Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning

Authors

Xiaohui Zhang, University of Illinois at Urbana-Champaign
Eric C. Landsness, Washington University School of Medicine in St. Louis
Wei Chen, Washington University School of Medicine in St. Louis
Hanyang Miao, Washington University School of Medicine in St. Louis
Michelle Tang, Washington University School of Medicine in St. Louis
Lindsey M. Brier, Washington University School of Medicine in St. Louis
Joseph P. Culver, Washington University School of Medicine in St. Louis
Jin-Moo Lee, Washington University School of Medicine in St. Louis
Mark A. Anastasio, University of Illinois at Urbana-Champaign

Journal

Journal of Neuroscience Methods

Publication Date

1-15-2022

Volume

366

First Page

109421

Document Type

Open Access Publication

DOI

10.1016/j.jneumeth.2021.109421

Rights and Permissions

Zhang X, Landsness EC, Chen W, Miao H, Tang M, Brier LM, Culver JP, Lee JM, Anastasio MA. Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning. J Neurosci Methods. 2022 Jan 15;366:109421. doi: 10.1016/j.jneumeth.2021.109421. © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Recommended Citation

Zhang, Xiaohui; Landsness, Eric C.; Chen, Wei; Miao, Hanyang; Tang, Michelle; Brier, Lindsey M.; Culver, Joseph P.; Lee, Jin-Moo; and Anastasio, Mark A., "Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning." Journal of Neuroscience Methods. 366, 109421 (2022).
https://digitalcommons.wustl.edu/oa_4/1344

Department

ICTS (Institute of Clinical and Translational Sciences)

Additional Links

Supplemental material is available for this article at publisher site.