September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Low-level object properties impact memory reconsolidation
Author Affiliations & Notes
  • Jean-Maxime Larouche
    Department of Psychology, University of Montreal
  • Frederic Gosselin
    Department of Psychology, University of Montreal
Journal of Vision September 2019, Vol.19, 39a. doi:https://doi.org/10.1167/19.10.39a
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      Jean-Maxime Larouche, Frederic Gosselin; Low-level object properties impact memory reconsolidation. Journal of Vision 2019;19(10):39a. https://doi.org/10.1167/19.10.39a.

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

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Abstract

When a consolidated memory is reactivated, it becomes unstable and can be modified before being reconsolidated (e.g. Schiller & Phelps 2011; Elsey, Van Ast et al., 2018). In the new learning paradigm—the most commonly used in human studies of memory reconsolidation— a new learning interferes with an old one when learned as long as a 6 hours after the reminder of the old learning (Nader et al., 2000). This interference increases with the similarity between old and new learning sets on a number of high-level attributes (for a review, see Crowder, 2014). Here, we tested for the first time if this extends to the similarity between low-level visual properties of objects from an old and a new learning set. Two subject groups learned to discriminate two sets of target from non-target faces over 3 sessions 24 hours apart: on day 1, subjects learned face set A; on day 2, they recalled face set A and learned face set B; on day 3, they recalled face set A again. Stimuli were 185 filtered neutral faces from the Chicago Face Database. In subject group 1, the spatial frequencies of face set A and face set B were filtered with the same log-polar checkerboard in the Fourier domain (like the one described in Yue et al., 2006) whereas, in subject group 2, the spatial frequencies of face set A and face set B were filtered with complementary log-polar checkerboards in the Fourier domain. Results indicate that the similarity of orientations and frequencies between face sets increases significantly the number of interferences.

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