Pathophysiological mechanisms of absence epilepsy: a computational modelling study

Abstract

A typical absence is a non-convulsive epileptic seizure that is a sole symptom of childhood absence epilepsy (CAE). It is characterised by a generalised hyper-synchronous activity (2.5-5 Hz) of neurons in the thalamocortical network that manifests as a spike and slow-wave discharge (SWD) in the electroencephalogram. Although CAE is not a benign form of epilepsy, its physiological basis is not well understood. In an attempt to make progress regarding the mechanism of SWDs, I built a large-scale computational model of the thalamocortical network that replicated key cellular and network electric oscillatory behaviours. Model simulation indicated that there are multiple pathological pathways leading to SWDs. They fell into three categories depending on their network-level effects. Moreover, all SWDs had the same physiological mechanism of generation irrespective of their underlying pathology. They were initiated by an increase in NRT cell bursting prior to the SWD onset. SWDs critically depended on the T-type Ca2+ current (IT) mediated firing in NRT and higher-order thalamocortical relay cells (TCHO), as well as GABAB synaptic receptor-mediated IPSPs in TCHO cells. On the other hand, first-order thalamocortical cells were inhibited during SWDs and did not actively participate in their generation. These cells, however, could promote or disrupt SWD generation if they were hyperpolarised or depolarised, respectively. Importantly, only a minority of active TC cells with a small proportion of them bursting were necessary to ensure the SWD generation. In terms of their relationship to other brain rhythms, simulated SWDs were a product of NRT sleep spindle (6.5-14 Hz) and cortical δ (1-4 Hz) pacemakers and had their oscillation frequency settle between the preferred oscillation frequencies of the two pacemakers with the actual value depending on the cortical bursting intensity. These modelling results are discussed in terms of their implications for understanding CAE and its future research and treatment

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