IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v12y2021i1d10.1038_s41467-021-25436-3.html
   My bibliography  Save this article

Stimulus-dependent representational drift in primary visual cortex

Author

Listed:
  • Tyler D. Marks

    (University of California)

  • Michael J. Goard

    (University of California
    University of California
    University of California)

Abstract

To produce consistent sensory perception, neurons must maintain stable representations of sensory input. However, neurons in many regions exhibit progressive drift across days. Longitudinal studies have found stable responses to artificial stimuli across sessions in visual areas, but it is unclear whether this stability extends to naturalistic stimuli. We performed chronic 2-photon imaging of mouse V1 populations to directly compare the representational stability of artificial versus naturalistic visual stimuli over weeks. Responses to gratings were highly stable across sessions. However, neural responses to naturalistic movies exhibited progressive representational drift across sessions. Differential drift was present across cortical layers, in inhibitory interneurons, and could not be explained by differential response strength or higher order stimulus statistics. However, representational drift was accompanied by similar differential changes in local population correlation structure. These results suggest representational stability in V1 is stimulus-dependent and may relate to differences in preexisting circuit architecture of co-tuned neurons.

Suggested Citation

  • Tyler D. Marks & Michael J. Goard, 2021. "Stimulus-dependent representational drift in primary visual cortex," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25436-3
    DOI: 10.1038/s41467-021-25436-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-021-25436-3
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-021-25436-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luis M. Franco & Michael J. Goard, 2024. "Differential stability of task variable representations in retrosplenial cortex," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Hannah Muysers & Hung-Ling Chen & Johannes Hahn & Shani Folschweiller & Torfi Sigurdsson & Jonas-Frederic Sauer & Marlene Bartos, 2024. "A persistent prefrontal reference frame across time and task rules," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    3. Zvi N. Roth & Elisha P. Merriam, 2023. "Representations in human primary visual cortex drift over time," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    4. Han Chin Wang & Amy M. LeMessurier & Daniel E. Feldman, 2022. "Tuning instability of non-columnar neurons in the salt-and-pepper whisker map in somatosensory cortex," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    5. Ravi Pancholi & Lauren Ryan & Simon Peron, 2023. "Learning in a sensory cortical microstimulation task is associated with elevated representational stability," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    6. Joel Bauer & Uwe Lewin & Elizabeth Herbert & Julijana Gjorgjieva & Carl E. Schoonover & Andrew J. P. Fink & Tobias Rose & Tobias Bonhoeffer & Mark Hübener, 2024. "Sensory experience steers representational drift in mouse visual cortex," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    7. Christoph Stöckl & Yukun Yang & Wolfgang Maass, 2024. "Local prediction-learning in high-dimensional spaces enables neural networks to plan," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    8. Percy K. Mistry & Anthony Strock & Ruizhe Liu & Griffin Young & Vinod Menon, 2023. "Learning-induced reorganization of number neurons and emergence of numerical representations in a biologically inspired neural network," Nature Communications, Nature, vol. 14(1), pages 1-21, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25436-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.