ArticlePLoS computational biology2019
Predicting neuronal dynamics with a delayed gain control model.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Model-based estimation of the population contrast response function in human visual cortex.Journal of vision · 2026Article
- Dissociating stimulus encoding and task demands in ECoG responses from human visual cortex.bioRxiv : the preprint server for biology · 2026Article
- A dynamic spatiotemporal normalization model captures perceptual and neural effects of spatial and temporal context.PLoS biology · 2025Article
- Perceptual Support for Temporal Normalization Across Hundreds of Milliseconds.bioRxiv : the preprint server for biology · 2025Article
- Early visual signatures and benefits of intra-saccadic motion streaks.PLoS computational biology · 2025Article
- Delayed Accumulation of Inhibitory Input Explains Gamma Frequency Variation with Changing Contrast in an Inhibition Stabilized Network.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Fast neural population dynamics in primate V1 captured by a genetically-encoded voltage indicator.Research square · 2025Article
- Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields.Nature communications · 2024Article
- Disparate nonlinear neural dynamics measured with different techniques in macaque and human V1.Scientific reports · 2024Article
- Article
- Temporal dynamics of short-term neural adaptation across human visual cortex.PLoS computational biology · 2024Article
- Article
- Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields.bioRxiv : the preprint server for biology · 2024Article
- Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- NEURAL CORRELATES OF PERCEPTUAL SIMILARITY MASKING IN PRIMATE V1.bioRxiv : the preprint server for biology · 2023Article
- Temporal dynamics of normalization reweighting.Journal of vision · 2023Article
- A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets.eLife · 2021Article
- Effect of Cross-Orientation Normalization on Different Neural Measures in Macaque Primary Visual Cortex.Cerebral cortex communications · 2021Article
- Diverse Temporal Dynamics of Repetition Suppression Revealed by Intracranial Recordings in the Human Ventral Temporal Cortex.Cerebral cortex (New York, N.Y. : 1991) · 2020Article
- Interaction between steady-state visually evoked potentials at nearby flicker frequencies.Scientific reports · 2020Article
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4 authors.
Funding
Abstract
Visual neurons respond to static images with specific dynamics: neuronal responses sum sub-additively over time, reduce in amplitude with repeated or sustained stimuli (neuronal adaptation), and are slower at low stimulus contrast. Here, we propose a simple model that predicts these seemingly disparate response patterns observed in a diverse set of measurements-intracranial electrodes in patients, fMRI, and macaque single unit spiking. The model takes a time-varying contrast time course of a stimulus as input, and produces predicted neuronal dynamics as output. Model computation consists of linear filtering, expansive exponentiation, and a divisive gain control. The gain control signal relates to but is slower than the linear signal, and this delay is critical in giving rise to predictions matched to the observed dynamics. Our model is simpler than previously proposed related models, and fitting the model to intracranial EEG data uncovers two regularities across human visual field maps: estimated linear filters (temporal receptive fields) systematically differ across and within visual field maps, and later areas exhibit more rapid and substantial gain control. The model is further generalizable to account for dynamics of contrast-dependent spike rates in macaque V1, and amplitudes of fMRI BOLD in human V1.
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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.