PMID- 26938460
OWN - NLM
STAT- MEDLINE
DCOM- 20160711
LR  - 20190201
IS  - 1553-7358 (Electronic)
IS  - 1553-734X (Print)
IS  - 1553-734X (Linking)
VI  - 12
IP  - 3
DP  - 2016 Mar
TI  - Extracting Behaviorally Relevant Traits from Natural Stimuli: Benefits of 
      Combinatorial Representations at the Accessory Olfactory Bulb.
PG  - e1004798
LID - 10.1371/journal.pcbi.1004798 [doi]
LID - e1004798
AB  - For many animals, chemosensation is essential for guiding social behavior. 
      However, because multiple factors can modulate levels of individual chemical 
      cues, deriving information about other individuals via natural chemical stimuli 
      involves considerable challenges. How social information is extracted despite 
      these sources of variability is poorly understood. The vomeronasal system 
      provides an excellent opportunity to study this topic due to its role in 
      detecting socially relevant traits. Here, we focus on two such traits: a female 
      mouse's strain and reproductive state. In particular, we measure stimulus-induced 
      neuronal activity in the accessory olfactory bulb (AOB) in response to various 
      dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus 
      female mice from two different strains. We first show that all tested secretions 
      provide information about a female's receptivity and genotype. Next, we 
      investigate how these traits can be decoded from neuronal activity despite 
      multiple sources of variability. We show that individual neurons are limited in 
      their capacity to allow trait classification across multiple sources of 
      variability. However, simple linear classifiers sampling neuronal activity from 
      small neuronal ensembles can provide a substantial improvement over that attained 
      with individual units. Furthermore, we show that some traits are more efficiently 
      detected than others, and that particular secretions may be optimized for 
      conveying information about specific traits. Across all tested stimulus sources, 
      discrimination between strains is more accurate than discrimination of 
      receptivity, and detection of receptivity is more accurate with vaginal 
      secretions than with urine. Our findings highlight the challenges of chemosensory 
      processing of natural stimuli, and suggest that downstream readout stages decode 
      multiple behaviorally relevant traits by sampling information from distinct but 
      overlapping populations of AOB neurons.
FAU - Kahan, Anat
AU  - Kahan A
AD  - Department of Medical Neurobiology, Hebrew University Medical School, Jerusalem, 
      Israel.
FAU - Ben-Shaul, Yoram
AU  - Ben-Shaul Y
AD  - Department of Medical Neurobiology, Hebrew University Medical School, Jerusalem, 
      Israel.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20160303
PL  - United States
TA  - PLoS Comput Biol
JT  - PLoS computational biology
JID - 101238922
SB  - IM
MH  - Animals
MH  - Computer Simulation
MH  - Estrus/*physiology
MH  - Female
MH  - *Genetic Background
MH  - Mating Preference, Animal/*physiology
MH  - Mice
MH  - Mice, Inbred BALB C
MH  - Mice, Inbred C57BL
MH  - *Models, Neurological
MH  - Nerve Net/physiology
MH  - Odorants
MH  - Olfactory Bulb/*physiology
MH  - Olfactory Perception/*physiology
MH  - Sex Characteristics
PMC - PMC4777510
COIS- The authors have declared that no competing interests exist.
EDAT- 2016/03/05 06:00
MHDA- 2016/07/12 06:00
PMCR- 2016/03/03
CRDT- 2016/03/04 06:00
PHST- 2015/07/13 00:00 [received]
PHST- 2016/02/08 00:00 [accepted]
PHST- 2016/03/04 06:00 [entrez]
PHST- 2016/03/05 06:00 [pubmed]
PHST- 2016/07/12 06:00 [medline]
PHST- 2016/03/03 00:00 [pmc-release]
AID - PCOMPBIOL-D-15-01161 [pii]
AID - 10.1371/journal.pcbi.1004798 [doi]
PST - epublish
SO  - PLoS Comput Biol. 2016 Mar 3;12(3):e1004798. doi: 10.1371/journal.pcbi.1004798. 
      eCollection 2016 Mar.