Computational Modeling of Seizure Dynamics Using Coupled Neuronal Networks: Factors Shaping Epileptiform Activity

• DOI: 10.1371/journal.pcbi.1004209
• Publication Date: 2015-05-13T17:58:44Z
• Authors: Sebastien Naze; Christophe Bernard; Viktor Jirsa
• Keywords: Bursting; Network Dynamics; Biological neural network; Nerve net; Network model

Epileptic seizure dynamics span multiple scales in space and time. Understanding mechanisms requires identifying the relations between components within across these scales, together with analysis of their dynamical repertoire. Mathematical models have been developed to reproduce ranging from single neuron neural population. In this study, we develop a network model spiking neurons systematically investigate conditions, under which displays emergent dynamic behaviors known Epileptor, is well-investigated abstract epileptic activity. This approach allows us study biophysical parameters variables leading epileptiform discharges at cellular levels. Our composed two neuronal populations, characterized by fast excitatory bursting regular inhibitory neurons, embedded common extracellular environment represented slow variable. By analyzing parameter landscape offered simulation framework, typical sequences activity observed during status epilepticus. We find that exogenous fluctuations electro-tonic couplings play major role progression seizure, supports previous studies further validates our model. also influence chemical synaptic coupling generation spontaneous seizure-like events. results argue towards temporal shift spike waves as strengths are varied. demonstrate waves, including interictal spikes, generated primarily whereas wave part due neurons. Simulated traces compared vivo experimental data rodents different stages disorder. draw conclusion variations global excitability, environment, gap junction communication push system into paroxysmal regimes. discuss potential underlying such machinery relevance approach, supporting detailed modeling reflecting on limitations methodology.