ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2024
Long-Horizon Associative Learning Explains Human Sensitivity to Statistical and Network Structures in Auditory Sequences.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Sensory integration, temporal prediction, and rule discovery reflect interdependent inference processes.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Article
- The Effect of Previously Encountered Sensory Information on Neural Representations of Predictability: Evidence From Human EEG.The European journal of neuroscience · 2025Article
- Article
- The role of conscious attention in auditory statistical learning: Evidence from patients with impaired consciousness.iScience · 2025Article
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Authors and funding
5 authors at 1 institution in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Networks are a useful mathematical tool for capturing the complexity of the world. In a previous behavioral study, we showed that human adults were sensitive to the high-level network structure underlying auditory sequences, even when presented with incomplete information. Their performance was best explained by a mathematical model compatible with associative learning principles, based on the integration of the transition probabilities between adjacent and nonadjacent elements with a memory decay. In the present study, we explored the neural correlates of this hypothesis via magnetoencephalography (MEG). Participants (
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