August 2016
Volume 16, Issue 12
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2016
Temporal dynamics of memorability: an intrinsic brain signal distinct from memory
Author Affiliations
  • Seyed-Mahdi Khaligh-Razavi
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  • Wilma Bainbridge
    Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
  • Dimitrios Pantazis
    McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
  • Aude Oliva
    Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Journal of Vision September 2016, Vol.16, 38. doi:10.1167/16.12.38
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      Seyed-Mahdi Khaligh-Razavi, Wilma Bainbridge, Dimitrios Pantazis, Aude Oliva; Temporal dynamics of memorability: an intrinsic brain signal distinct from memory. Journal of Vision 2016;16(12):38. doi: 10.1167/16.12.38.

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

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Abstract

Can we predict what people will remember, as they are perceiving an image? Recent work has identified that images carry the attribute of memorability, a predictive value of whether a novel image will be later remembered or forgotten (Isola et al. 2011, 2014; Bainbridge et al. 2013). Despite the separate subjective experiences people have, certain faces and scenes are consistently remembered and others forgotten, independent of observer. Whereas many studies have concentrated on an observer-centric predictor of memory (e.g. Kuhl et al. 2012), memorability is a complementary, stimulus-centric predictor, generalizable across observers and context. How is memorability manifested in the brain, and how does it differ from pure memory encoding? In this study we characterized temporal dynamics of memorability, and showed that magnetoencephalography (MEG) brain signals are predictive of memorability. We further showed that the neural signature of memorability exists for both faces and scenes; however each of them has its own specific temporal dynamics. Faces showed a persistent memorability signal whereas scenes had more transient characteristics. We also found that neural signatures of memorability across time are different from that of memory encoding, as measured by a post-MEG memory recognition task. This work is the first to measure memorability, as an innate property of images, from electrophysiological brain signals and characterize its temporal dynamics.

Meeting abstract presented at VSS 2016

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