Electroconvulsive therapy (ECT) is a procedure that involves the induction of seizures in the brain of patients with severe psychiatric disorders. The efficacy and therapeutic outcome of electrically-induced seizures is dependent upon both the stimulus intensity and the electrode placement over the scalp, with potentially signif- icant memory loss as side effect. Over the years, ECT modeling aimed to understand current propagation in the head medium with increasingly realistic geometry and conductivity descriptions. The utility of these models remain limited since seizure propagation in the active neural tissue has largely been ignored. Accordingly, a modeling framework that combines head conductivity models with active neural models to describe observed EEG signals under ECT is highly desirable. We present herein a simplified multi-area active neural model that describes (i) the transition from normal to seizure states under external stimuli with particular emphasis on disinhibition and (ii) the initiation and propagation of seizures between multiple connected brain areas. A simulation scenario is shown to qualitatively resemble clinical EEG recordings of ECT. Fitting model param- eters is then performed using modern nonlinear state estimation approaches (cubature Kalman filters). Future work will integrate active models with passive volume conduction approaches to explore seizure induction and propagation.