The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Integration of visual motion and locomotion in mouse visual cortex
Open accessAbstract
Successful navigation through the world requires accurate estimation of one's own speed. To derive this estimate, animals integrate visual speed gauged from optic flow and run speed gauged from proprioceptive and locomotor systems. The primary visual cortex (V1) carries signals related to visual speed, and its responses are also affected by run speed. To study how V1 combines these signals during navigation, we recorded from mice that traversed a virtual environment. Nearly half of the V1 neurons were reliably driven by combinations of visual speed and run speed. These neurons performed a weighted sum of the two speeds. The weights were diverse across neurons, and typically positive. As a population, V1 neurons predicted a linear combination of visual and run speeds better than either visual or run speeds alone. These data indicate that V1 in the mouse participates in a multimodal processing system that integrates visual motion and locomotion during navigation.
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
Cites
Rao, R. P. N., & Ballard, D. H. (1999) · Nature Neuroscience · doi:10.1038/4580 · Cited by 5,483
Humans integrate visual and haptic information in a statistically optimal fashion
Ernst, M. O., & Banks, M. S. (2002) · Nature · doi:10.1038/415429a · Cited by 4,844
Canonical Microcircuits for Predictive Coding
Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.038 · Cited by 2,421
The importance of mixed selectivity in complex cognitive tasks
Rigotti, M., Barak, O., Warden, M. R., Wang, X.-J., Daw, N. D., Miller, E. K., & Fusi, S. (2013) · Nature · doi:10.1038/nature12160 · Cited by 1,639
Modulation of visual responses by behavioral state in mouse visual cortex
Niell, C. M., & Stryker, M. P. (2010) · Neuron · doi:10.1016/j.neuron.2010.01.033 · Cited by 1,483
Brain-wide neuronal dynamics during motor adaptation in zebrafish
Ahrens, M. B., Li, J. M., Orger, M. B., Robson, D. N., Schier, A. F., Engert, F., & Portugues, R. (2012) · Nature · doi:10.1038/nature11057 · Cited by 729
Sensorimotor mismatch signals in primary visual cortex of the behaving mouse
Keller, G. B., Bonhoeffer, T., & Hübener, M. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.040 · Cited by 668
Neural correlates of multisensory cue integration in macaque MSTd
Gu, Y., Angelaki, D. E., & DeAngelis, G. C. (2008) · Nature Neuroscience · doi:10.1038/nn.2191 · Cited by 554
Perception of self-motion from visual flow
Lappe, M., Bremmer, F., & van den Berg, A. V. (1999) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(99)01364-9 · Cited by 430
A computational perspective on the neural basis of multisensory spatial representations
Pouget, A., Deneve, S., & Duhamel, J.-R. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn914 · Cited by 413
Cited by
Spontaneous behaviors drive multidimensional, brainwide activity
Stringer, C., Pachitariu, M., Steinmetz, N., Reddy, C. B., Carandini, M., & Harris, K. D. (2019) · Science · doi:10.1126/science.aav7893 · Cited by 1,510
Self-citationThe neocortical circuit: themes and variations
Harris, K. D., & Shepherd, G. M. G. (2015) · Nature Neuroscience · doi:10.1038/nn.3917 · Cited by 1,215
Self-citationArousal and Locomotion Make Distinct Contributions to Cortical Activity Patterns and Visual Encoding
Vinck, M., Batista-Brito, R., Knoblich, U., & Cardin, J. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.028 · Cited by 819
Waking state: rapid variations modulate neural and behavioral responses
McGinley, M. J., Vinck, M., Reimer, J., Batista-Brito, R., Zagha, E., Cadwell, C. R., Tolias, A. S., Cardin, J. A., & McCormick, D. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.012 · Cited by 801
“…of locomotion on the spontaneous discharge rates of presumed pyramidal neurons recorded in other layers is more diverse (Ayaz et al., 2013; Beloozerova et al., 2003; Bennett et al., 2013; Nelson et al., 2013; Saleem et al., 2013; Schneider et al., 2014; Vinck et al., 2015; Zhou et al., 2014).”
Predictive Processing: A Canonical Cortical Computation
Keller, G. B., & Mrsic-Flogel, T. D. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.003 · Cited by 836
Metadata
- Authors
- Saleem, A. B., Ayaz, A., Jeffery, K. J., Harris, K. D., & Carandini, M.
- Venue
- Nature Neuroscience
- Published
- 2013-11-03
- Volume
- 16
- Issue
- 12
- Pages
- 1864-1869
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2040165511
- Cited by
- 418
- References
- 15
- FWCI
- 10.10
- Type
- journal article
- Language
- en
- Open access
- green
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: Integration of visual motion and locomotion in mouse visual cortex. https://app.cochat.ai/papers/10.1038/nn.3567
- The paper
- Saleem, A. B., Ayaz, A., Jeffery, K. J., Harris, K. D., & Carandini, M. (2013). Integration of visual motion and locomotion in mouse visual cortex. Nature Neuroscience. https://doi.org/10.1038/nn.3567
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.
