ArticlePLoS computational biology2016
Error-Robust Modes of the Retinal Population Code.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Exact minimax entropy models of large-scale neuronal activity.Physical review. E · 2025Article
- Latent dynamics of primary sensory cortical population activity structured by fluctuations in the local field potential.Frontiers in computational neuroscience · 2024Article
- Article
- Spikebench: An open benchmark for spike train time-series classification.PLoS computational biology · 2023Article
- Unsupervised Bayesian Ising Approximation for decoding neural activity and other biological dictionaries.eLife · 2022Article
- Embedding optimization reveals long-lasting history dependence in neural spiking activity.PLoS computational biology · 2021Article
- Modeling a population of retinal ganglion cells with restricted Boltzmann machines.Scientific reports · 2020Article
- Optimal Encoding in Stochastic Latent-Variable Models.Entropy (Basel, Switzerland) · 2020Article
- Insights about collective decision-making at the genetic level.Biophysical reviews · 2020Article
- Clustering of Neural Activity: A Design Principle for Population Codes.Frontiers in computational neuroscience · 2020Article
- Blindfold learning of an accurate neural metric.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Correction: Error-Robust Modes of the Retinal Population Code.PLoS computational biology · 2017Article
- The structured 'low temperature' phase of the retinal population code.PLoS computational biology · 2017Article
- Probabilistic models for neural populations that naturally capture global coupling and criticality.PLoS computational biology · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
Abstract
Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords-collective modes-carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina's output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells' collective signaling is endowed with a form of error-correcting code-a principle that may hold in brain areas beyond retina.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.