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Christina Weaver
I received my PhD in Applied Mathematics and Statistics from Stony Brook University in 2003. Since then I have been at Mount Sinai, originally as an NSF Postdoctoral Fellow in Interdisciplinary Informatics. My research interests include computational neuroscience and image analysis. My thesis work contributed to image analysis software packages that are applicable to many biological systems, particularly automated analysis of neuronal morphology. My current research centers around modeling of neurons of the precerebellar nucleus Area II in goldfish. These neurons are necessary for eye velocity storage, a mechanism that displays persistent activity after extinguishing visual or vestibular stimuli. Persistent activity is found in many different brain regions, and is believed to be a mechanism responsible for working memory. We study how the morphology and intrinsic membrane properties of Area II neurons interact to shape their firing properties. To this end, I am developing both simplified and morphologically faithful models of Area II neurons that are consistent with experimental data. The models are based on the actual morphology traced from the neurons, and are constrained by experiments in vivo and in vitro performed within CNIC by Dr Georgi Gamkrelidze, and by our collaborator at NYU Medical School, Dr Robert Baker. More generally, I am interested in computational methods to parameterize and analyze mathematical models. These methods include parameter optimization and sensitivity analysis. I have designed objective functions capable of capturing a range of neuronal dynamics, used to guide automated parameter searches. I have also developed techniques to investigate the sensitivity of model output to its parameters. Applied to our compartmental modeling studies, these techniques allow us to assess how morphology, active conductances and passive cable properties influence neuronal dynamics, in Area II and in other brain regions. |