Constructing the hierarchy of predictive auditory sequences in the marmoset brain
- Chinese Academy of Sciences, China
- Center for Brain Science, RIKEN, Japan
Abstract
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 g and top-down b 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.
Data availability
The fMRI and ECoG data that support the findings of this study are publicly available in Dryad: Jiang, Yuwei (2021), Constructing the hierarchy of predictive auditory sequences in the marmoset brain, Dryad, Dataset, https://doi.org/10.5061/dryad.j3tx95xfp.
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Data from: Constructing the hierarchy of predictive auditory sequences in the marmoset brainDryad Digital Repository, doi:10.5061/dryad.j3tx95xfp.
Article and author information
Author details
Funding
National Science and Technology Innovation 2030 Major Program (2021ZD0204102)
- Liping Wang
Youth Innovation Promotion Association Chinese Academy of Sciences
- Yuwei Jiang
Brain/MINDS from the Japan Agency for Medical Research and Development (JP20dm0207069)
- Misako Komatsu
JSPS KAKENHI (JP19H04993)
- Misako Komatsu
Strategic Priority Research Program (XDB32070201)
- Liping Wang
Strategic Priority Research Program (XDB32030100)
- Liping Wang
Strategic Priority Research Program (XDBS01030100)
- Zhifeng Liang
Pioneer Hundreds of Talents Program from the Chinese Academy of Sciences
- Zhifeng Liang
- Liping Wang
Shanghai Municipal Science and Technology Major Project (2018SHZDZX05)
- Liping Wang
Shanghai Municipal Science and Technology Major Project (2018SHZDZX05)
- Zhifeng Liang
National Natural Science Foundation of China (81801354)
- Zhifeng Liang
National Natural Science Foundation of China (31900797)
- Yuwei Jiang
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: The protocol of the fMRI study was approved by the Ethical Committee of the Institute of Neuroscience, Chinese Academy of Sciences (no. ION-20180522). All procedures of the ECoG study were conducted in accordance with a protocol approved by the RIKEN Ethical Committee [no. W2020-2-008(2)].
Copyright
© 2022, Jiang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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