Spatio-temporal dynamics of neurotransmitters and neuromodulators to predict seizures.

Despite decades of effort, we still cannot predict seizures with good accuracy. Patients' propensity to experiencing seizures changes throughout the day and is influenced by brain states. Therefore, seizure susceptibility not only depends on predictable circadian rhythms, but also on stochastic brain states. Key regulators of neuronal excitability, namely neurotransmitters (NTs) and neuromodulators (NMs), are also strongly modulated by circadian rhythms and brain states and so by tracking their fluctuations we should be able to better understand and predict seizure occurrence. Here I hypothesize that seizures are associated with specific, predictable neurochemical signatures. To test this, we will first take advantage of genetically-encoded neurotransmitter indicators and multi-fiber photometry to monitor 6 major NTs/NMs in chronic models of epilepsy. We will image simultaneously in 5 brain regions involved in seizure activity. Combined with electrophysiological recordings, this will allow us to investigate NT/NM distributions in relation to seizures and brain states. We will then manipulate the neurochemical environment either indirectly, by altering brain states, or directly, by optogenetic/chemogenetic techniques, to systematically test whether the extracted rules are necessary and sufficient to promote seizures. Through this work, I aim to build a comprehensive spatio-temporal map of the extracellular NT/NM landscape underlying seizure risk.