dc.contributor.author | Bolaños, F | |
dc.contributor.author | Orlandi, JG | |
dc.contributor.author | Aoki, R | |
dc.contributor.author | Jagadeesh, AV | |
dc.contributor.author | Gardner, JL | |
dc.contributor.author | Benucci, A | |
dc.date.accessioned | 2024-05-01T10:25:02Z | |
dc.date.available | 2024-02-06 | |
dc.date.available | 2024-05-01T10:25:02Z | |
dc.date.issued | 2024-03-19 | |
dc.identifier.citation | Bolaños, F., Orlandi, J.G., Aoki, R. et al. Efficient coding of natural images in the mouse visual cortex. Nat Commun 15, 2466 (2024). https://doi.org/10.1038/s41467-024-45919-3Bolaños, F., Orlandi, J.G., Aoki, R. et al. Efficient coding of natural images in the mouse visual cortex. Nat Commun 15, 2466 (2024). https://doi.org/10.1038/s41467-024-45919-3 | en_US |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/96583 | |
dc.description.abstract | How the activity of neurons gives rise to natural vision remains a matter of intense investigation. The mid-level visual areas along the ventral stream are selective to a common class of natural images-textures-but a circuit-level understanding of this selectivity and its link to perception remains unclear. We addressed these questions in mice, first showing that they can perceptually discriminate between textures and statistically simpler spectrally matched stimuli, and between texture types. Then, at the neural level, we found that the secondary visual area (LM) exhibited a higher degree of selectivity for textures compared to the primary visual area (V1). Furthermore, textures were represented in distinct neural activity subspaces whose relative distances were found to correlate with the statistical similarity of the images and the mice's ability to discriminate between them. Notably, these dependencies were more pronounced in LM, where the texture-related subspaces were smaller than in V1, resulting in superior stimulus decoding capabilities. Together, our results demonstrate texture vision in mice, finding a linking framework between stimulus statistics, neural representations, and perceptual sensitivity-a distinct hallmark of efficient coding computations. | en_US |
dc.format.extent | 2466 - ? | |
dc.language | eng | |
dc.publisher | Springer Nature | en_US |
dc.relation.ispartof | Nat Commun | |
dc.rights | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. | |
dc.subject | Animals | en_US |
dc.subject | Mice | en_US |
dc.subject | Photic Stimulation | en_US |
dc.subject | Visual Pathways | en_US |
dc.subject | Visual Cortex | en_US |
dc.subject | Neurons | en_US |
dc.subject | Visual Perception | en_US |
dc.title | Efficient coding of natural images in the mouse visual cortex. | en_US |
dc.type | Article | en_US |
dc.rights.holder | © The Author(s) 2024 | |
dc.identifier.doi | 10.1038/s41467-024-45919-3 | |
pubs.author-url | https://www.ncbi.nlm.nih.gov/pubmed/38503746 | en_US |
pubs.issue | 1 | en_US |
pubs.notes | Not known | en_US |
pubs.publication-status | Published online | en_US |
pubs.volume | 15 | en_US |
dcterms.dateAccepted | 2024-02-06 | |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |