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Specialized structure of neural population codes in parietal cortex outputs.
Safaai, Houman; Wang, Alice Y; Kira, Shinichiro; Malerba, Simone Blanco; Panzeri, Stefano; Harvey, Christopher D.
Afiliação
  • Safaai H; Department of Neurobiology, Harvard Medical School, Boston, USA.
  • Wang AY; Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
  • Kira S; Department of Neurobiology, Harvard Medical School, Boston, USA.
  • Malerba SB; Department of Neurobiology, Harvard Medical School, Boston, USA.
  • Panzeri S; Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
  • Harvey CD; Neural Computation Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
bioRxiv ; 2023 Aug 26.
Article em En | MEDLINE | ID: mdl-37662297
ABSTRACT
Do cortical neurons that send axonal projections to the same target area form specialized population codes for transmitting information? We used calcium imaging in mouse posterior parietal cortex (PPC), retrograde labeling, and statistical multivariate models to address this question during a delayed match-to-sample task. We found that PPC broadcasts sensory, choice, and locomotion signals widely, but sensory information is enriched in the output to anterior cingulate cortex. Neurons projecting to the same area have elevated pairwise activity correlations. These correlations are structured as information-limiting and information-enhancing interaction networks that collectively enhance information levels. This network structure is unique to sub-populations projecting to the same target and strikingly absent in surrounding neural populations with unidentified projections. Furthermore, this structure is only present when mice make correct, but not incorrect, behavioral choices. Therefore, cortical neurons comprising an output pathway form uniquely structured population codes that enhance information transmission to guide accurate behavior.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article