Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex

Yina Wei (), Anirban Nandi, Xiaoxuan Jia, Joshua H. Siegle, Daniel Denman, Soo Yeun Lee, Anatoly Buchin, Werner Geit, Clayton P. Mosher, Shawn Olsen and Costas A. Anastassiou ()
Additional contact information
Yina Wei: Zhejiang Lab
Anirban Nandi: Allen Institute for Brain Science
Xiaoxuan Jia: Allen Institute for Brain Science
Joshua H. Siegle: Allen Institute for Brain Science
Daniel Denman: University of Denver
Soo Yeun Lee: Allen Institute for Brain Science
Anatoly Buchin: Allen Institute for Brain Science
Werner Geit: Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL) Campus Biotech
Clayton P. Mosher: Cedars-Sinai Medical Center
Shawn Olsen: Allen Institute for Brain Science
Costas A. Anastassiou: Cedars-Sinai Medical Center

Nature Communications, 2023, vol. 14, issue 1, 1-20

Abstract: Abstract The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-023-37844-8 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-37844-8

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-023-37844-8

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().