ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2018
Sleep Strengthens Predictive Sequence Coding.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Sleep and the extraction of hidden regularities: A systematic review and the importance of temporal rules.Sleep medicine reviews · 2019Pooled it
- Probing sensorimotor memory through the human speech-audiomotor system.Journal of neurophysiology · 2025Article
- Consolidation Enhances Sequential Multistep Anticipation but Diminishes Access to Perceptual Features.Psychological science · 2024Article
- Sleep shapes the associative structure underlying pattern completion in multielement event memory.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- What triggers explicit awareness in implicit sequence learning? Implications from theories of consciousness.Psychological research · 2022Review
- Article
- Balancing Prediction and Surprise: A Role for Active Sleep at the Dawn of Consciousness?Frontiers in systems neuroscience · 2021Article
- Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing.Frontiers in human neuroscience · 2021Review
- Mechanisms of systems memory consolidation during sleep.Nature neuroscience · 2019Review
- Updating Internal Cognitive Models during Sleep.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predictive-coding theories assume that perception and action are based on internal models derived from previous experience. Such internal models require selection and consolidation to be stored over time. Sleep is known to support memory consolidation. We hypothesized that sleep supports both consolidation and abstraction of an internal task model that is subsequently used to predict upcoming stimuli. Human subjects (of either sex) were trained on deterministic visual sequences and tested with interleaved deviant stimuli after retention intervals of sleep or wakefulness. Adopting a predictive-coding approach, we found increased prediction strength after sleep, as expressed by increased error rates to deviant stimuli, but fewer errors for the immediately following standard stimuli. Sleep likewise enhanced the formation of an abstract sequence model, independent of the temporal context during training. Moreover, sleep increased confidence for sequence knowledge, reflecting enhanced metacognitive access to the model. Our results suggest that sleep supports the formation of internal models which can be used to predict upcoming events in different contexts.
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