ReviewProgress in retinal and eye research2013
Retinal connectomics: towards complete, accurate networks.
Review in Progress in retinal and eye research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 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
45 citing papers in PubMed, 91 citations in OpenAlex.
- Synaptic Organization of the Primate Retina: Toward a Human Foveal Connectome.Annual review of vision science · 2026Review
- Eyewire II - A connectomic resource for resolving cell types and circuits of the mouse retina.bioRxiv : the preprint server for biology · 2026Article
- The mysterious middlemen making your vision pop: understanding the function of amacrine cells.The Journal of physiology · 2025Review
- The structure, function, and distribution of gap junctions in the retina: Life cycle in health and disease.Journal of cell communication and signaling · 2025Review
- Nitric oxide modulates contrast suppression in a subset of mouse retinal ganglion cells.eLife · 2025Article
- Morphology and Fractal-Based Classifications of Neurons and Microglia in Two and Three Dimensions.Advances in neurobiology · 2024Review
- Spatial Cluster Patterns of Retinal Sensitivity Loss in Intermediate Age-Related Macular Degeneration Features.Translational vision science & technology · 2023Article
- Distinctive synaptic structural motifs link excitatory retinal interneurons to diverse postsynaptic partner types.Cell reports · 2023Article
- Retinal Pathoconnectomics: A Window into Neurodegeneration.Advances in experimental medicine and biology · 2023Article
- Impact of Retinal Degeneration on Response of ON and OFF Cone Bipolar Cells to Electrical Stimulation.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2023Article
- Review
- Dissecting cascade computational components in spiking neural networks.PLoS computational biology · 2021Article
- Model-based comparison of current flow in rod bipolar cells of healthy and early-stage degenerated retina.Experimental eye research · 2021Article
- An Update on Connexin Gap Junction and Hemichannels in Diabetic Retinopathy.International journal of molecular sciences · 2021Review
- A pathoconnectome of early neurodegeneration: Network changes in retinal degeneration.Experimental eye research · 2020Article
- Network Architecture of Gap Junctional Coupling among Parallel Processing Channels in the Mammalian Retina.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
- Stimulus waveform design for decreasing charge and increasing stimulation selectivity in retinal prostheses.Healthcare technology letters · 2020Article
- Optic cup morphogenesis requires neural crest-mediated basement membrane assembly.Development (Cambridge, England) · 2020Article
- Persistent remodeling and neurodegeneration in late-stage retinal degeneration.Progress in retinal and eye research · 2020Review
- Application of machine learning in ophthalmic imaging modalities.Eye and vision (London, England) · 2020Review
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 1 institution in 1 country.
Funding
Abstract
Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 10(12)-10(15) byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies of complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication.
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.