Scientific Reports (Nov 2023)

Probabilistic and rich individual working memories revealed by a betting game

  • Syaheed B. Jabar,
  • Kartik K. Sreenivasan,
  • Stergiani Lentzou,
  • Anish Kanabar,
  • Timothy F. Brady,
  • Daryl Fougnie

DOI
https://doi.org/10.1038/s41598-023-48242-x
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 14

Abstract

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Abstract When asked to remember a color, do people remember a point estimate (e.g., a particular shade of red), a point estimate plus an uncertainty estimate, or are memory representations rich probabilistic distributions over feature space? We asked participants to report the color of a circle held in working memory. Rather than collecting a single report per trial, we had participants place multiple bets to create trialwise uncertainty distributions. Bet dispersion correlated with performance, indicating that internal uncertainty guided bet placement. While the first bet was on average the most precisely placed, the later bets systematically shifted the distribution closer to the target, resulting in asymmetrical distributions about the first bet. This resulted in memory performance improvements when averaging across bets, and overall suggests that memory representations contain more information than can be conveyed by a single response. The later bets contained target information even when the first response would generally be classified as a guess or report of an incorrect item, suggesting that such failures are not all-or-none. This paradigm provides multiple pieces of evidence that memory representations are rich and probabilistic. Crucially, standard discrete response paradigms underestimate the amount of information in memory representations.