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BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos

Eleanor Batty, Matthew Whiteway, Shreya Saxena, Dan Biderman, Taiga Abe, Simon Musall, Winthrop Gillis, Jeffrey Markowitz, Anne Churchland, John P. Cunningham, Sandeep R. Datta, Scott W. Linderman (+1 others)
2019 Neural Information Processing Systems  
Finally, based on this generative model, we develop a novel Bayesian decoding approach that takes in neural activity and outputs probabilistic estimates of the full-resolution behavioral video.  ...  This framework provides tools for compression, segmentation, generation, and decoding of behavioral videos.  ...  This work was supported by the Simons Foundation and the Gatsby Charitable Foundation, by NSF NeuroNex Award DBI-1707398, and by NIH awards 5U19NS107613, 5U19NS104649, and 1U19NS113201.  ... 
dblp:conf/nips/BattyWSBAMGMCCD19 fatcat:yi5z2lbrgbadpdbxrbefwhw7jy

Batty_columbia_0054D_15883.pdf [article]

2020
Bayesian decoding of natural images from these retinal cells.  ...  Finally, we present a probabilistic framework to distill behavioral videos into useful low-dimensional variables and to decode this behavior from neural activity.  ...  Acknowledgements The work presented in this thesis was done with the help of a plethora of wonderful mentors and collaborators.  ... 
doi:10.7916/d8-qb2a-3b48 fatcat:lflmn7yzcnca7dlnzefadrpwaq

Interrogating theoretical models of neural computation with deep inference [article]

Sean R Bittner, Agostina Palmigiano, Alex T Piet, Chunyu A Duan, Carlos D Brody, Kenneth D Miller, John P Cunningham
2019 bioRxiv   pre-print
Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or in terms of neural activity -- and thus can offer insights into neural computation.  ...  A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism.  ...  Behavenet: 452 nonlinear embedding and bayesian neural decoding of behavioral videos. Advances in Neural 453 Information Processing Systems, 2019. 454 [15] Liam Paninski and John P Cunningham.  ... 
doi:10.1101/837567 fatcat:c46qurti3jfzljsfvpg5mho6bi