What the odor is not: Estimation by elimination.
Journal
Physical review. E
ISSN: 2470-0053
Titre abrégé: Phys Rev E
Pays: United States
ID NLM: 101676019
Informations de publication
Date de publication:
Aug 2021
Aug 2021
Historique:
received:
05
10
2020
accepted:
02
08
2021
entrez:
16
9
2021
pubmed:
17
9
2021
medline:
17
9
2021
Statut:
ppublish
Résumé
Olfactory systems use a small number of broadly sensitive receptors to combinatorially encode a vast number of odors. We propose a method of decoding such distributed representations by exploiting a statistical fact: Receptors that do not respond to an odor carry more information than receptors that do because they signal the absence of all odorants that bind to them. Thus, it is easier to identify what the odor is not rather than what the odor is. For realistic numbers of receptors, response functions, and odor complexity, this method of elimination turns an underconstrained decoding problem into a solvable one, allowing accurate determination of odorants in a mixture and their concentrations. We construct a neural network realization of our algorithm based on the structure of the olfactory pathway.
Identifiants
pubmed: 34525542
doi: 10.1103/PhysRevE.104.024415
pmc: PMC8892575
mid: NIHMS1779679
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
024415Subventions
Organisme : NIGMS NIH HHS
ID : SC2 GM140945
Pays : United States
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