Eric L. Denovellis¶
Computational research scientist at UCSF — building scalable, interpretable tools to decode, categorize, and visualize how the brain represents information.
About me¶
I work in Dr. Loren Frank’s lab developing methods for decoding neural representations – particularly in the hippocampus. My methodological focus is on marked point process switching state space models for characterizing replay dynamics, work I began during my postdoc with Dr. Uri T. Eden. I work closely with experimental collaborators to ensure these methods are usable on large-scale data, and I build open-source infrastructure to make advanced computational techniques accessible to the broader neuroscience community.
Previously, I completed my Ph.D. in computational neuroscience at Boston University with Drs. Daniel H. Bullock and Earl K. Miller. There I developed computational tools and models to understand how prefrontal cortex supports the underlying neural computations necessary to switch between contexts. Specifically:
I showed how synchronous network oscillations in the prefrontal cortex provide a mechanism to flexibly coordinate context representations between groups of neurons during task switching.
I used generalized additive models to show that anterior cingulate neurons can represent context, but do not play a significant role in switching between contexts.
Finally, I developed a set of web-enabled interactive visualization tools designed to provide a multi-dimensional integrated view of electrophysiological datasets (See RasterVis and SpectraVis).
Education¶
Ph.D. in Computational Neuroscience, Boston University
Advisor: Daniel H. Bullock, Ph.D.; Co-mentor: Earl K. Miller, Ph.D.
Thesis Committee: Helen Barbas, Ph.D., David Somers, Ph.D., Uri T. Eden, Ph.D.
B.S. in Mathematics, University of California, Santa Barbara
B.A. in Philosophy, University of California, Santa Barbara
CV¶
Here is my CV.