Characterisation of seizure dynamics in zebrafish to investigate critical transitions in epilepsy
Alice Oldano, PhD supervisor: Alexander Skupin with Alexander Crawford
The project aims to characterise epileptic seizure dynamics at single-cell resolution and understand the spatiotemporal neuronal interactions with respect to early warning signatures. Through a collaboration with the EMBL (an FNR CORE-EMBL project on microglial dynamics in the epileptic brain), AC’s group is already investigating the brain activity of zebrafish epilepsy models using calcium imaging analysis of transgenic zebrafish larvae with pan-neural expression of a GCaMP calcium indicator (Akerboom 2012). By improving the resolution of this imaging analysis using selective plane illumination microscopy (SPIM), we will be able to track the activity of many neurons in parallel at the single-cell level, thereby providing significantly increased insight into the activity dynamics of at least a subset of the neural networks involved in the initiation of epileptic seizures (Keller 2015). The data obtained by this high-resolution imaging analysis of brain activity before and during epileptic seizures will be useful for the analytical approaches developed within this DTU for the identification and characterisation of CTs and, subsequently, for the possible generation of a theoretical model for seizure initiation. In particular, the subproject will also provide spatial dynamic data that will allow for the development of a spatial distribution framework (AS) and percolation-like statistical description (ME).
Within this project, 2-3 zebrafish epilepsy models (Afrikanova 2013; Schubert 2014)will first be migrated to a transgenic line expressing a GCaMP calcium indicator under the control of a pan-neural promoter such as her4. Upon integration of a new SPIM microscope at the LCSB imaging facility, these models will be subjected to high-resolution calcium imaging analysis to characterise the activity patterns of differently sized subsets of neurons before and during epileptic seizures (Jiruska 2013). In this manner, we will generate experimental data on neural activity patterns in zebrafish models of epilepsy that can be analysed for the identification and characterisation of CTs in neural activity.
The theoretical frameworks developed within this DTU will serve as the basis for analysing the neural activity data from our zebrafish epilepsy models with regards to the identification and characterisation of CTs. In turn, the experimental data generated by our group can possibly be used to generate new models of critical transitions. In the long run, insights generated by this type of analysis may help inform efforts for seizure prediction, in which device-based monitoring of human brain activity may be able to predict epileptic seizures before these occur, possibly enabling their prevention through acute pharmacological or electrical intervention.