On the spatiotemporal dynamics and couplings across epileptogenic networks

Abstract

For patients with partial epilepsy, one or several brain regions generate seizures ('epileptogenic zone' [1]), which may recruit other regions that are themselves non-epileptogenic. For these patients, the epileptogenic zone can sometimes be surgically removed and thus must be precisely delineated using intracranial EEG, giving us a deeper insight into the spatiotemporal dynamic of the seizure. Intracranial EEG times series show that brain regions and seizures may display a large variability in dynamics: (i) some seizures recruit more brain regions than others, (ii) the delays between the onset of the seizure in the epileptogenic zone and other areas can change on a time scale of several seconds, (iii) recruited areas exhibit different levels of coherence with the epileptogenic zone according to their position. Here we propose a model able to reproduce these 3 features (for other macroscopic models of seizures see [2,3]). Our network model comprises two neural masses autonomously able to produce epileptic seizure. We symmetrically coupled two of these neural mass models on a slow time scale (several seconds) and studied systematically the effect of two parameters : the epileptogenicity of the neural masses and the coupling values between neural masses. By choosing specific values of these parameters, we reproduce each of the features above (see Figure ​Figure1).1). We mathematically reduced the network model to uncover the essential mechanisms underlying a coupling acting on a slow time scale. Figure 1 Simultaneous times series of two coupled neural masses. The neural mass 1 starts first the seizure and then recruits the neural mass 2.