Fine-scale computations for adaptive processing in the human brain

Abstract

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalize on the sub-millimetre resolution of ultra-high field imaging to examine fMRI signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2 and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

Data availability

Source data have been provided for Figures 3, 4, and 5. Data can also be found on the Cambridge Data repository

Article and author information

Author details

  1. Elisa Zamboni

    Psychology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Valentin G Kemper

    Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  3. Nuno Reis Goncalves

    Psychology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Ke Jia

    Psychology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Vasilis M Karlaftis

    Psychology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1285-1593
  6. Samuel J Bell

    Psychology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Joseph Giorgio

    Psychology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Reuben Rideaux

    Psychology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8416-005X
  9. Rainer Goebel

    Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  10. Zoe Kourtzi

    Psychology, University of Cambridge, Cambridge, United Kingdom
    For correspondence
    zk240@cam.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9441-7832

Funding

Biotechnology and Biological Sciences Research Council (H012508)

  • Zoe Kourtzi

Biotechnology and Biological Sciences Research Council (BB/P021255/1)

  • Zoe Kourtzi

Wellcome Trust (205067/Z/16/Z)

  • Zoe Kourtzi

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

Ethics

Human subjects: Participants gave written informed consent. The study was approved by the local Ethical Committee of the Faculty of Psychology and Neuroscience at Maastricht University and the University of Cambridge Ethics Committee (ethics number PRE2018.003).

Copyright

© 2020, Zamboni 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. Elisa Zamboni
  2. Valentin G Kemper
  3. Nuno Reis Goncalves
  4. Ke Jia
  5. Vasilis M Karlaftis
  6. Samuel J Bell
  7. Joseph Giorgio
  8. Reuben Rideaux
  9. Rainer Goebel
  10. Zoe Kourtzi
(2020)
Fine-scale computations for adaptive processing in the human brain
eLife 9:e57637.
https://doi.org/10.7554/eLife.57637

Share this article

https://doi.org/10.7554/eLife.57637

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