There is still a strong debate in the working memory literature about the cause of forgetting, with many articles providing evidence for the existence of temporal decay and as many publications providing evidence compatible with interference being the only mechanism involved in forgetting. In order to reconcile the two views, this article describes TBRS∗-I (for Time-Based Resource-Sharing∗-Interference), a computational model of working memory which incorporates an interference-based mechanism to the decay-based implementation TBRS∗ within the TBRS theoretical framework. At encoding, memoranda are associated to their context, namely their position in the list. Temporal decay decreases the strength of these associations, but a refreshing process may reactivate it during free time. Distractors may alter the distributed representation of memoranda but refreshing can restore them based on the long-term memory representations. Refreshing is therefore twofold: reactivation plus restoration, each one counteracting the detrimental time-based and interference-based decays, respectively. Two types of interference are implemented: interference by confusion which depends on the degree of overlap between memoranda and distractors and interference by superposition which depends on the similarity between them. TBRS∗-I was tested on six benchmark findings on retention-interval and distractor-processing effects by means of millions of simulations testing the effects of seven factors on memory performance: the number of memoranda, the duration of distractor attentional capture, the duration of free time, the number of distractors, the amount of overlap between memoranda and distractors, the similarity between memoranda and distractors and the homogeneity of distractors (all identical or all distinct). TBRS∗-I replicated classical effects and proved to be a suitable hybrid model integrating both interference and time-based decay. The article also discusses the compatibility of TBRS∗-I with a unitary or dual view of memory and the issue of integrating time and interference in a single model. Computer codes and data are available at https://osf.io/65sna/.
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 April 2018.
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Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 31,443 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.6. This one has gotten more attention than average, scoring higher than 71% of its peers.
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