Identification of effective stimulation parameters to abort epileptic seizures in a neural mass model

Pathological brain activity can be modulated by using electrical stimulation. However, one major challenge is the identification of the optimal parameter values normalizing pathological activity towards more physiological patterns. One possible approach to address this challenge is the use of computational models. Here, we used a validated neural mass model (NMM) to simulate epileptiform activity and its modulation by electrical stimulation. Based on simple features of the simulated signals before and during stimulation within the time and frequency domains, we studied the effectiveness of a given stimulation parameters. Stimulations inducing a membrane polarization greater than 4 mV and a frequency over 25 Hz were identified as common effective parameters for the majority of epileptiform signals. This work provides further evidence for model-guided stimulation parameters optimization as a rationale for neuromodulation therapy refinement.