ArticleeLife2018
Sensory cortex is optimized for prediction of future input.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 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
- Sequential experience reshapes population representations in visual cortex.bioRxiv : the preprint server for 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
- Recurrent neural networks as neuro-computational models of human speech recognition.PLoS computational biology · 2025Article
- Diversity of omission responses to visual images across brain-wide regions.Science advances · 2025Article
- Prediction of future input explains lateral connectivity in primary visual cortex.Current biology : CB · 2025Article
- TiDHy: Timescale Demixing via Hypernetworks to learn simultaneous dynamics from mixed observations.bioRxiv : the preprint server for biology · 2025Article
- Adaptation optimizes sensory encoding for future stimuli.PLoS computational biology · 2025Article
- Brain-machine convergent evolution: Why finding parallels between brain and artificial systems is informative.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Predictive coding networks for temporal prediction.PLoS computational biology · 2024Article
- A number sense as an emergent property of the manipulating brain.Scientific reports · 2024Article
- Inferring neural activity before plasticity as a foundation for learning beyond backpropagation.Nature neuroscience · 2024Article
- Dynamic predictive coding: A model of hierarchical sequence learning and prediction in the neocortex.PLoS computational biology · 2024Article
- The combination of Hebbian and predictive plasticity learns invariant object representations in deep sensory networks.Nature neuroscience · 2023Article
- Article
- Prediction in cultured cortical neural networks.PNAS nexus · 2023Article
- Omission responses in local field potentials in rat auditory cortex.BMC biology · 2023Article
- A time-causal and time-recursive scale-covariant scale-space representation of temporal signals and past time.Biological cybernetics · 2023Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Neurons in sensory cortex are tuned to diverse features in natural scenes. But what determines which features neurons become selective to? Here we explore the idea that neuronal selectivity is optimized to represent features in the recent sensory past that best predict immediate future inputs. We tested this hypothesis using simple feedforward neural networks, which were trained to predict the next few moments of video or audio in clips of natural scenes. The networks developed receptive fields that closely matched those of real cortical neurons in different mammalian species, including the oriented spatial tuning of primary visual cortex, the frequency selectivity of primary auditory cortex and, most notably, their temporal tuning properties. Furthermore, the better a network predicted future inputs the more closely its receptive fields resembled those in the brain. This suggests that sensory processing is optimized to extract those features with the most capacity to predict future 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.