ArticleScientific reports2025
Direct brain recordings reveal implicit encoding of structure in random auditory streams.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Natural auditory behaviors invoke cognitive brain networks.Current opinion in neurobiology · 2026Review
- Human hippocampal ripples tune cortical responses based on predicted uncertainty.Nature neuroscience · 2026Article
- Continuous Theta Burst to Supplementary Motor Area Modulates Groove.Annals of the New York Academy of Sciences · 2026Article
- Neuronal mismatch responses to auditory stimuli in the dorsal hippocampus of anesthetized rats.Communications biology · 2025Article
- 4/4 and more, rhythmic complexity more strongly predicts groove in common meters.Communications psychology · 2025Article
- The hearing hippocampus.Progress in neurobiology · 2022Review
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Authors and funding
11 authors.
Funding
Abstract
The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where such modeling proceeds is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of the temporal structure of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain automatically and continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Our work provides a comprehensive picture of the neural correlates of automatic encoding of implicit structure that can be the crucial substrate for the swift detection of patterns and unexpected events in the environment.
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