ArticleNature neuroscience2023
Multilevel visual motion opponency in Drosophila.
Article in Nature neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Connectomes: a re-emerging hub dataset for neuroscience.Frontiers in neuroscience · 2026Review
- Convergence-divergence circuits for multimodal integration of innate and learned opponent valences.Frontiers in systems neuroscience · 2026Article
- On analogies in vertebrate and insect visual systems.Nature reviews. Neuroscience · 2025Review
- Correlative light and electron microscopy reveals the fine circuit structure underlying evidence accumulation in larval zebrafish.bioRxiv : the preprint server for biology · 2025Article
- A competitive disinhibitory network for robust optic flow processing in Drosophila.Nature neuroscience · 2025Article
- Article
- Neuronal wiring diagram of an adult brain.Nature · 2024Article
- Article
- Neuronal "parts list" and wiring diagram for a visual system.bioRxiv : the preprint server for biology · 2024Article
- Biased cell adhesion organizes a circuit for visual motion integration.bioRxiv : the preprint server for biology · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
Inhibitory interactions between opponent neuronal pathways constitute a common circuit motif across brain areas and species. However, in most cases, synaptic wiring and biophysical, cellular and network mechanisms generating opponency are unknown. Here, we combine optogenetics, voltage and calcium imaging, connectomics, electrophysiology and modeling to reveal multilevel opponent inhibition in the fly visual system. We uncover a circuit architecture in which a single cell type implements direction-selective, motion-opponent inhibition at all three network levels. This inhibition, mediated by GluClα receptors, is balanced with excitation in strength, despite tenfold fewer synapses. The different opponent network levels constitute a nested, hierarchical structure operating at increasing spatiotemporal scales. Electrophysiology and modeling suggest that distributing this computation over consecutive network levels counteracts a reduction in gain, which would result from integrating large opposing conductances at a single instance. We propose that this neural architecture provides resilience to noise while enabling high selectivity for relevant sensory information.
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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.