Efficient coding of natural images in the mouse visual cortex

Federico Bolaños, Javier G. Orlandi (), Ryo Aoki, Akshay V. Jagadeesh, Justin L. Gardner and Andrea Benucci ()
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Federico Bolaños: University of British Columbia, Neuroimaging and NeuroComputation Centre
Javier G. Orlandi: University of Calgary, Department of Physics and Astronomy
Ryo Aoki: RIKEN Center for Brain Science, Laboratory for Neural Circuits and Behavior
Akshay V. Jagadeesh: Stanford University, Wu Tsai Neurosciences Institute
Justin L. Gardner: Stanford University, Wu Tsai Neurosciences Institute
Andrea Benucci: RIKEN Center for Brain Science, Laboratory for Neural Circuits and Behavior

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-45919-3

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