The DOI matches its Crossref record.
Rats Smell in Stereo
Abstract
It has been hypothesized that rats and other mammals can use stereo cues to localize odor sources, but there is limited behavioral evidence to support this hypothesis. We found that rats trained on an odor-localization task can localize odors accurately in one or two sniffs. Bilateral sampling was essential for accurate odor localization, with internasal intensity and timing differences as directional cues. If the stimulus arrived at the correct point of the respiration cycle, internasal timing differences as short as 50 milliseconds sufficed. Neuronal recordings show that bulbar neurons responded differentially to stimuli from the left and stimuli from the right.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The neural mechanisms of gustation: A distributed processing code
Simon, S. A., de Araujo, I. E., Gutierrez, R., & Nicolelis, M. A. L. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn2006 · Cited by 305
The fluid dynamics of canine olfaction: unique nasal airflow patterns as an explanation of macrosmia
Craven, B. A., Paterson, E. G., & Settles, G. S. (2010) · Journal of The Royal Society Interface · doi:10.1098/rsif.2009.0490 · Cited by 301
Robust Odor Coding via Inhalation-Coupled Transient Activity in the Mammalian Olfactory Bulb
Cury, K. M., & Uchida, N. (2010) · Neuron · doi:10.1016/j.neuron.2010.09.040 · Cited by 275
Grid-like Neural Representations Support Olfactory Navigation of a Two-Dimensional Odor Space
Bao, X., Gjorgieva, E., Shanahan, L. K., Howard, J. D., Kahnt, T., & Gottfried, J. A. (2019) · Neuron · doi:10.1016/j.neuron.2019.03.034 · Cited by 207
Smelling sounds: Olfactory-auditory sensory convergence in the olfactory tubercle
Wesson, D. W., & Wilson, D. A. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.6003-09.2010 · Cited by 150
Metadata
- Authors
- Rajan, R., Clement, J. P., & Bhalla, U. S.
- Venue
- Science
- Published
- 2006-02-03
- Volume
- 311
- Issue
- 5761
- Pages
- 666-670
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1997834037
- Cited by
- 192
- References
- 0
- FWCI
- 5.23
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Rats Smell in Stereo. https://app.cochat.ai/papers/10.1126/science.1122096
- The paper
- Rajan, R., Clement, J. P., & Bhalla, U. S. (2006). Rats Smell in Stereo. Science. https://doi.org/10.1126/science.1122096
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
