A dynamic neural resource model bridges sensory and working memory.

Ivan Tomić, Paul M Bays
Author Information
  1. Ivan Tomić: Department of Psychology, University of Cambridge, Cambridge, United Kingdom. ORCID
  2. Paul M Bays: Department of Psychology, University of Cambridge, Cambridge, United Kingdom. ORCID

Abstract

Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or 'iconic' memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.

Keywords

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Grants

  1. /Wellcome Trust
  2. 10.35802/106926/Wellcome Trust

MeSH Term

Humans
Memory, Short-Term
Models, Neurological
Visual Perception
Adult
Mental Recall
Male
Female
Young Adult

Word Cloud

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