August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
Non-monotonic plasticity from real-time inception of competition between object representations
Author Affiliations
  • Kailong Peng
    Department of Psychology, Yale University
    Interdepartmental Neuroscience Program, Yale University
  • Jefferey D. Wammes
    Department of Psychology, Queen's University
    Center for Neuroscience Studies, Queen's University
  • Alex Nguyen
    Department of Psychology, Princeton University
    Princeton Neuroscience Institute, Princeton University
  • Marius Cătălin Iordan
    Department of Brain and Cognitive Sciences, University of Rochester
    Department of Neuroscience, University of Rochester
  • Kenneth A. Norman
    Department of Psychology, Princeton University
    Princeton Neuroscience Institute, Princeton University
  • Nicholas B. Turk-Browne
    Department of Psychology, Yale University
    Wu Tsai Institute, Yale University
Journal of Vision August 2023, Vol.23, 5354. doi:
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      Kailong Peng, Jefferey D. Wammes, Alex Nguyen, Marius Cătălin Iordan, Kenneth A. Norman, Nicholas B. Turk-Browne; Non-monotonic plasticity from real-time inception of competition between object representations. Journal of Vision 2023;23(9):5354.

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      © ARVO (1962-2015); The Authors (2016-present)

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When neural representations compete, this can trigger learning processes that act to resolve this competition. The non-monotonic plasticity hypothesis (NMPH) predicts that such competition will alter the relationship between representations according to a U-shaped curve: they integrate when strongly co-activated, differentiate when moderately co-activated, and remain unaffected when weakly co-activated. The NMPH is often tested by quantifying patterns of neural co-activation after the fact. Here, we sought to manipulate and control this co-activation during online perception with real-time fMRI. We used neurofeedback to incept competing object representations at different degrees of co-activation. While viewing a target object (e.g., a bed), we trained participants to activate the neural representation of a competitor object from the same category (e.g., a chair). We performed multivariate pattern analysis in real-time to quantify neural evidence for the competitor relative to other untrained objects from the same category, and this evidence determined the feedback provided. The entire protocol involved five scanning sessions. Sessions 2-4 consisted of multiple runs of neurofeedback, each bookended by a pre- and post-session run without feedback, to estimate the evolving neural representations of the target and competitor objects in each session. Session 1 and 5 allowed us to estimate neural representations before and after the full training protocol. With this multiple session whole-brain approach, we probed for changes in the representational similarity between targets and competitors as a function of the degree of competitor activation that participants achieved with neurofeedback, both within and across sessions. Preliminary results show evidence of non-monotonic changes in multivariate pattern similarity induced by neurofeedback in some areas of the hippocampus, frontal cortex, and visual cortex. These results support the predictions of the NMPH, and also demonstrate the potential of real-time fMRI to induce competition between visual representations and alter their overlap in the brain.


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