Odor identity coding by distributed ensembles of neurons in the mouse olfactory cortex
Abstract
Olfactory perception and behaviors critically depend on the ability to identify an odor across a wide range of concentrations. Here, we use calcium imaging to determine how odor identity is encoded in olfactory cortex. We find that, despite considerable trial-to-trial variability, odor identity can accurately be decoded from ensembles of co-active neurons that are distributed across piriform cortex without any apparent spatial organization. However, piriform response patterns change substantially over a 100-fold change in odor concentration, apparently degrading the population representation of odor identity. We show that this problem can be resolved by decoding odor identity from a subpopulation of concentration-invariant piriform neurons. These concentration-invariant neurons are overrepresented in piriform cortex but not in olfactory bulb mitral and tufted cells. We therefore propose that distinct perceptual features of odors are encoded in independent subnetworks of neurons in the olfactory cortex.
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Author details
Funding
Marie Curie International Reintegration Grant (IRG 276869)
- Alexander Fleischmann
Fondation pour la Recherche Médicale (AJE201106)
- Alexander Fleischmann
European Molecular Biology Organization (ASTF 395 - 2014)
- Benjamin Roland
LabEx Memolife
- Benjamin Roland
National Institute on Deafness and Other Communication Disorders (DC009839 and DC015525)
- Kevin M Franks
Agence Nationale de la Recherche (SENSEMAKER)
- Brice Bathellier
Human Frontier Science Program (CDA-0064-2015)
- Brice Bathellier
Marie Curie Program (CIG 334581)
- Brice Bathellier
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: This study was performed in strict accordance with French National and INSERM animal care and use committee guidelines (#B750512/00615.02). All surgery was performed under ketamine/xylazine anesthesia.
Copyright
© 2017, Roland et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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