Eric L. Denovellis¶

Computational research scientist at UCSF — building scalable, interpretable tools to decode, categorize, and visualize how the brain represents information.

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About me¶

I build statistical models and open-source software to understand how the brain represents past experiences and alternative possibilities, and how those representations guide memory and decisions.

As a research scientist in Loren Frank’s lab at UCSF, I developed models that decode which location the hippocampus is representing from moment to moment, including during replay, when it rapidly reactivates sequences of paths. With collaborators, I adapted them to run in real time, enabling closed-loop neurofeedback on hippocampal spatial representations. I also co-led development of Spyglass, open-source software for reproducible, shareable neuroscience analysis.

I began developing these models as a postdoc at Boston University with Uri T. Eden and Mark A. Kramer. Before that, I did my Ph.D. in computational neuroscience there with Daniel H. Bullock and Earl K. Miller, where we showed that synchronized rhythms can pull rule-specific groups of neurons out of overlapping prefrontal circuits, supporting flexible switching between rules.