Recurrent seizures, which define epilepsy, are transient abnormalities in the electrical activity of the brain. The mechanistic basis of seizure initiation, and the contribution of defined neuronal subtypes to seizure pathophysiology, remains poorly understood. We performedin vivotwo-photon calcium imaging in neocortex during temperature-induced seizures in male and female Dravet syndrome (Scn1a+/−) mice, a neurodevelopmental disorder with prominent temperature-sensitive epilepsy. Mean activity of both putative principal cells and parvalbumin-positive interneurons (PV-INs) was higher inScn1a+/− relative to wild-type controls during quiet wakefulness at baseline and at elevated core body temperature. However, wild-type PV-INs showed a progressive synchronization in response to temperature elevation that was absent in PV-INs fromScn1a+/− mice. Hence, PV-IN activity remains intact interictally inScn1a+/− mice, yet exhibits decreased synchrony immediately before seizure onset. We suggest that impaired PV-IN synchronization may contribute to the transition to the ictal state during temperature-induced seizures in Dravet syndrome.SIGNIFICANCE STATEMENTEpilepsy is a common neurological disorder defined by recurrent, unprovoked seizures. However, basic mechanisms of seizure initiation and propagation remain poorly understood. We performedin vivotwo-photon calcium imaging in an experimental model of Dravet syndrome (Scn1a+/− mice)—a severe neurodevelopmental disorder defined by temperature-sensitive, treatment-resistant epilepsy—and record activity of putative excitatory neurons and parvalbumin-positive GABAergic neocortical interneurons (PV-INs) during naturalistic seizures induced by increased core body temperature. PV-IN activity was higher inScn1a+/− relative to wild-type controls during quiet wakefulness. However, wild-type PV-INs showed progressive synchronization in response to temperature elevation that was absent in PV-INs fromScn1a+/− mice before seizure onset. Hence, impaired PV-IN synchronization may contribute to transition to seizure in Dravet syndrome.

Many recent efforts in computational modeling of macro-scale brain dynamics have begun to take a data-driven approach by incorporating structural and/or functional information derived from subject data. Here, we discuss recent work using personalized brain network models to study structure-function relationships in human brains. We describe the steps necessary to build such models and show how this computational approach can provide previously unobtainable information through the ability to perform virtual experiments. Finally, we present examples of how personalized brain network models can be used to gain insight into the effects of local stimulation and improve surgical outcomes in epilepsy.

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