Predictive learning shapes the representational geometry of the human brain
Abstract Predictive coding theories propose that the brain constantly updates internal models to minimize prediction errors and optimize sensory processing. However, the neural mechanisms that link prediction error encoding and optimization of sensory representations remain unclear. Here, we provide...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-11-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-54032-4 |
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| _version_ | 1846171824985997312 |
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| author | Antonino Greco Julia Moser Hubert Preissl Markus Siegel |
| author_facet | Antonino Greco Julia Moser Hubert Preissl Markus Siegel |
| author_sort | Antonino Greco |
| collection | DOAJ |
| description | Abstract Predictive coding theories propose that the brain constantly updates internal models to minimize prediction errors and optimize sensory processing. However, the neural mechanisms that link prediction error encoding and optimization of sensory representations remain unclear. Here, we provide evidence how predictive learning shapes the representational geometry of the human brain. We recorded magnetoencephalography (MEG) in humans listening to acoustic sequences with different levels of regularity. We found that the brain aligns its representational geometry to match the statistical structure of the sensory inputs, by clustering temporally contiguous and predictable stimuli. Crucially, the magnitude of this representational shift correlates with the synergistic encoding of prediction errors in a network of high-level and sensory areas. Our findings suggest that, in response to the statistical regularities of the environment, large-scale neural interactions engaged in predictive processing modulate the representational content of sensory areas to enhance sensory processing. |
| format | Article |
| id | doaj-art-8bb7868556934a6cb641c33e72aa4c05 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-8bb7868556934a6cb641c33e72aa4c052024-11-10T12:32:26ZengNature PortfolioNature Communications2041-17232024-11-0115111210.1038/s41467-024-54032-4Predictive learning shapes the representational geometry of the human brainAntonino Greco0Julia Moser1Hubert Preissl2Markus Siegel3Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of TübingenIDM/fMEG Center of the Helmholtz Center Munich, University of TübingenIDM/fMEG Center of the Helmholtz Center Munich, University of TübingenDepartment of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of TübingenAbstract Predictive coding theories propose that the brain constantly updates internal models to minimize prediction errors and optimize sensory processing. However, the neural mechanisms that link prediction error encoding and optimization of sensory representations remain unclear. Here, we provide evidence how predictive learning shapes the representational geometry of the human brain. We recorded magnetoencephalography (MEG) in humans listening to acoustic sequences with different levels of regularity. We found that the brain aligns its representational geometry to match the statistical structure of the sensory inputs, by clustering temporally contiguous and predictable stimuli. Crucially, the magnitude of this representational shift correlates with the synergistic encoding of prediction errors in a network of high-level and sensory areas. Our findings suggest that, in response to the statistical regularities of the environment, large-scale neural interactions engaged in predictive processing modulate the representational content of sensory areas to enhance sensory processing.https://doi.org/10.1038/s41467-024-54032-4 |
| spellingShingle | Antonino Greco Julia Moser Hubert Preissl Markus Siegel Predictive learning shapes the representational geometry of the human brain Nature Communications |
| title | Predictive learning shapes the representational geometry of the human brain |
| title_full | Predictive learning shapes the representational geometry of the human brain |
| title_fullStr | Predictive learning shapes the representational geometry of the human brain |
| title_full_unstemmed | Predictive learning shapes the representational geometry of the human brain |
| title_short | Predictive learning shapes the representational geometry of the human brain |
| title_sort | predictive learning shapes the representational geometry of the human brain |
| url | https://doi.org/10.1038/s41467-024-54032-4 |
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