A theoretical model for spontaneous seizure generation based on Markov chain process

Here a theoretical model for seizure generation is presented. This is done according to a simple physiological model of epileptic activities in which seizure occurrence is mainly attributed to imbalance of excitatory/inhibitory ratio. Although factors that play a role in ictogenesis are not exactly known, this process can be assumed as a stochastic process. Indeed, we claim that in neural synapses both excitatory and inhibitory gains change randomly. We propose that their values theoretically change as a tri-variant 2^nd-order Markov chain process. States of Markov chain must be selected such that any sudden change is avoided. Important result of this modeling is that epileptic behavior of a cortical area may appear in various manners not in a unique one. Thus different observations in seizure onset all are validated and it is proved that they do not contradict each other.