ReviewBiological cybernetics2008
Modeling convergent ON and OFF pathways in the early visual system.
Review in Biological cybernetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed.
- A standard model for the vertebrate retina.Vision research · 2026Article
- Filter-based models of suppression in retinal ganglion cells: Comparison and generalization across species and stimuli.PLoS computational biology · 2025Article
- An actor-model framework for visual sensory encoding.Nature communications · 2024Article
- Article
- Model-Based Approach Shows ON Pathway Afferents Elicit a Transient Decrease of V1 Responses.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Simple model for encoding natural images by retinal ganglion cells with nonlinear spatial integration.PLoS computational biology · 2022Article
- What the salamander eye has been telling the vision scientist's brain.Seminars in cell & developmental biology · 2020Review
- New Features of Receptive Fields in Mouse Retina through Spike-triggered Covariance.Experimental neurobiology · 2020Article
- From deep learning to mechanistic understanding in neuroscience: the structure of retinal prediction.Advances in neural information processing systems · 2019Article
- Functional characterization of retinal ganglion cells using tailored nonlinear modeling.Scientific reports · 2019Article
- The dynamic receptive fields of retinal ganglion cells.Progress in retinal and eye research · 2018Review
- Multiplexed computations in retinal ganglion cells of a single type.Nature communications · 2017Article
- Rapid and coordinated processing of global motion images by local clusters of retinal ganglion cells.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2017Article
- Neurons in primary visual cortex represent distribution of luminance.Physiological reports · 2016Article
- Analysis of Neuronal Spike Trains, Deconstructed.Neuron · 2016Review
- Neural correlations enable invariant coding and perception of natural stimuli in weakly electric fish.eLife · 2016Article
- Electrosensory Midbrain Neurons Display Feature Invariant Responses to Natural Communication Stimuli.PLoS computational biology · 2015Article
- Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina.PLoS computational biology · 2015Article
- Ambient illumination switches contrast preference of specific retinal processing streams.Journal of neurophysiology · 2015Article
- The neural circuit mechanisms underlying the retinal response to motion reversal.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
For understanding the computation and function of single neurons in sensory systems, one needs to investigate how sensory stimuli are related to a neuron's response and which biological mechanisms underlie this relationship. Mathematical models of the stimulus-response relationship have proved very useful in approaching these issues in a systematic, quantitative way. A starting point for many such analyses has been provided by phenomenological "linear-nonlinear" (LN) models, which comprise a linear filter followed by a static nonlinear transformation. The linear filter is often associated with the neuron's receptive field. However, the structure of the receptive field is generally a result of inputs from many presynaptic neurons, which may form parallel signal processing pathways. In the retina, for example, certain ganglion cells receive excitatory inputs from ON-type as well as OFF-type bipolar cells. Recent experiments have shown that the convergence of these pathways leads to intriguing response characteristics that cannot be captured by a single linear filter. One approach to adjust the LN model to the biological circuit structure is to use multiple parallel filters that capture ON and OFF bipolar inputs. Here, we review these new developments in modeling neuronal responses in the early visual system and provide details about one particular technique for obtaining the required sets of parallel filters from experimental data.
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.