|
|
|
Data
|
Mesoscopic dynamics from AdEx recurrent networks (Zerlaut et al JCNS 2018)
|
Yann Zerlaut
|
|
|
|
|
We present a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions. We study a network of regular-spiking (RS) excitatory neurons and fast-spiking (FS) inhibitory neurons. We use a Master Equation formalism, together with a semi-analytic approach to the transfer function of AdEx neurons to describe the average dynamics of the coupled populations. We compare the predictions of this mean-field model to simulated networks of RS-FS cells, first at the level of the spontaneous activity of the network, which is well predicted by the analytical description. Second, we investigate the response of the network to time-varying external input, and show that the mean-field model predicts the response time course of the population. Finally, to model VSDi signals, we consider a one-dimensional ring model made of interconnected RS-FS mean-field units.
|
|
|
-
Abstract integrate-and-fire adaptive exponential (AdEx) neuron Show
Other
|
|
|
|
|
|
|
|
|
|
|
-
Zerlaut Y, Chemla S, Chavane F, Destexhe A (2018) Show
Other
|
|
|
|
|
|
|
|
|
|
|
|
yann.zerlaut@iit.it
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Zerlaut, Y., Chemla, S., Chavane, F. et al. J Comput Neurosci (2017). https://doi.org/10.1007/s10827-017-0668-2
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
