ArticleNature communications2024
Efficient coding of natural images in the mouse visual cortex.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Complex pectoral-fin-driven locomotion underlies refined visuomotor behavior in the cichlidiScience · 2026Article
- Article
- Ecological Visual Processing in the Mouse.Annual review of neuroscience · 2026Review
- Locomotion selectively enhances visual speed encoding in mouse medial higher visual areas.iScience · 2026Article
- Functional organization and natural scene responses across mouse visual cortical areas revealed with encoding manifolds.PloS one · 2026Article
- Top-down perceptual inference shaping the activity of early visual cortex.Nature communications · 2025Article
- Article
- A simplified minimodel of visual cortical neurons.Nature communications · 2025Article
- Broadband visual stimuli improve neuronal representation and sensory perception.Nature communications · 2025Article
- Decoding dynamic visual scenes across the brain hierarchy.PLoS computational biology · 2024Article
- Thalamocortical control of cell-type specificity drives circuits for processing whisker-related information in mouse barrel cortex.Nature communications · 2023Article
- Efficient processing of natural scenes in visual cortex.Frontiers in cellular neuroscience · 2022Review
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Authors and funding
6 authors.
Funding
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.
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