HP16: Estimating synaptic transmission changes in the epileptic brain with and without stimulation

Abstract

Computational modeling is a powerful tool for exploring brain mechanisms underlying neurophysiological observations. Nowadays, it is increasingly used to design and evaluate the effect of therapeutic interventions. In this contribution, the computational approach is used to investigate the effects of single pulse and repetitive electrical stimulation on excitation, slow dendritic and fast somatic inhibition in a rodent model of epilepsy. Method: Building on the modeling work of Wendling et al. (J Clin Neurophysiol 2005;22(5):343–356), we replicated local field potential recordings of hippocampal rat slices with and without stimulation. Through an automated comparison of simulated and real data segments, we classified different types of epileptic activity and estimated levels of excitatory and inhibitory synaptic gains across time. Result: Spontaneous transitions from interictal to ictal activity were associated with consistent patterns of excitatory and inhibitory dynamics. Interestingly, model results suggest that an increase of excitation close to seizure onset is preceded by a slow build-up of peri-dendritic inhibition. Single pulse stimulation with varying intensity led to seizure facilitation, accompanied by a significant increase in excitation pre-to-post stimulation. Repetitive stimulation at 1 Hz with varying intensity and duration led to seizure prevention, locking synaptic communication to a characteristic state post stimulation. During stimulation, we observed an increase of excitation, followed by a drop in somatic and an increase in dendritic inhibition, prolonging the duration of the inter-seizure interval. Conclusion: A slow build-up of dendritic inhibition might be linked to ictogenesis. Opposing effects of brain stimulation are associated with characteristic changes in synaptic transmission.