Aktay Sinan, Sander Leonard M, Zochowski Michal
Biophysics Program, <a href="https://ror.org/00jmfr291">University of Michigan, Ann Arbor</a>, Michigan 48105, USA.
Department of Physics, <a href="https://ror.org/00jmfr291">University of Michigan, Ann Arbor</a>, Michigan 48105, USA.
Phys Rev E. 2024 Oct;110(4-1):044401. doi: 10.1103/PhysRevE.110.044401.
Neuromodulatory processes in the brain can critically change signal processing on a cellular level, leading to dramatic changes in network level reorganization. Here, we use coupled nonidentical Kuramoto oscillators to investigate how changes in the shape of phase response curves from Type 1 to Type 2, mediated by varying ACh levels, coupled with activity-dependent plasticity may alter network reorganization. We first show that, when plasticity is absent, the Type 1 networks with symmetric adjacency matrix, as expected, exhibit asynchronous dynamics with oscillators of the highest natural frequency robustly evolving faster in terms of their phase dynamics. However, interestingly, Type 1 networks with an asymmetric connectivity matrix can produce stable synchrony (so-called splay states) with complex phase relationships. At the same time, Type 2 networks synchronize independent of the symmetry of their connectivity matrix, with oscillators locked so that those with higher natural frequency have a constant phase lead as compared to those with lower natural frequency. This relationship establishes a robust mapping between the frequency and oscillators' phases in the network, leading to structure and frequency mapping when plasticity is present. Finally, we show that biologically realistic, phase-locking dependent, connection plasticity naturally produces splay states in Type 1 networks that do not display the structure-frequency reorganization observed in synchronized Type II networks. These results indicate that the formation of splay states in the brain could be a common phenomenon.
大脑中的神经调节过程能够在细胞水平上显著改变信号处理,进而导致网络水平的重组发生巨大变化。在此,我们使用耦合的非相同Kuramoto振子来研究,由不同乙酰胆碱水平介导的从1型到2型相位响应曲线形状的变化,与活动依赖的可塑性相结合,如何改变网络重组。我们首先表明,当不存在可塑性时,具有对称邻接矩阵的1型网络,正如预期的那样,表现出异步动力学,具有最高自然频率的振子在相位动力学方面稳健地演化得更快。然而,有趣的是,具有不对称连接矩阵的1型网络可以产生具有复杂相位关系的稳定同步(所谓的展开状态)。同时,2型网络的同步与它们连接矩阵的对称性无关,振子被锁定,使得具有较高自然频率的振子相比于具有较低自然频率的振子具有恒定的相位领先。这种关系在网络中的频率和振子相位之间建立了稳健的映射,当存在可塑性时导致结构和频率映射。最后,我们表明,生物学上现实的、依赖锁相的连接可塑性自然地在1型网络中产生展开状态,而这些网络不会显示出在同步的2型网络中观察到的结构 - 频率重组。这些结果表明,大脑中展开状态的形成可能是一种常见现象。