Complementary codes for odor identity and intensity in olfactory cortex
Abstract
The ability to represent both stimulus identity and intensity is fundamental for perception. Using large-scale population recordings in awake mice, we find distinct coding strategies facilitate non-interfering representations of odor identity and intensity in piriform cortex. Simply knowing which neurons were activated is sufficient to accurately represent odor identity, with no additional information about identity provided by spike time or spike count. Decoding analyses indicate that cortical odor representations are not sparse. Odorant concentration had no systematic effect on spike counts, indicating that rate cannot encode intensity. Instead, odor intensity can be encoded by temporal features of the population response. We found a subpopulation of rapid, largely concentration-invariant responses was followed by another population of responses whose latencies systematically decreased at higher concentrations. Cortical inhibition transforms olfactory bulb output to sharpen these dynamics. Our data therefore reveal complementary coding strategies that can selectively represent distinct features of a stimulus.
Article and author information
Author details
Funding
National Institutes of Health (DC009839)
- Kevin M Franks
National Institutes of Health (DC015525)
- Kevin M Franks
Edward Mallinckrodt Jr. Foundation
- Kevin M Franks
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Upinder S Bhalla, National Centre for Biological Sciences, India
Ethics
Animal experimentation: All experimental protocols were approved by Duke University Institutional Animal Care and Use Committee according to protocols A243-12-09 and A220-15-08.
Version history
- Received: October 24, 2016
- Accepted: April 1, 2017
- Accepted Manuscript published: April 5, 2017 (version 1)
- Version of Record published: May 19, 2017 (version 2)
Copyright
© 2017, Bolding & Franks
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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