학술논문

Stochastic attractor models of visual working memory.
Document Type
Article
Author
Source
PLoS ONE. 4/3/2024, Vol. 19 Issue 4, p1-25. 25p.
Subject
*VISUAL memory
*STOCHASTIC models
*SHORT-term memory
*ATTRACTORS (Mathematics)
*STOCHASTIC processes
*CONTINUOUS functions
Language
ISSN
1932-6203
Abstract
This paper investigates models of working memory in which memory traces evolve according to stochastic attractor dynamics. These models have previously been shown to account for response-biases that are manifest across multiple trials of a visual working memory task. Here we adapt this approach by making the stable fixed points correspond to the multiple items to be remembered within a single-trial, in accordance with standard dynamical perspectives of memory, and find evidence that this multi-item model can provide a better account of behavioural data from continuous-report tasks. Additionally, the multi-item model proposes a simple mechanism by which swap-errors arise: memory traces diffuse away from their initial state and are captured by the attractors of other items. Swap-error curves reveal the evolution of this process as a continuous function of time throughout the maintenance interval and can be inferred from experimental data. Consistent with previous findings, we find that empirical memory performance is not well characterised by a purely-diffusive process but rather by a stochastic process that also embodies error-correcting dynamics. [ABSTRACT FROM AUTHOR]