Network-level time computations in the suprachiasmatic nucleus
File(s)26772_0_merged_1713964749.pdf (1.26 MB)
Accepted version
Author(s)
Ness, Natalie
Brancaccio, Marco
Type
Journal Article
Abstract
Deciphering neuronal circuit dynamics is critical for understanding how the brain encodes information. In a recent study in Cell Research, Wang et al. shed light on how neuronal ensemble activity encodes time in the suprachiasmatic nucleus, and demonstrate the transformative potential of machine learning to decode complex neural processes.
Date Issued
2024-07
Date Acceptance
2024-05-01
Citation
Cell Research, 2024, 34 (7), pp.471-472
ISSN
1001-0602
Publisher
Springer Nature
Start Page
471
End Page
472
Journal / Book Title
Cell Research
Volume
34
Issue
7
Copyright Statement
Copyright © 2024 Springer-Verlag. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1038/s41422-024-00969-6
Identifier
https://www.nature.com/articles/s41422-024-00969-6
Subjects
Cell Biology
Life Sciences & Biomedicine
Science & Technology
Publication Status
Published
Date Publish Online
2024-05-08