Genes to networks - insights into dynamic brain pathology from genetic epilepsies (360G-Wellcome-209164_Z_17_Z)

Genetic mutations cause the majority of severe childhood epilepsies. Many 'epilepsy-genes' play a direct role in synaptic transmission, such as SCN1A (coding for voltage-gated sodium channels) and GRIN2A (coding for NMDA-receptor subunits). Some mutations also induce seizures in zebrafish larvae, a novel vertebral model of genetic epilepsies. Furthermore, long-term functional neuronal recordings of large neuronal networks using light sheet microscopy are now possible in these larvae, allowing unique insights into the pathophysiological of the epileptic brain. My proposal will utilise computational network modelling to identify mechanisms leading from synaptic dysfunction to whole-brain epileptic dynamics. I will (1) analyse patients' EEG recordings and light-sheet imaging in zebrafish with corresponding genetic mutations to evaluate whether there are shared abnormal network dynamics, (2) use Bayesian inversion of generative neuronal models to understand how microcircuit dysfunction leads to these abnormal dynamics, and (3) test the predictive validity of the generative models against empirical measurements of anti-epileptic drug effects. This work will provide insights into multi-scale mechanisms underlying devastating childhood epilepsies. The computational analyses will provide novel strategies to translate observations between animal models and patients, and thus in the future will increase the potential of these models to help the development of novel therapies.