1. Neuroscience

Flexing the principal gradient of the cerebral cortex to suit changing semantic task demands

  1. Zhiyao Gao  Is a corresponding author
  2. Li Zheng
  3. Katya Krieger-Redwood
  4. Ajay Halai
  5. Daniel S Margulies
  6. Jonathan Smallwood
  7. Elizabeth Jefferies  Is a corresponding author
  1. University of York, United Kingdom
  2. University of Arizona, United States
  3. University of Cambridge, United Kingdom
  4. Centre National de la Recherche Scientifique, France
  5. Queens University, Canada
https://doi.org/10.7554/eLife.80368
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Cite this article
  1. Zhiyao Gao
  2. Li Zheng
  3. Katya Krieger-Redwood
  4. Ajay Halai
  5. Daniel S Margulies
  6. Jonathan Smallwood
  7. Elizabeth Jefferies
(2022)
Flexing the principal gradient of the cerebral cortex to suit changing semantic task demands
eLife 11:e80368.
https://doi.org/10.7554/eLife.80368
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Abstract

Understanding how thought emerges from the topographical structure of the cerebral cortex is a primary goal of cognitive neuroscience. Recent work has revealed a principal gradient of intrinsic connectivity capturing the separation of sensory-motor cortex from transmodal regions of the default mode network (DMN); this is thought to facilitate memory-guided cognition. However, studies have not explored how this dimension of connectivity changes when conceptual retrieval is controlled to suit the context. We used gradient decomposition of informational connectivity in a semantic association task to establish how the similarity in connectivity across brain regions changes during familiar and more original patterns of retrieval. Multivoxel activation patterns at opposite ends of the principal gradient were more divergent when participants retrieved stronger associations; therefore, when long-term semantic information is sufficient for ongoing cognition, regions supporting heteromodal memory are functionally separated from sensory-motor experience. In contrast, when less related concepts were linked, this dimension of connectivity was reduced in strength as semantic control regions separated from the DMN to generate more flexible and original responses. We also observed fewer dimensions within the neural response towards the apex of the principal gradient when strong associations were retrieved, reflecting less complex or varied neural coding across trials and participants. In this way, the principal gradient explains how semantic cognition is organised in the human cerebral cortex: the separation of DMN from sensory-motor systems is a hallmark of the retrieval of strong conceptual links that are culturally shared.

Data availability

Experiment materials, behavioral data, source data for producing the figures, brain parcellation template, and group-level neuroimaging data (gradient-relevant analysis) are accessible in the Open Science Framework at https://osf.io/mkgcy/.The Neurovault collection provides the processed version of the data set for the other analyses, including neural dimensionality and second-order representational analysis: https://neurovault.org/collections/12539/.I have uploaded all analysis codes and software being used in this study onto osf: https://osf.io/mkgcy/, which include but are not limited to the gradient analysis (Matlab), dimensionality analysis (python), and second-RSA analysis (Matlab).The conditions of our ethical approval do not permit public archiving of the data because participants did not provide sufficient consent for the release of their biomedical data.Researchers who wish to access the data should contact the Research Ethics and Governance Committee of the York Neuroimaging Centre, University of York, or the corresponding authors. Data will be released to researchers when this is possible under the terms of the GDPR (General Data Protection Regulation). The decision as to whether the data can be reused and how access can be provided will be taken by the Research Ethics and Governance Committee of the York Neuroimaging Centre; data access arrangements are likely to exclude commercial use of the data.

Article and author information

Author details

  1. Zhiyao Gao

    Department of Psychology, University of York, York, United Kingdom
    For correspondence
    zhiyao.gao@york.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8909-8096

  2. Li Zheng

    Department of Psychology, University of Arizona, Tucson, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Katya Krieger-Redwood

    Department of Psychology, University of York, York, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  4. Ajay Halai

    MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  5. Daniel S Margulies

    Integrative Neuroscience and Cognition Center (UMR 8002), Centre National de la Recherche Scientifique, Paris, France
    Competing interests
    The authors declare that no competing interests exist.

  6. Jonathan Smallwood

    Department of Psychology, Queens University, Kingston, Canada
    Competing interests
    The authors declare that no competing interests exist.

  7. Elizabeth Jefferies

    Department of Psychology, University of York, York, United Kingdom
    For correspondence
    beth.jefferies@york.ac.uk
    Competing interests
    The authors declare that no competing interests exist.

Funding

European Research Council (771863 - FLEXSEM)

  • Elizabeth Jefferies

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

Ethics

Human subjects: The study was approved by the Research Ethics Committee of the York Neuroimaging Centre (Project number: P1391). All volunteers provided informed written consent and received monetary compensation or course credit for their participation.

Copyright

© 2022, Gao 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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  1. Zhiyao Gao
  2. Li Zheng
  3. Katya Krieger-Redwood
  4. Ajay Halai
  5. Daniel S Margulies
  6. Jonathan Smallwood
  7. Elizabeth Jefferies
(2022)
Flexing the principal gradient of the cerebral cortex to suit changing semantic task demands
eLife 11:e80368.
https://doi.org/10.7554/eLife.80368

Share this article

https://doi.org/10.7554/eLife.80368

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