ArticleNature communications2020
Natural images are reliably represented by sparse and variable populations of neurons in visual cortex.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed, 129 citations in OpenAlex.
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- Ultrasound Modulation of Visual Circuits in Mice Independent of Auditory Confound.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Learnable Diffusion Framework for Mouse V1 Neural Decoding.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Multidimensional visual feature encoding and functional organization in the pigeon entopallium.Zoological research · 2026Article
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- Triggering action potentials of a single neuron by multiphoton excitation elicits visually guided behavior.Nature communications · 2026Article
- Data-driven ANN-based visual decoding enables unsupervised functional alignment.Communications biology · 2026Article
- Mapping the visual cortex with Zebra noise and wavelets.Journal of vision · 2026Article
- Behavioral techniques for controlling visual stimuli to modulate visual processing in the brain and their implementation in augmented reality technology.Frontiers in neuroscience · 2026Review
- State-space kinetic Ising model reveals task-dependent entropy flow in sparsely active nonequilibrium neuronal dynamics.Nature communications · 2025Article
- Emergence of sparse coding, balance and decorrelation from a biologically-grounded spiking neural network model of learning in the primary visual cortex.PLoS computational biology · 2025Article
- Efficient and robust temporal processing with neural oscillations modulated spiking neural networks.Nature communications · 2025Article
- Temporal coding carries more stable cortical visual representations than firing rate over time.Nature communications · 2025Article
- Continual familiarity decoding from recurrent connections in spiking networks.PLoS computational biology · 2025Article
- Multiphoton Neurophotonics: Recent Advances in Imaging and Manipulating Neuronal Circuits.ACS photonics · 2025Review
- The cortical critical power law balances energy and information in an optimal fashion.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Recurrent cortical networks encode natural sensory statistics via sequence filtering.bioRxiv : the preprint server for biology · 2025Article
- Tensor-powered insights into neural dynamics.Communications biology · 2025Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Natural scenes sparsely activate neurons in the primary visual cortex (V1). However, how sparsely active neurons reliably represent complex natural images and how the information is optimally decoded from these representations have not been revealed. Using two-photon calcium imaging, we recorded visual responses to natural images from several hundred V1 neurons and reconstructed the images from neural activity in anesthetized and awake mice. A single natural image is linearly decodable from a surprisingly small number of highly responsive neurons, and the remaining neurons even degrade the decoding. Furthermore, these neurons reliably represent the image across trials, regardless of trial-to-trial response variability. Based on our results, diverse, partially overlapping receptive fields ensure sparse and reliable representation. We suggest that information is reliably represented while the corresponding neuronal patterns change across trials and collecting only the activity of highly responsive neurons is an optimal decoding strategy for the downstream neurons.
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