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The Pattern of Glomerular Map Formation Defines Responsiveness to Aversive Odorants in Mice

2011· article· en· W1988691844 on OpenAlexafffund
Jin Hyung Cho, Janet E. A. Prince, Tyler Cutforth, Jean‐François Cloutier

Bibliographic record

VenueJournal of Neuroscience · 2011
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOlfactory bulbNeuroscienceSensory systemBiologyForagingOlfactionVomeronasal organDorsumCell biologyCentral nervous systemAnatomyEcology

Abstract

fetched live from OpenAlex

In many species, the detection and recognition of odors is critical to regulate behaviors that are essential for survival, such as foraging for food and avoidance of predators. The formation of complex stereotypic connections between olfactory sensory neurons (OSNs) and second-order neurons in the olfactory bulb (OB) is believed to be important for accurate odorant information processing. In mice, ablation of OSNs that innervate the dorsal region of the OB leads to a loss of avoidance behavior in response to aversive and predator odorants (Kobayakawa et al., 2007). It remains to be determined whether the accurate formation of a glomerular map in this region of the OB is required for these innate responses. Here, we have generated mice that lack expression of the axon guidance receptor Robo-2 in OSNs and found that ablation of Robo-2 expression leads to mistargeting of subsets of OSN axons within the dorsal region of the OB. Furthermore, these mice show decreased avoidance behavior toward the predator odorant trimethyl-thiazoline. Our results indicate that the pattern of glomerular innervation in the OB is critical for innate behavioral responses in mice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.182
GPT teacher head0.283
Teacher spread0.101 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations39
Published2011
Admission routes2
Has abstractyes

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