ArticleeLife2018
Adaptive coding for dynamic sensory inference.
Article in eLife, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed.
- Locomotion optimizes sensory representations through a computational principle shared by rodents and primates.Science advances · 2026Article
- Filter, Detector, Predictor: The expanding repertoire of retinal computation in vertebrates.Vision research · 2026Review
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- Computational and Neuronal Basis of Visual Confidence.Annual review of vision science · 2025Review
- The geometry of efficient codes: How rate-distortion trade-offs distort the latent representations of generative models.PLoS computational biology · 2025Article
- Modulation of brain signal variability in visual cortex reflects aging, GABA, and behavior.eLife · 2025Article
- A universal power law optimizes energy and representation fidelity in visual adaptation.bioRxiv : the preprint server for biology · 2025Article
- Foraging animals use dynamic Bayesian updating to model meta-uncertainty in environment representations.PLoS computational biology · 2025Article
- Bayesian inference by visuomotor neurons in the prefrontal cortex.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Single-neuron spiking variability in hippocampus dynamically tracks sensory content during memory formation in humans.Nature communications · 2025Article
- Type-specific molecular signaling architectures and synaptic plasticity ofFrontiers in cellular neuroscience · 2025Article
- Bayesian inference by visuomotor neurons in prefrontal cortex.bioRxiv : the preprint server for biology · 2024Article
- Response Plasticity ofInternational journal of molecular sciences · 2024Article
- A vast space of compact strategies for effective decisions.Science advances · 2024Article
- Encoding surprise by retinal ganglion cells.PLoS computational biology · 2024Article
- Foraging Under Uncertainty Follows the Marginal Value Theorem with Bayesian Updating of Environment Representations.bioRxiv : the preprint server for biology · 2024Article
- Adaptation of the inferior temporal neurons and efficient visual processing.Frontiers in behavioral neuroscience · 2024Review
- Environmental dynamics shape perceptual decision bias.PLoS computational biology · 2023Article
- Adaptation in auditory processing.Physiological reviews · 2023Review
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Behavior relies on the ability of sensory systems to infer properties of the environment from incoming stimuli. The accuracy of inference depends on the fidelity with which behaviorally relevant properties of stimuli are encoded in neural responses. High-fidelity encodings can be metabolically costly, but low-fidelity encodings can cause errors in inference. Here, we discuss general principles that underlie the tradeoff between encoding cost and inference error. We then derive adaptive encoding schemes that dynamically navigate this tradeoff. These optimal encodings tend to increase the fidelity of the neural representation following a change in the stimulus distribution, and reduce fidelity for stimuli that originate from a known distribution. We predict dynamical signatures of such encoding schemes and demonstrate how known phenomena, such as burst coding and firing rate adaptation, can be understood as hallmarks of optimal coding for accurate inference.
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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.