ABSTRACT The switch between non-seizure and seizure states involves profound alterations in network excitability and synchrony. Both increased and decreased excitability may underlie the state transitions, as shown in epilepsy patients and animal models. Inspired by video-electroencephalography recordings in patients, we developed a framework to study spontaneous and photic-evoked neural and locomotor activity in zebrafish larvae. We combined high-throughput behavioral tracking and whole-brain in vivo two-photon calcium imaging to perform side-by-side comparison of multiple zebrafish seizure and epilepsy models. Our setup allowed us to dissect behavioral and physiological features that are divergent or convergent across multiple models. We observed that locomotor and neural activity during interictal and spontaneous ictal periods exhibit great diversity across models. Yet, during photic stimulation, hyperexcitability and rapid response dynamics was well conserved across multiple models, highlighting the reliability of photic-evoked seizure activity for high-throughput assays. Intriguingly, in several models, we observed that the initial elevated photic response is often followed by fast decay of neural activity and a prominent depressed state. We argue that such depressed states are likely due to homeostatic mechanisms triggered by excessive neural activity. An improved understanding of the interplay between elevated and depressed excitability states might suggest tailored epilepsy therapies. KEY POINTS Features of spontaneous locomotor and neural activity varies across zebrafish epilepsy and seizure models. We propose photic stimulation as a reliable tool to investigate behavioral and physiological phenotypes in zebrafish epilepsy and seizure models. We observed elevated activity with faster dynamics in response to photic stimulation in all tested zebrafish models. Photic-evoked neural responses were often followed by depressed state in seizure-prone networks

Elevated photic response is followed by a rapid decay and depressed state in ictogenic networks