ArticlePLoS computational biology2015
High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 69 citations in OpenAlex.
- Attention maps reveal stimulus-dependent retinal population codes.Frontiers in computational neuroscience · 2026Article
- Information transfer and recovery for the sense of touch.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Retinal ganglion cells encode the direction of motion outside their classical receptive field.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Decoding dynamic visual scenes across the brain hierarchy.PLoS computational biology · 2024Article
- Article
- Linear Response of General Observables in Spiking Neuronal Network Models.Entropy (Basel, Switzerland) · 2021Article
- Modeling a population of retinal ganglion cells with restricted Boltzmann machines.Scientific reports · 2020Article
- What the salamander eye has been telling the vision scientist's brain.Seminars in cell & developmental biology · 2020Review
- Neural variability determines coding strategies for natural self-motion in macaque monkeys.eLife · 2020Article
- Global Motion Processing by Populations of Direction-Selective Retinal Ganglion Cells.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
- Towards optogenetic vision restoration with high resolution.PLoS computational biology · 2020Article
- Estimating information in time-varying signals.PLoS computational biology · 2019Article
- Evolutionary aspects of reservoir computing.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Review
- Article
- Article
- Nonlinear decoding of a complex movie from the mammalian retina.PLoS computational biology · 2018Article
- Blindfold learning of an accurate neural metric.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Learning to make external sensory stimulus predictions using internal correlations in populations of neurons.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Clinical Impact of Spontaneous Hyperactivity in Degenerating Retinas: Significance for Diagnosis, Symptoms, and Treatment.Frontiers in cellular neuroscience · 2018Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
Abstract
Motion tracking is a challenge the visual system has to solve by reading out the retinal population. It is still unclear how the information from different neurons can be combined together to estimate the position of an object. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bar's position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. We then took advantage of this unprecedented precision to explore the spatial structure of the retina's population code. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar's position. Instead, we found that most ganglion cells in the salamander fired sparsely and idiosyncratically, so that their neural image did not track the bar. Furthermore, ganglion cell activity spanned an area much larger than predicted by their receptive fields, with cells coding for motion far in their surround. As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision. This organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.