Determining higher-order organization of control and epileptic brain networks at single cell resolution

The pathological generation and propagation of seizures in the epileptic brain is poorly understood. The convergence of large-scale neural recording, quantitative massive network mining, and precise genetic engineering platforms provides us an unprecedented opportunity to examine epilepsy-induced alterations in mesoscale network dynamics. Here, we will identify higher-order features of neuronal circuits responsible for seizure initiation and propagation by quantifying mesoscale-network reorganization in genetic models of zebra sh that faithfully recapitulate seizure dynamics in humans. To further validate, we will quantify drug treatment induced network normalization.

Darian is currently housed in the Department of Bioengineering and is pursuing his PhD under the mentorship of Dr. Ivan Soltesz. Darian will leverage biophysically detailed computational models of the rodent hippocampus to investigate open questions in both the basic sciences and in translational research. Specifically, these models will be used to investigate the role of synaptic plasticity in the genesis of place fields and sharp-wave ripples. Characterizing these mechanisms will have important consequences regarding the formation and consolidation of episodic memories. Furthermore, Darian is investigating if seizures can be aborted in real-time through non-specific cell stimulation of the hilus. If computational modeling and subsequent experiment with rodents can confirm this hypothesis, then one can envision a generation of hippocampal brain-machine interfaces that can detect and provide closed-loop stimulation to abort seizures in humans.  Collectively, the symbiotic relationship between computational and experimental neuroscience heralds a new age towards the advancement of both basic and translational research.