Neural underpinning of a respiration-associated resting-state fMRI network

  1. Wenyu Tu
  2. Nanyin Zhang  Is a corresponding author
  1. Pennsylvania State University, United States

Abstract

Respiration can induce motion and CO2 fluctuation during resting-state fMRI (rsfMRI) scans, which will lead to non-neural artifacts in the rsfMRI signal. In the meantime, as a crucial physiologic process, respiration that can directly drive neural activity change in the brain, and may thereby modulate the rsfMRI signal. Nonetheless, this potential neural component in the respiration-fMRI relationship is largely unexplored. To elucidate this issue, here we simultaneously recorded the electrophysiology, rsfMRI and respiration signals in rats. Our data show that respiration is indeed associated with neural activity changes, evidenced by a phase-locking relationship between slow respiration variations and the gamma-band power of the electrophysiologic signal recorded in the anterior cingulate cortex. Intriguingly, slow respiration variations are also linked to a characteristic rsfMRI network, which is mediated by gamma-band neural activity. In addition, this respiration-related brain network disappears when brain-wide neural activity is silenced at an iso-electrical state, while the respiration is maintained, further confirming the necessary role of neural activity in this network. Taken together, this study identifies a respiration-related brain network underpinned by neural activity, which represents a novel component in the respiration-rsfMRI relationship that is distinct from respiration-related rsfMRI artifacts. It opens a new avenue for investigating the interactions between respiration, neural activity and resting-state brain networks in both healthy and diseased conditions.

Data availability

All data for this study have been deposited to NITRIC repository.

The following data sets were generated
    1. Tu W
    2. Zhang
    3. N
    (2022) Electrophysiology, resting state fMRI and respiration in rats
    NeuroImaging Tools and Resources Collaboratory (NITRC), https://www.nitrc.org/docman/?group_id=1582.

Article and author information

Author details

  1. Wenyu Tu

    The Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Nanyin Zhang

    Department of Biomedical Engineering, Pennsylvania State University, University Park, United States
    For correspondence
    nuz2@psu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5824-9058

Funding

National Institute of Neurological Disorders and Stroke (R01NS085200)

  • Nanyin Zhang

National Institute of Mental Health (RF1MH114224)

  • Nanyin Zhang

National Institute of General Medical Sciences (R01GM141792)

  • Nanyin Zhang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Karla L Miller, University of Oxford, United Kingdom

Ethics

Animal experimentation: The present study was approved by the Pennsylvania State University Institutional Animal Care and Use Committee (IACUC) with the protocol number of PRAMS201343583.

Version history

  1. Received: July 1, 2022
  2. Preprint posted: July 13, 2022 (view preprint)
  3. Accepted: October 13, 2022
  4. Accepted Manuscript published: October 20, 2022 (version 1)
  5. Version of Record published: November 9, 2022 (version 2)

Copyright

© 2022, Tu & Zhang

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

  • 2,841
    views
  • 423
    downloads
  • 14
    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. Wenyu Tu
  2. Nanyin Zhang
(2022)
Neural underpinning of a respiration-associated resting-state fMRI network
eLife 11:e81555.
https://doi.org/10.7554/eLife.81555

Share this article

https://doi.org/10.7554/eLife.81555

Further reading

    1. Neuroscience
    Kenta Abe, Yuki Kambe ... Tatsuo Sato
    Research Article

    Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing. By optimizing microprism-mediated two-photon calcium imaging of dopamine axon terminals, we found diverse activity in dopamine axons responsive to both reward and aversive stimuli. Some axons exhibited a preference for reward, while others favored aversive stimuli, and there was a strong bias for the latter at the population level. Long-term longitudinal imaging revealed that the preference was maintained in reward- and aversive-preferring axons throughout classical conditioning in which rewarding and aversive stimuli were paired with preceding auditory cues. However, as mice learned to discriminate reward or aversive cues, a cue activity preference gradually developed only in aversive-preferring axons. We inferred the trial-by-trial cue discrimination based on machine learning using anticipatory licking or facial expressions, and found that successful discrimination was accompanied by sharper selectivity for the aversive cue in aversive-preferring axons. Our findings indicate that a group of mesocortical dopamine axons encodes aversive-related signals, which are modulated by both classical conditioning across days and trial-by-trial discrimination within a day.

    1. Neuroscience
    Baiwei Liu, Zampeta-Sofia Alexopoulou, Freek van Ede
    Research Article

    Working memory enables us to bridge past sensory information to upcoming future behaviour. Accordingly, by its very nature, working memory is concerned with two components: the past and the future. Yet, in conventional laboratory tasks, these two components are often conflated, such as when sensory information in working memory is encoded and tested at the same location. We developed a task in which we dissociated the past (encoded location) and future (to-be-tested location) attributes of visual contents in working memory. This enabled us to independently track the utilisation of past and future memory attributes through gaze, as observed during mnemonic selection. Our results reveal the joint consideration of past and future locations. This was prevalent even at the single-trial level of individual saccades that were jointly biased to the past and future. This uncovers the rich nature of working memory representations, whereby both past and future memory attributes are retained and can be accessed together when memory contents become relevant for behaviour.