Constructing the hierarchy of predictive auditory sequences in the marmoset brain
Our brains constantly generate predictions of sensory input that are compared with actual inputs, propagate the prediction-errors through a hierarchy of brain regions, and subsequently update the internal predictions of the world. However, the essential feature of predictive coding, the notion of hi...
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2022-02-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/74653 |
| _version_ | 1811205266104909824 |
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| author | Yuwei Jiang Misako Komatsu Yuyan Chen Ruoying Xie Kaiwei Zhang Ying Xia Peng Gui Zhifeng Liang Liping Wang |
| author_facet | Yuwei Jiang Misako Komatsu Yuyan Chen Ruoying Xie Kaiwei Zhang Ying Xia Peng Gui Zhifeng Liang Liping Wang |
| author_sort | Yuwei Jiang |
| collection | DOAJ |
| description | Our brains constantly generate predictions of sensory input that are compared with actual inputs, propagate the prediction-errors through a hierarchy of brain regions, and subsequently update the internal predictions of the world. However, the essential feature of predictive coding, the notion of hierarchical depth and its neural mechanisms, remains largely unexplored. Here, we investigated the hierarchical depth of predictive auditory processing by combining functional magnetic resonance imaging (fMRI) and high-density whole-brain electrocorticography (ECoG) in marmoset monkeys during an auditory local-global paradigm in which the temporal regularities of the stimuli were designed at two hierarchical levels. The prediction-errors and prediction updates were examined as neural responses to auditory mismatches and omissions. Using fMRI, we identified a hierarchical gradient along the auditory pathway: midbrain and sensory regions represented local, shorter-time-scale predictive processing followed by associative auditory regions, whereas anterior temporal and prefrontal areas represented global, longer-time-scale sequence processing. The complementary ECoG recordings confirmed the activations at cortical surface areas and further differentiated the signals of prediction-error and update, which were transmitted via putative bottom-up γ and top-down β oscillations, respectively. Furthermore, omission responses caused by absence of input, reflecting solely the two levels of prediction signals that are unique to the hierarchical predictive coding framework, demonstrated the hierarchical top-down process of predictions in the auditory, temporal, and prefrontal areas. Thus, our findings support the hierarchical predictive coding framework, and outline how neural networks and spatiotemporal dynamics are used to represent and arrange a hierarchical structure of auditory sequences in the marmoset brain. |
| first_indexed | 2024-04-12T03:27:54Z |
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| institution | Directory Open Access Journal |
| issn | 2050-084X |
| language | English |
| last_indexed | 2024-04-12T03:27:54Z |
| publishDate | 2022-02-01 |
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| series | eLife |
| spelling | doaj.art-fd67234748ce4b65a3a6d06e5402a8bf2022-12-22T03:49:37ZengeLife Sciences Publications LtdeLife2050-084X2022-02-011110.7554/eLife.74653Constructing the hierarchy of predictive auditory sequences in the marmoset brainYuwei Jiang0https://orcid.org/0000-0002-9533-0760Misako Komatsu1https://orcid.org/0000-0003-4464-4484Yuyan Chen2Ruoying Xie3Kaiwei Zhang4Ying Xia5Peng Gui6Zhifeng Liang7https://orcid.org/0000-0003-2758-1194Liping Wang8https://orcid.org/0000-0003-2038-0234Institute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaLaboratory for Molecular Analysis of Higher Brain Function, Center for Brain Science, RIKEN, Saitama, JapanInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaInstitute of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, ChinaOur brains constantly generate predictions of sensory input that are compared with actual inputs, propagate the prediction-errors through a hierarchy of brain regions, and subsequently update the internal predictions of the world. However, the essential feature of predictive coding, the notion of hierarchical depth and its neural mechanisms, remains largely unexplored. Here, we investigated the hierarchical depth of predictive auditory processing by combining functional magnetic resonance imaging (fMRI) and high-density whole-brain electrocorticography (ECoG) in marmoset monkeys during an auditory local-global paradigm in which the temporal regularities of the stimuli were designed at two hierarchical levels. The prediction-errors and prediction updates were examined as neural responses to auditory mismatches and omissions. Using fMRI, we identified a hierarchical gradient along the auditory pathway: midbrain and sensory regions represented local, shorter-time-scale predictive processing followed by associative auditory regions, whereas anterior temporal and prefrontal areas represented global, longer-time-scale sequence processing. The complementary ECoG recordings confirmed the activations at cortical surface areas and further differentiated the signals of prediction-error and update, which were transmitted via putative bottom-up γ and top-down β oscillations, respectively. Furthermore, omission responses caused by absence of input, reflecting solely the two levels of prediction signals that are unique to the hierarchical predictive coding framework, demonstrated the hierarchical top-down process of predictions in the auditory, temporal, and prefrontal areas. Thus, our findings support the hierarchical predictive coding framework, and outline how neural networks and spatiotemporal dynamics are used to represent and arrange a hierarchical structure of auditory sequences in the marmoset brain.https://elifesciences.org/articles/74653predictive codingauditory sequencemarmosetfunctional magnetic resonance imagingelectrocorticography |
| spellingShingle | Yuwei Jiang Misako Komatsu Yuyan Chen Ruoying Xie Kaiwei Zhang Ying Xia Peng Gui Zhifeng Liang Liping Wang Constructing the hierarchy of predictive auditory sequences in the marmoset brain eLife predictive coding auditory sequence marmoset functional magnetic resonance imaging electrocorticography |
| title | Constructing the hierarchy of predictive auditory sequences in the marmoset brain |
| title_full | Constructing the hierarchy of predictive auditory sequences in the marmoset brain |
| title_fullStr | Constructing the hierarchy of predictive auditory sequences in the marmoset brain |
| title_full_unstemmed | Constructing the hierarchy of predictive auditory sequences in the marmoset brain |
| title_short | Constructing the hierarchy of predictive auditory sequences in the marmoset brain |
| title_sort | constructing the hierarchy of predictive auditory sequences in the marmoset brain |
| topic | predictive coding auditory sequence marmoset functional magnetic resonance imaging electrocorticography |
| url | https://elifesciences.org/articles/74653 |
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