Mechanisms underlying different onset patterns of focal seizures

Yujiang Wang, Andrew J Trevelyan, Antonio Valentin, Gonzalo Alarcon, Peter N Taylor and Marcus Kaiser

PLOS Computational Biology, 2017, vol. 13, issue 5, 1-22

Abstract: Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types—low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the “healthy” surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome.Author summary: Much attention has been devoted to the mechanisms underlying epileptic seizures. However, so far, the morphology of how seizures start on electrographic recordings (i.e. the seizure onset pattern) has been neglected as a potential indicator of the underlying dynamic mechanism. In this work, we take a spatio-temporal modelling approach to reproduce and understand two major seizure onset patterns. We find that it is not necessarily the initiation in the seizure core that determines onset pattern, but that the excitability of the surrounding “healthy” tissue plays a pivotal role in how the seizure onset appears. In agreement with previous computational modelling work, we hypothesise that indeed the two patterns could arise due to different dynamic onset mechanisms, where the surround excitability differs fundamentally in their dynamic properties. Our hypothesis indeed also offers a simple explanation for the clinically reported difference in surgical outcome for the two onset patterns. As an outlook, we also propose a possible way to track such changes in the surround excitability in a proof-of-principle computational demonstration.

Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1005475

DOI: 10.1371/journal.pcbi.1005475

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