Association cortical areas in the mouse contain a large population of fast-spiking GABAergic neurons that do not express parvalbumin.
cerebral cortex
inhibitory interneurons
parvalbumin
perirhinal cortex
prefrontal cortex
Journal
The European journal of neuroscience
ISSN: 1460-9568
Titre abrégé: Eur J Neurosci
Pays: France
ID NLM: 8918110
Informations de publication
Date de publication:
21 Apr 2024
21 Apr 2024
Historique:
revised:
21
03
2024
received:
15
11
2023
accepted:
25
03
2024
medline:
22
4
2024
pubmed:
22
4
2024
entrez:
21
4
2024
Statut:
aheadofprint
Résumé
GABAergic neurons represent 10-15% of the neuronal population of the cortex but exert a powerful control over information flow in cortical circuits. The largest GABAergic class in the neocortex is represented by the parvalbumin-expressing fast-spiking neurons, which provide powerful somatic inhibition to their postsynaptic targets. Recently, the density of parvalbumin interneurons has been shown to be lower in associative areas of the mouse cortex as compared with sensory and motor areas. Modelling work based on these quantifications linked the low-density of parvalbumin interneurons with specific computations of associative cortices. However, it is still unknown whether the total GABAergic population of association cortices is smaller or whether another GABAergic type can compensate for the low density of parvalbumin interneurons. In the present study, we investigated these hypotheses using a combination of neuroanatomy, mouse genetics and neurophysiology. We found that the GABAergic population of association areas is comparable with that of primary sensory areas, and it is enriched of fast-spiking neurons that do not express parvalbumin and were not accounted for by previous quantifications. We developed an intersectional viral strategy to demonstrate that the population of fast-spiking neurons is comparable across cortical regions. Our results provide quantifications of the density of fast-spiking GABAergic neurons and offers new biological constrains to refine current models of cortical computations.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Norwegian Research Council
ID : 223262
Organisme : Norwegian Research Council
ID : 332640
Organisme : European Union's Horizon 2020 Research and Innovation Programme
ID : 885955
Organisme : Kavli Foundation
Informations de copyright
© 2024 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
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