ArticleeLife2023
Hierarchical temporal prediction captures motion processing along the visual pathway.
Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Temporal prediction captures retinal spiking responses across animal species.Nature communications · 2026Article
- Hierarchical recurrent temporal prediction as a model of the mammalian dorsal visual pathway.PLoS computational biology · 2026Article
- The representation of omitted sounds in the mouse auditory cortex.Nature communications · 2026Article
- Self-supervised predictive learning accounts for cortical layer-specificity.Nature communications · 2025Article
- Prediction of future input explains lateral connectivity in primary visual cortex.Current biology : CB · 2025Article
- Poisson Variational Autoencoder.ArXiv · 2024Article
- Predictive coding networks for temporal prediction.PLoS computational biology · 2024Article
- Dynamic predictive coding: A model of hierarchical sequence learning and prediction in the neocortex.PLoS computational biology · 2024Article
- Article
- Local minimization of prediction errors drives learning of invariant object representations in a generative network model of visual perception.Frontiers in computational neuroscience · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Visual neurons respond selectively to features that become increasingly complex from the eyes to the cortex. Retinal neurons prefer flashing spots of light, primary visual cortical (V1) neurons prefer moving bars, and those in higher cortical areas favor complex features like moving textures. Previously, we showed that V1 simple cell tuning can be accounted for by a basic model implementing temporal prediction - representing features that predict future sensory input from past input (Singer et al., 2018). Here, we show that hierarchical application of temporal prediction can capture how tuning properties change across at least two levels of the visual system. This suggests that the brain does not efficiently represent all incoming information; instead, it selectively represents sensory inputs that help in predicting the future. When applied hierarchically, temporal prediction extracts time-varying features that depend on increasingly high-level statistics of the sensory input.
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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.