ArticleNeuron2023
Interpreting the retinal neural code for natural scenes: From computations to neurons.
Article in Neuron, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- A standard model for the vertebrate retina.Vision research · 2026Article
- Temporal prediction captures retinal spiking responses across animal species.Nature communications · 2026Article
- Subunit-specific behavioral modulation of sensory tuning in the visual cortex.PLoS computational biology · 2026Article
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- Bioinspired spiking architecture enables energy constrained touch encoding.Nature communications · 2026Article
- Task success in trained spiking neural network models coincides with emergence of cross-stimulus-modulated inhibition.Biological cybernetics · 2026Article
- Speed modulations in grid cell information geometry.Nature communications · 2025Article
- Article
- Neural models for detection and classification of brain states and transitions.Communications biology · 2025Article
- Orthogonal neural representations support perceptual judgments of natural stimuli.Scientific reports · 2025Article
- Universality of representation in biological and artificial neural networks.bioRxiv : the preprint server for biology · 2024Article
- Stimulus-invariant aspects of the retinal code drive discriminability of natural scenes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Interpretable deep learning for deconvolutional analysis of neural signals.bioRxiv : the preprint server for biology · 2024Article
- Adaptation of retinal discriminability to natural scenes.bioRxiv : the preprint server for biology · 2024Article
- Plaid masking explained with input-dependent dendritic nonlinearities.Scientific reports · 2024Article
- Article
- Applying Super-Resolution and Tomography Concepts to Identify Receptive Field Subunits in the Retina.PLoS computational biology · 2024Article
- Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation.Nature communications · 2024Article
- Orthogonal neural representations support perceptual judgements of natural stimuli.bioRxiv : the preprint server for biology · 2024Article
- Encoding surprise by retinal ganglion cells.PLoS computational biology · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Understanding the circuit mechanisms of the visual code for natural scenes is a central goal of sensory neuroscience. We show that a three-layer network model predicts retinal natural scene responses with an accuracy nearing experimental limits. The model's internal structure is interpretable, as interneurons recorded separately and not modeled directly are highly correlated with model interneurons. Models fitted only to natural scenes reproduce a diverse set of phenomena related to motion encoding, adaptation, and predictive coding, establishing their ethological relevance to natural visual computation. A new approach decomposes the computations of model ganglion cells into the contributions of model interneurons, allowing automatic generation of new hypotheses for how interneurons with different spatiotemporal responses are combined to generate retinal computations, including predictive phenomena currently lacking an explanation. Our results demonstrate a unified and general approach to study the circuit mechanisms of ethological retinal computations under natural visual scenes.
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