IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1011283.html
   My bibliography  Save this article

Continuous action with a neurobiologically inspired computational approach reveals the dynamics of selection history

Author

Listed:
  • Mukesh Makwana
  • Fan Zhang
  • Dietmar Heinke
  • Joo-Hyun Song

Abstract

Everyday perception-action interaction often requires selection of a single goal from multiple possibilities. According to a recent framework of attentional control, object selection is guided not only by the well-established factors of perceptual salience and current goals but also by selection history. Yet, underlying mechanisms linking selection history and visually-guided actions are poorly understood. To examine such interplay and disentangle the impact of target and distractor history on action selection, we employed a priming-of-popout (PoP) paradigm combined with continuous tracking of reaching movements and computational modeling. Participants reached an odd-colored target among homogeneous distractors while we systematically manipulated the sequence of target and distractor colors from one trial to the next. We observed that current reach movements were significantly influenced by the interaction between attraction by the prior target feature and repulsion by the prior distractor feature. With principal component regression, we found that inhibition led by prior distractors influenced reach target selection earlier than facilitation led by the prior target. In parallel, our newly developed computational model validated that current reach target selection can be explained best by the mechanism postulating the preceded impact of previous distractors followed by a previous target. Such converging empirical and computational evidence suggests that the prior selection history triggers a dynamic interplay between target facilitation and distractor inhibition to guide goal-directed action successfully. This, in turn, highlights the necessity of an explicitly integrated approach to determine how visual attentional selection links with adaptive actions in a complex environment.Author summary: Most real-world visual scenes are complex and crowded, where multiple objects compete for attention and goal-directed action. The interactions between mechanisms of attentional selection and action selection are at the root of many complex behaviors. However, their link has been understudied. To examine this interplay and disentangle the impact of target and distractor history on action selection, we employed a priming-of-popout (PoP) paradigm combined with continuous tracking of reaching movements and computational modeling. This integrated approach constitutes a significant departure from existing practice, where attention and action selection mechanisms are typically investigated separately. Our converging evidence supports the notion that prior selection history triggers a dynamic interplay between target facilitation and distractor inhibition to guide goal-directed action successfully. This finding highlights the necessity of an explicitly integrated approach to determine how visual attentional selection links with adaptive actions in complex environments. Taken together, our study provides valuable insights into the mechanisms underlying attentional selection and action selection, and has important implications for future research in this field.

Suggested Citation

  • Mukesh Makwana & Fan Zhang & Dietmar Heinke & Joo-Hyun Song, 2023. "Continuous action with a neurobiologically inspired computational approach reveals the dynamics of selection history," PLOS Computational Biology, Public Library of Science, vol. 19(7), pages 1-20, July.
  • Handle: RePEc:plo:pcbi00:1011283
    DOI: 10.1371/journal.pcbi.1011283
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011283
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1011283&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1011283?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
    ---><---

    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:plo:pcbi00:1011283. 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: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    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.