Constructing the hierarchy of predictive auditory sequences in the marmoset brain

  1. Yuwei Jiang
  2. Misako Komatsu
  3. Yuyan Chen
  4. Ruoying Xie
  5. Kaiwei Zhang
  6. Ying Xia
  7. Peng Gui
  8. Zhifeng Liang  Is a corresponding author
  9. Liping Wang  Is a corresponding author
  1. Chinese Academy of Sciences, China
  2. 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.

The following data sets were generated

Article and author information

Author details

  1. Yuwei Jiang

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9533-0760
  2. Misako Komatsu

    Laboratory for Molecular Analysis of Higher Brain Function, Center for Brain Science, RIKEN, Saitama, Japan
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4464-4484
  3. Yuyan Chen

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Ruoying Xie

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Kaiwei Zhang

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Ying Xia

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Peng Gui

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Zhifeng Liang

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    For correspondence
    zliang@ion.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
  9. Liping Wang

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    For correspondence
    lipingwng@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2038-0234

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.

Metrics

  • 2,288
    views
  • 486
    downloads
  • 30
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Yuwei Jiang
  2. Misako Komatsu
  3. Yuyan Chen
  4. Ruoying Xie
  5. Kaiwei Zhang
  6. Ying Xia
  7. Peng Gui
  8. Zhifeng Liang
  9. Liping Wang
(2022)
Constructing the hierarchy of predictive auditory sequences in the marmoset brain
eLife 11:e74653.
https://doi.org/10.7554/eLife.74653

Share this article

https://doi.org/10.7554/eLife.74653

Further reading

    1. Neuroscience
    Lisa Reisinger, Gianpaolo Demarchi ... Nathan Weisz
    Research Article

    Phantom perceptions like tinnitus occur without any identifiable environmental or bodily source. The mechanisms and key drivers behind tinnitus are poorly understood. The dominant framework, suggesting that tinnitus results from neural hyperactivity in the auditory pathway following hearing damage, has been difficult to investigate in humans and has reached explanatory limits. As a result, researchers have tried to explain perceptual and potential neural aberrations in tinnitus within a more parsimonious predictive-coding framework. In two independent magnetoencephalography studies, participants passively listened to sequences of pure tones with varying levels of regularity (i.e. predictability) ranging from random to ordered. Aside from being a replication of the first study, the pre-registered second study, including 80 participants, ensured rigorous matching of hearing status, as well as age, sex, and hearing loss, between individuals with and without tinnitus. Despite some changes in the details of the paradigm, both studies equivalently reveal a group difference in neural representation, based on multivariate pattern analysis, of upcoming stimuli before their onset. These data strongly suggest that individuals with tinnitus engage anticipatory auditory predictions differently to controls. While the observation of different predictive processes is robust and replicable, the precise neurocognitive mechanism underlying it calls for further, ideally longitudinal, studies to establish its role as a potential contributor to, and/or consequence of, tinnitus.

    1. Neuroscience
    Rongxin Fang, Aaron Halpern ... Xiaowei Zhuang
    Tools and Resources

    Multiplexed error-robust fluorescence in situ hybridization (MERFISH) allows genome-scale imaging of RNAs in individual cells in intact tissues. To date, MERFISH has been applied to image thin-tissue samples of ~10 µm thickness. Here, we present a thick-tissue three-dimensional (3D) MERFISH imaging method, which uses confocal microscopy for optical sectioning, deep learning for increasing imaging speed and quality, as well as sample preparation and imaging protocol optimized for thick samples. We demonstrated 3D MERFISH on mouse brain tissue sections of up to 200 µm thickness with high detection efficiency and accuracy. We anticipate that 3D thick-tissue MERFISH imaging will broaden the scope of questions that can be addressed by spatial genomics.