We present a rate model of the spontaneous activity in the auditory cortex, based on synaptic depression. A Stochastic integro-differential
system of equations is derived and the analysis reveals two main regimes. The first regime corresponds to a normal activity.
The second regime corresponds to epileptic spiking. A detailed analysis of each regime is presented and we prove in particular
that synaptic depression stabilizes the global cortical dynamics. The transition between the two regimes is induced by a change
in synaptic connectivity: when the overall connectivity is strong enough, an epileptic activity is spontaneously generated.
Numerical simulations confirm the predictions of the theoretical analysis. In particular, our results explain the transition
from normal to epileptic regime which can be induced in rats auditory cortex, following a specific pairing protocol. A change
in the cortical maps reorganizes the synaptic connectivity and this transition between regimes is accounted for by our model.
We have used data from recording experiments to fit synaptic weight distributions. Simulations with the fitted distributions
are qualitatively similar to the real EEG recorded in vivo during the experiments.
We conclude that changes in the synaptic weight function in our model, which affects excitatory synapses organization and
reproduces the changes in cortical map connectivity can be understood as the main mechanism to explain the transitions of
the EEG from the normal to the epileptic regime in the auditory cortex.
Keywords modeling - spontaneous activity - auditory cortex - stochastic equations - epilepsy - rate model - synaptic depression
D.H is incumbent to the Hass Russell Career Chair Development.