Cellular Mediators of Dentate Pattern Separation in Epilepsy - Temporal lobe epilepsy (TLE) represents 60% of all epilepsy cases and involves the hippocampus resulting in
memory and cognitive deficits. Within the hippocampus is the dentate gyrus (DG), a selectivity filter which
generates unique representations of contextually similar inputs, a process known as pattern separation. Pattern
separation relies on the coordinated activation of multiple types of interneurons (INs) which, in TLE, are
susceptible to cell death and reorganize. Without proper inhibition, granule cells (GCs), the main projection
neuron, fire imprecisely leading to failure in pattern separation. Two important IN subtypes in the DG are the
parvalbumin (PV) INs, which modulates GC firing by delivering reliable perisomatic inhibition thus affecting output
signals, and the somatostatin (SOM) INs, which modulates incoming signals by synapsing onto the distal
dendrites. However, their individual contributions to pattern separation computation have yet to be determined.
Recently, the semilunar granule cells (SGCs), an excitatory neuron identified by their wide dendrites, has been
hypothesized to aid in maintaining suppression of the non-firing GCs. How SGCs and GCs differ in molecular
and connectivity profiles is currently unknown. Interestingly, SGCs have been shown to be the primary source
of perisomatic excitation onto PV-INs, potentially enhancing feedback inhibition onto local GCs. However, how
SGCs affect network activity and their contribution to pattern separation in TLE is unknown. I hypothesize that
SGCs will show reduced intrinsic pattern separation compared to GCs and that SGC driven PV-IN activity more
robustly supports pattern separation than feedback dendritic inhibition by SOM-INs. Furthermore, experimental
TLE will disrupt the precision of SGC to PV/SOM-IN mediated inhibition resulting in pattern separation deficits.
This proposal will investigate the unique connectome of SGCs and, using an ex vivo temporal pattern separation
paradigm as well as a in silico DG network model, to elucidate the contributions of PV-INs and SOM-INs to
pattern separation in SGCs and GCs in healthy and epileptic circuits. Together, identification of the local circuit
mechanisms underlying dentate pattern separation and how it is impaired during epileptogenesis will pave the
way for novel strategies to manage memory related co-morbidities in epilepsy.
