A model for the evolution of the neuronal network in kindled brain slices

Abstract

A biologically realistic neuronal network model for epileptic burst dynamics in chemically kindled rat hippocampal slices is proposed. The neuronal dynamics of hippocampus is incorporated through Hindmarsh–Rose (HR) neurons. Creation of new synapses or strengthening of existing synapses observed in the kindled brain slices is modelled through a hebbian learning mechanism that is switched on during kindling. The model reproduces a number of important features of kindling experiments. Prior to kindling, the neuronal network shows low activity oscillation corresponding to the normal or resting state of the brain. Subthreshold stimulation leads to a small growth in synapses that is not enough to elicit afterdischarge and the network reverts to the resting phase. At a critical threshold the network shows novel bistable bursting dynamics characterized by recurrent transition between a low ‘normal’ activity and a high ‘bursting’ activity as observed in experiments. Suprathreshold stimuli generate seizure states. For the four initial network choices, i.e., regular, small world, random and modular topologies, bistable dynamics and seizure states were observed for all. We observe that all topologies lead to seizure generation by the same mechanism of formation of modular clusters that fire simultaneously during population bursts. We believe that this computer model for focal epilepsy shall be useful in future epilepsy research.