NeurIPS 2020poster35 citations
Identifying signal and noise structure in neural population activity with Gaussian process factor models
Stephen Keeley, Mikio Aoi, Yiyi Yu, Spencer Smith, Jonathan W Pillow
Abstract
Neural datasets often contain measurements of neural activity across multiple trials of a repeated stimulus or behavior. An important problem in the analysis of such datasets is to characterize systematic aspects of neural activity that carry information about the repeated stimulus or behavior of interest, which can be considered
BibTeX
@inproceedings{NEURIPS2020_9eed867b,
author = {Keeley, Stephen and Aoi, Mikio and Yu, Yiyi and Smith, Spencer and Pillow, Jonathan W},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
pages = {13795--13805},
publisher = {Curran Associates, Inc.},
title = {Identifying signal and noise structure in neural population activity with Gaussian process factor models},
url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/9eed867b73ab1eab60583c9d4a789b1b-Paper.pdf},
volume = {33},
year = {2020}
}