Direct brain recordings reveal implicit encoding of structure in random auditory streams
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...
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-98865-5 |
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| author | Julian Fuhrer Kyrre Glette Jugoslav Ivanovic Pål Gunnar Larsson Tristan Bekinschtein Silvia Kochen Robert T. Knight Jim Tørresen Anne-Kristin Solbakk Tor Endestad Alejandro Blenkmann |
| author_facet | Julian Fuhrer Kyrre Glette Jugoslav Ivanovic Pål Gunnar Larsson Tristan Bekinschtein Silvia Kochen Robert T. Knight Jim Tørresen Anne-Kristin Solbakk Tor Endestad Alejandro Blenkmann |
| author_sort | Julian Fuhrer |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e4c157fe717b4b6097d7aa3dbc258052 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e4c157fe717b4b6097d7aa3dbc2580522025-08-20T02:55:21ZengNature PortfolioScientific Reports2045-23222025-04-0115111410.1038/s41598-025-98865-5Direct brain recordings reveal implicit encoding of structure in random auditory streamsJulian Fuhrer0Kyrre Glette1Jugoslav Ivanovic2Pål Gunnar Larsson3Tristan Bekinschtein4Silvia Kochen5Robert T. Knight6Jim Tørresen7Anne-Kristin Solbakk8Tor Endestad9Alejandro Blenkmann10RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of OsloRITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of OsloDepartment of Neurosurgery, Oslo University Hospital, RikshospitaletDepartment of Neurosurgery, Oslo University Hospital, RikshospitaletCambridge Consciousness and Cognition Lab, Department of Psychology, University of CambridgeENyS-CONICET-Univ JauretcheHelen Wills Neuroscience Institute and Department of Psychology, University of CaliforniaRITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of OsloRITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of OsloRITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of OsloRITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of OsloAbstract 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.https://doi.org/10.1038/s41598-025-98865-5Statistical learningPattern detectionPredictive codingHigh-frequency activityMMN |
| spellingShingle | Julian Fuhrer Kyrre Glette Jugoslav Ivanovic Pål Gunnar Larsson Tristan Bekinschtein Silvia Kochen Robert T. Knight Jim Tørresen Anne-Kristin Solbakk Tor Endestad Alejandro Blenkmann Direct brain recordings reveal implicit encoding of structure in random auditory streams Scientific Reports Statistical learning Pattern detection Predictive coding High-frequency activity MMN |
| title | Direct brain recordings reveal implicit encoding of structure in random auditory streams |
| title_full | Direct brain recordings reveal implicit encoding of structure in random auditory streams |
| title_fullStr | Direct brain recordings reveal implicit encoding of structure in random auditory streams |
| title_full_unstemmed | Direct brain recordings reveal implicit encoding of structure in random auditory streams |
| title_short | Direct brain recordings reveal implicit encoding of structure in random auditory streams |
| title_sort | direct brain recordings reveal implicit encoding of structure in random auditory streams |
| topic | Statistical learning Pattern detection Predictive coding High-frequency activity MMN |
| url | https://doi.org/10.1038/s41598-025-98865-5 |
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