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Asst. Prof.
Georgia Tech & Emory University
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Schedule
Wednesday, December 1, 2021
2:00 AM America/New_York
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Recording provided by the organiser.
Domain
NeuroscienceHost
Neuromatch 4
Duration
60 minutes
Large-scale recordings of neural activity are providing new opportunities to study network-level dynamics with unprecedented detail. However, the sheer volume of data and its dynamical complexity are major barriers to uncovering and interpreting these dynamics. I will present machine learning frameworks that enable inference of dynamics from neuronal population spiking activity on single trials and millisecond timescales, from diverse brain areas, and without regard to behavior. I will then demonstrate extensions that allow recovery of dynamics from two-photon calcium imaging data with surprising precision. Finally, I will discuss our efforts to facilitate comparisons within our field by curating datasets and standardizing model evaluation, including a currently active modeling challenge, the 2021 Neural Latents Benchmark [neurallatents.github.io].
Chethan Pandarinath
Asst. Prof.
Georgia Tech & Emory University
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