Department of Physics, University of Ottawa, 150 Louis Pasteur, Ottawa, ON, K1N6N5, Canada.
Centre for Neural Dynamics, University of Ottawa, Ottawa, Canada.
Biol Cybern. 2022 Apr;116(2):129-146. doi: 10.1007/s00422-022-00932-x.
We elucidate how coupling delays and noise impact phase and mutual information relationships between two stochastic brain rhythms. This impact depends on the dynamical regime of each PING-based rhythm, as well as on network heterogeneity and coupling asymmetry. The number of peaks at positive and negative time lags in the delayed mutual information between the two bi-directionally communicating rhythms defines our measure of flexibility of information sharing and reflects the number of ways in which the two networks can alternately lead one another. We identify two distinct mechanisms for the appearance of qualitatively similar flexible information sharing. The flexibility in the quasi-cycle regime arises from the coupling delay-induced bimodality of the phase difference distribution, and the related bimodal mutual information. It persists in the presence of asymmetric coupling and heterogeneity but is limited to two routes of information sharing. The second mechanism in noisy limit cycle regime is not induced by the delay. However, delay-coupling and heterogeneity enable communication routes at multiple time lags. Noise disrupts the shared compromise frequency, allowing the expression of individual network frequencies which leads to a slow beating pattern. Simulations of an envelope-phase description for delay-coupled quasi-cycles yield qualitatively similar properties as for the full system. Near the bifurcation from in-phase to out-of-phase behaviour, a single preferred phase difference can coexist with two information sharing routes; further, the phase laggard can be the mutual information leader, or vice versa. Overall, the coupling delay endows a two-rhythm system with an array of lead-lag relationships and mutual information resonances that exist in spite of the noise and across the Hopf bifurcation. These beg to be mapped out experimentally with the help of our predictions.
我们阐明了耦合延迟和噪声如何影响两个随机脑节律之间的相位和互信息关系。这种影响取决于基于 PING 的每个节律的动力学状态,以及网络异质性和耦合不对称性。在两个双向通信节律之间的延迟互信息的正滞后和负滞后处的峰数定义了我们衡量信息共享灵活性的指标,并反映了两个网络可以交替引导彼此的方式的数量。我们确定了两种不同的机制来出现定性相似的灵活信息共享。准循环状态下的灵活性源于相位差分布的耦合延迟诱导的双峰性,以及相关的双峰互信息。它在存在不对称耦合和异质性的情况下仍然存在,但仅限于两种信息共享途径。噪声极限环状态下的第二个机制不是由延迟引起的。然而,延迟耦合和异质性使多个时间滞后的通信路径成为可能。噪声会破坏共享的妥协频率,允许个体网络频率的表达,从而导致缓慢的跳动模式。延迟耦合准循环的包络相位描述的模拟产生了与完整系统定性相似的性质。在从同相到异相行为的分岔附近,单个首选相位差可以与两种信息共享途径共存;此外,相位滞后者可以成为互信息领先者,反之亦然。总体而言,耦合延迟赋予了两个节律系统一系列的领先滞后关系和互信息共振,这些关系存在于噪声和 Hopf 分岔的情况下。这些关系需要借助我们的预测在实验中进行映射。