Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making.


Journal

Nature neuroscience
ISSN: 1546-1726
Titre abrégé: Nat Neurosci
Pays: United States
ID NLM: 9809671

Informations de publication

Date de publication:
03 2023
Historique:
received: 12 01 2022
accepted: 06 12 2022
pubmed: 24 1 2023
medline: 10 3 2023
entrez: 23 1 2023
Statut: ppublish

Résumé

Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Functional differences across pyramidal neuron (PyN) types have been observed within cortical areas, but it is not known whether these local differences extend throughout the cortex, nor whether additional differences emerge when larger-scale dynamics are considered. We used genetic and retrograde labeling to target pyramidal tract, intratelencephalic and corticostriatal projection neurons and measured their cortex-wide activity. Each PyN type drove unique neural dynamics, both at the local and cortex-wide scales. Cortical activity and optogenetic inactivation during an auditory decision task revealed distinct functional roles. All PyNs in parietal cortex were recruited during perception of the auditory stimulus, but, surprisingly, pyramidal tract neurons had the largest causal role. In frontal cortex, all PyNs were required for accurate choices but showed distinct choice tuning. Our results reveal that rich, cell-type-specific cortical dynamics shape perceptual decisions.

Identifiants

pubmed: 36690900
doi: 10.1038/s41593-022-01245-9
pii: 10.1038/s41593-022-01245-9
pmc: PMC9991922
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

495-505

Subventions

Organisme : NIMH NIH HHS
ID : F32 MH120888
Pays : United States

Informations de copyright

© 2023. The Author(s).

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Auteurs

Simon Musall (S)

Institute of Biological Information Processing (IBI-3), Forschungszentrum Jülich, Jülich, Germany. s.musall@fz-juelich.de.
Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany. s.musall@fz-juelich.de.

Xiaonan R Sun (XR)

Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.
Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.

Hemanth Mohan (H)

Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.
Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.

Xu An (X)

Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.
Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.

Steven Gluf (S)

Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.

Shu-Jing Li (SJ)

Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.

Rhonda Drewes (R)

Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.

Emma Cravo (E)

Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany.

Irene Lenzi (I)

Institute of Biological Information Processing (IBI-3), Forschungszentrum Jülich, Jülich, Germany.
Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany.

Chaoqun Yin (C)

Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.

Björn M Kampa (BM)

Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany.
JARA Brain, Institute for Neuroscience and Medicine (INM-10), Forschungszentrum Jülich, Jülich, Germany.

Anne K Churchland (AK)

Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA. achurchland@mednet.ucla.edu.
Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. achurchland@mednet.ucla.edu.

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Classifications MeSH