Abstract
Short-term memorization of items while performing a concurrent distracting task requires maintenance processes. The time-based resource-sharing model of working memory (Barrouillet et al. in Psychol Rev 118:175–192, 2011) and its computational version TBRS* (Oberauer and Lewandowsky in Psychon Bull Rev 18:10–45, 2011) proposed that items are refreshed when attention is not captured by the distracting activity. However, these models are unable to account for human performance on the last items when temporal constraints are substantial. The present study presents an analytic approach and computational simulations showing that the sequentiality of the domain-general attentional refreshing mechanism is responsible for the discrepancy between humans and model. It is suggested that the focus of attention could be flexible. The implementation of a computational model based on this solution provides a much better fit to human data. Outcomes are discussed in reference to contemporary works on the phonological loop as well as in reference to other computational models of short-term memory.
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Because the number of squares condition (4 and 8 squares) did not have any effect on recall performances, the three SPC represent data for the three pace conditions (slow, medium, fast) irrespective of the number of squares.
For sake of clarity, it is worth noting that in the present case, B would have been refreshed once plus once more during a fraction of time of about 70 ms (corresponding to the remaining time available after having refreshed the ABCA sequence).
Refreshing in TBRS* is based on Hebbian association learning. With this mechanism, it is not possible to associate n items with n positions simultaneously so that the first item is associated with the first position, the second item to the second position, and so on. So, even if the refreshing is conceptually simultaneous across multiple item-position associations, at a computational level, refreshing still occurs sequentially, one item-position association at a time, but in such a way that four subsequent item-position associations are grouped together, and assigned a single duration Tr.
Other simulations showed that an improvement over the original model has already appeared with an attentional focus size of two and is increasing slightly with a size of three, then four.
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Acknowledgments
We thank anonymous reviewers of a previous version of this paper whose comments helped us to improve the manuscript, as well as the “Région Rhône-Alpes” for its financial support.
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Portrat, S., Lemaire, B. Is Attentional Refreshing in Working Memory Sequential? A Computational Modeling Approach. Cogn Comput 7, 333–345 (2015). https://doi.org/10.1007/s12559-014-9294-8
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DOI: https://doi.org/10.1007/s12559-014-9294-8