State and parameter estimation of a neural mass model from electrophysiological signals during the status epilepticus
Abstract
Status epilepticus is an emergency condition in patients with prolonged seizure or recurrent seizures without full recovery between them. The pathophysiological mechanisms of status epilepticus are not well established. With this argument, we use a computational modeling approach combined with in vivo electrophysiological data obtained from an experimental model of status epilepticus to infer about changes that may lead to a seizure. Special emphasis is done to analyze parameter changes during or after pilocarpine administration. A cubature Kalman filter is utilized to estimate parameters and states of the model in real time from the observed electrophysiological signals. It was observed that during basal activity (before pilocarpine administration) the parameters presented a standard deviation below 30% of the mean value, while during SE activity, the parameters presented variations larger than 200% of the mean value with respect to basal state. The ratio of excitation-inhibition, increased during SE activity by 80% with respect to the transition state, and reaches the lowest value during cessation. In addition, a progression between low and fast inhibitions before or during this condition was found. This method can be impleme...Continue Reading
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