What is the time course of working memory attentional refreshing?

Abstract

One way of maintaining information in working memory is through attentional refreshing, a process that was recently shown to be independent from verbal rehearsal. In the classical working memory complex span task, the usual assumption is that memoranda are refreshed in a cumulative fashion, starting from the first item, going in a forward order until the latest one, and cycling until there is no time to continue the process. However, there is no evidence that refreshing operates in that way. The present study proposes a computational modelling study, which constitutes a powerful method to investigate alternative hypotheses. Different refreshing schedules are investigated within computational implementation of the time-based resource sharing model. Their ability to fit three sets of behavioral data and to reproduce the major time-based resource sharing predictions were evaluated using standard model selection criteria. Besides an already published schedule in which the attentional focus is expanded, it appeared that one schedule, the least-activated-first, outperforms the classical cumulative one. The memory trace refreshed at a given time is the one that is the least activated in working memory at that time. These findings characterized the time course of attentional refreshing in working memory and specified the contribution of refreshing to primacy and recency effects. Moreover, in the light of various fields of cognitive psychology, we propose that such refreshing schedules can operate without a homunculus within a general framework including cognitive control and strategic considerations.

A Computational Model of Working Memory Integrating Time-Based Decay and Interference

“…They found a linear relationship between the mean memory span of participants and the cognitive load regardless of the nature of the processing component. This relationship was also predicted by the original TBRS ∗ computational model ( Oberauer and Lewandowsky, 2011 ) and its recent extensions ( Portrat and Lemaire, 2015 ; Lemaire et al, 2017 ). This was expected because increasing the cognitive load means less time for refreshing items and more time for temporal decay.…”

“…TBRS has been tested numerous times in the literature and constitutes a strong cognitive description on top of which a computational model can be designed. TBRS ∗ -I also relies on the basic architecture of TBRS ∗ ( Oberauer and Lewandowsky, 2011 ), a TBRS computational implementation which has also been tested several times after its first publication ( Lewandowsky and Oberauer, 2015 ; Portrat and Lemaire, 2015 ; Hoareau et al, 2016 ; Lemaire et al, 2017 ). In this section, we will discuss whether TBRS ∗ -I is compatible with a unitary or dual view of memory but also the issue of integrating time and interference in a single model as well as the parsimonious and reversible mechanisms that we propose.…”

“…As we mentioned earlier, the TBRS ∗ architecture is a two-layer network that connects item nodes to position nodes. Each item is represented as a single unit in the item layer, whereas each position is represented by a set of nodes in the position layer, such that adjacent positions share a particular proportion of nodes to simulate the usual confusion between adjacent positions ( Figure 1 from Lemaire et al, 2017 ). When a new memoranda is presented, connections are made between the corresponding unit in the item layer and position units in the position layer.…”

“… From Lemaire et al (2017) . (Upper) Simulated time course of a complex span task in which items J, N, H, and F are encoded (light gray areas).…”

“…The refreshing schedule is cumulative, exactly like in TBRS ∗ . Alternative schedules have been proposed ( Portrat and Lemaire, 2015 ; Lemaire et al, 2017 ) but our goal here is to make minimal changes to TBRS ∗ in order to be able to objectively evaluate the benefit of these changes. Numerous changes would make it difficult to understand the role of each one in the new behavior of the model.…”