ArticleProceedings of the National Academy of Sciences of the United States of America2020
A recurrent circuit implements normalization, simulating the dynamics of V1 activity.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Principles of cortical interactions in modular recurrent networks.bioRxiv : the preprint server for biology · 2026Article
- Neuronal heterogeneity of normalization strength in a circuit model.Science advances · 2026Article
- A dynamic spatiotemporal normalization model captures perceptual and neural effects of spatial and temporal context.PLoS biology · 2025Article
- Article
- Attention-induced perceptual traveling waves in binocular rivalry.Journal of vision · 2025Article
- Spatial attention selectively alters visual cortical representation during target anticipation.Nature communications · 2025Article
- Relating natural image statistics to patterns of response covariability in macaque primary visual cortex.Nature communications · 2025Article
- Hierarchical Neural Circuit Theory of Normalization and Inter-areal Communication.bioRxiv : the preprint server for biology · 2025Article
- Balanced state of networks of winner-take-all units.PLoS computational biology · 2025Article
- Dynamics of energy-efficient coding in visual cortex.Journal of neurophysiology · 2025Article
- Unconditional stability of a recurrent neural circuit implementing divisive normalization.Advances in neural information processing systems · 2024Article
- Contrast gain control is a reparameterization of a population response curve.Journal of neurophysiology · 2024Article
- Contrast gain control is a reparameterization of a population response curve.bioRxiv : the preprint server for biology · 2024Article
- Adult neurogenesis improves spatial information encoding in the mouse hippocampus.Nature communications · 2024Article
- Response sub-additivity and variability quenching in visual cortex.Nature reviews. Neuroscience · 2024Review
- Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns.Nature communications · 2024Article
- On the contrast response function of adapted neural populations.Journal of neurophysiology · 2024Article
- Cellular mechanisms of cooperative context-sensitive predictive inference.Current research in neurobiology · 2024Review
- Normalization by orientation-tuned surround in human V1-V3.PLoS computational biology · 2023Article
- Modeling the diverse effects of divisive normalization on noise correlations.PLoS computational biology · 2023Article
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2 authors.
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Abstract
The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model's defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. Despite the success of the normalization model, there are three unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another's normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can recapitulate key experimental observations of the dynamics of neural activity in V1.
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