in determining and analyzing various phase-locking modes in networks of oscillators under pulse-coupling assumptions, as reviewed in Mathematical Biosciences, 226:77-96, 2010. Here, we update that review to include progress since 2010 on pulse coupled oscillators with conduction delays. We then present original results that extend the derivation of the criteria for stability of global synchrony in networks of pulse-coupled oscillators to include conduction delays. We also incorporate conduction delays to extend previous studies that showed how an alternating firing pattern between two synchronized clusters could enforce within-cluster synchrony, even for clusters unable to synchronize themselves in isolation. To obtain these results, we used self-connected neurons to represent clusters. These results greatly extend the applicability of the stability analyses to networks of pulse-coupled oscillators since conduction delays are ubiquitous and strongly impact the stability of synchrony. Although these analyses only strictly apply to identical oscillators with identical connections to other oscillators, the principles are general and suggest how to promote or impede synchrony in physiological networks of neurons, for example. Heterogeneity can be interpreted as a form of frozen noise, and approximate synchrony can be sustained despite heterogeneity. The pulse-coupled oscillator model can not only be used to describe biological neuronal networks but also cardiac pacemakers, lasers, fireflies, artificial neural networks, social self-organization, and wireless sensor networks.
如《数学生物学》2010年第226卷第77 - 96页所述,相位响应曲线(PRCs)在脉冲耦合假设下确定和分析振荡器网络中的各种锁相模式方面很有用。在此,我们更新该综述,以纳入自2010年以来关于具有传导延迟的脉冲耦合振荡器的进展。然后,我们给出原始结果,将脉冲耦合振荡器网络中全局同步稳定性判据的推导扩展到包含传导延迟的情况。我们还纳入传导延迟,以扩展先前的研究,这些研究表明两个同步簇之间的交替放电模式如何能够强制实现簇内同步,即使对于孤立时无法同步的簇也是如此。为了获得这些结果,我们使用自连接神经元来表示簇。这些结果极大地扩展了稳定性分析对脉冲耦合振荡器网络的适用性,因为传导延迟无处不在且对同步稳定性有强烈影响。尽管这些分析仅严格适用于与其他振荡器具有相同连接的相同振荡器,但这些原理具有普遍性,并举例说明了如何促进或阻碍神经元生理网络中的同步。异质性可以解释为一种冻结噪声的形式,并且尽管存在异质性,近似同步仍可维持。脉冲耦合振荡器模型不仅可用于描述生物神经元网络,还可用于描述心脏起搏器、激光器、萤火虫、人工神经网络、社会自组织和无线传感器网络。