Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai, India.
Department of Electronics and Communication Engineering, Presidency University, Bengaluru, Karnataka, India.
Biosystems. 2023 Oct;232:105010. doi: 10.1016/j.biosystems.2023.105010. Epub 2023 Aug 24.
A Locally active memristors can mimic neural synapses, resulting in rich neuro-morphological dynamics in biological neurons. To illustrate the impact of a local active memristive synapse, we consider coupled Hindmarsh-Rose (HR) neurons. Firstly, the dynamical transitions of the proposed system are investigated using bifurcation analysis and Lyapunov exponents, and we find that the transition between periodic and chaotic states depends on the input currents and memristive coupling strength. By performing the two-parameter analysis, the existence of periodic and chaotic regions is revealed. The collective behavior is then examined by expanding the network to include memristive coupled HR neurons under different network connectivities. We show that the system achieves synchronization behavior for all network connectivities, including regular, random, and small-world, when the strength of the memristive coupling is increased.
局部激活的忆阻器可以模拟神经突触，从而在生物神经元中产生丰富的神经形态动力学。为了说明局部激活的忆阻突触的影响，我们考虑耦合 Hindmarsh-Rose (HR) 神经元。首先，使用分岔分析和李雅普诺夫指数研究了所提出系统的动力学跃迁，发现周期性和混沌状态之间的跃迁取决于输入电流和忆阻耦合强度。通过进行双参数分析，揭示了周期性和混沌区域的存在。然后，通过扩展网络，在不同的网络连接下包括忆阻耦合的 HR 神经元，研究了集体行为。我们表明，当忆阻耦合强度增加时，系统在所有网络连接中都实现了同步行为，包括规则、随机和小世界。
