December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Neural mechanisms underlying reactivation-induced perceptual learning
Author Affiliations
  • Taly Kondat
    Tel-Aviv University
  • Shachar Gal
    Tel-Aviv University
  • Haggai Sharon
    Tel Aviv Sourasky Medical Center
  • Ido Tavor
    Tel-Aviv University
  • Nitzan Censor
    Tel-Aviv University
Journal of Vision December 2022, Vol.22, 3208. doi:https://doi.org/10.1167/jov.22.14.3208
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      Taly Kondat, Shachar Gal, Haggai Sharon, Ido Tavor, Nitzan Censor; Neural mechanisms underlying reactivation-induced perceptual learning. Journal of Vision 2022;22(14):3208. https://doi.org/10.1167/jov.22.14.3208.

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

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Abstract

The common practice-makes-perfect dogma as a unitary form of procedural learning has recently been challenged: adapting memory reactivation-reconsolidation frameworks, we showed that brief reactivations of an encoded visual skill memory are sufficient to improve human perceptual thresholds (Amar-Halpert et al., 2017). What are the underlying mechanisms of reactivation-induced perceptual learning? To address this question, we had participants perform a standard texture discrimination task (TDT) (Karni and Sagi, 1991). The memory was first encoded and consolidated on a Day1 standard session (252 trials), during which the discrimination threshold was measured. Participants then returned for three sessions on separate days, during which the encoded memory was reactivated with only five near-threshold reminder trials (Reactivation group). An additional group of subjects performed full standard daily sessions (Full-Practice group). A standard retest session was performed on Day5 to measure the final discrimination thresholds. Task-based fMRI was measured on Day1 and Day5 before the standard TDT session. Preliminary results show that both groups exhibited significant and comparable learning. Following practice, there were reduced activations in the intra-parietal sulcus (IPS) and the frontal eye-field (FEF) in the Full-Practice compared to the Reactivation group. These results suggest that whereas higher-order regions are involved in performing the task pre-learning, their engagement is reduced with repeated practice, but persists following reactivation-induced learning. Such persistence of higher-order regions may suggest that reactivation-induced learning is beneficial not only by minimizing practice duration but also in its potential for learning generalization.

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