2024/03/12 by Magnus J. E. Richardson, Richardson, Magnus J E
Computer Science · Neuroscience · Physics and Astronomy · #FOS: Biological sciences #Neural Networks and Applications #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #stochastic dynamics and bifurcation
paper · pdf · doi:10.48550/arxiv.2403.07670
openalex publication_date 2024/03/12 · openalex created_date 2024/03/14 · openalex updated_date 2026/07/28
The steady-state firing rate and firing-rate response of the leaky and exponential integrate-and-fire models receiving synaptic shot noise with excitatory and inhibitory reversal potentials is examined. For the particular case where the underlying synaptic conductances are exponentially distributed, it is shown that the master equation for a population of such model neurons can be reduced from an integro-differential form to a more tractable set of three differential equations. The system is nevertheless more challenging analytically than for current-based synapses: where possible analytical results are provided with an efficient numerical scheme and code provided for other quantities. The increased tractability of the framework developed supports an ongoing critical comparison between models in which synapses are treated with and without reversal potentials, such as recently in the context of networks with balanced excitatory and inhibitory conductances.