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Latent Variable Modeling of Neural Population Dynamics - Where Do We Go From Here?

Weekly Seminar | Not Open to the Public
Who Should Attend: 


Dr. Chethan Pandarinath's Photo
Assistant Professor
Departments of Biomedical Engineering and Neurosurgery


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 [].

Dr. Chethan Pandarinath's Figure


Chethan Pandarinath, Daniel J O'Shea, Jasmine Collins, Rafal Jozefowicz, Sergey D Stavisky, Jonathan C Kao, Eric M Trautmann, Matthew T Kaufman, Stephen I Ryu, Leigh R Hochberg, Jaimie M Henderson, Krishna V Shenoy, L F Abbott, David Sussillo
Inferring single-trial neural population dynamics using sequential auto-encoders
Nat Methods. 2018 Oct;15(10):805-815. doi: 10.1038/s41592-018-0109-9. Epub 2018 Sep 17.
Mohammad Reza Keshtkaran, Andrew R. Sedler, Raeed H. Chowdhury, Raghav Tandon, Diya Basrai, Sarah L. Nguyen, Hansem Sohn, Mehrdad Jazayeri, Lee E. Miller, Chethan Pandarinath
A large-scale neural network training framework for generalized estimation of single-trial population dynamics
bioRxiv 2021.01.13.426570v1. doi:
Feng Zhu, Harrison A. Grier, Raghav Tandon, Changjia Cai, Andrea Giovannucci, Matthew T. Kaufman, Chethan Pandarinath
A deep learning framework for inference of single-trial neural population activity from calcium imaging with sub-frame temporal resolution
bioRxiv 2021.11.21.469441v1. doi:


Tuesday, February 1, 2022 - 12:30pm


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