Coexistence of asynchronous and clustered dynamics in noisy inhibitory neural networks
New Journal of Physics(2024)
摘要
A regime of coexistence of asynchronous and clustered dynamics is analyzed
for globally coupled homogeneous and heterogeneous inhibitory networks of
quadratic integrate-and-fire (QIF) neurons subject to Gaussian noise. The
analysis is based on accurate extensive simulations and complemented by a
mean-field description in terms of low-dimensional next generation neural mass
models for heterogeneously distributed synaptic couplings. The asynchronous
regime is observable at low noise and becomes unstable via a sub-critical Hopf
bifurcation at sufficiently large noise. This gives rise to a coexistence
region between the asynchronous and the clustered regime. The clustered phase
is characterized by population bursts in the γ-range (30-120 Hz), where
neurons are split in two equally populated clusters firing in alternation. This
clustering behaviour is quite peculiar: despite the global activity being
essentially periodic, single neurons display switching between the two clusters
due to heterogeneity and/or noise.
更多查看译文
关键词
spiking neural networks,inhibition,noise,neural mass model,quadratic integrate-and-fire neuron,cluster synchronisation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要