Modeling verbal short-term memory: A walk around the neighborhood.

Abstract

When remembering over the short-term, long-term knowledge has a large effect on the number of correctly recalled items and little impact on memory for order. This is true, for example, when the effects of semantic category are examined. Contrary to what these findings suggest, Poirier et al. in 2015 proposed that memory for order relies on the level of activation within long-term networks. Importantly, although their view has been criticized, they showed that manipulating semantic associations led to item migrations that were atypical. In this article, we show that similar migrations can be obtained with another knowledge-based factor: orthographic neighborhood. In three experiments, we manipulated the orthographic neighborhood of to-berecalled items. The latter is a sublexical factor; as such, it is much less likely than semantic relatedness to involve demand characteristics or grouping strategies. The first experiment established that the neighborhood manipulation produced the pattern of item migrations previously observed with semantic relatedness, confirming that the migration effect can generalize to other variables. The last two experiments suggested that migrations were due to the features shared across list items rather than to item co-activation (as in Poirier et al.). The results were successfully modeled by calling upon the Revised Feature Model, where recall depends on selecting a retrieval candidate based on the features of the cueing information. Overall, our findings underline the usefulness of a model where retrieval is determined by relative distinctiveness and underline that multiple mechanisms can lead to order errors in recall.

The Production Effect Becomes Spatial

“…With the aim of contributing to these advances, we examined a series of predictions derived from the RFM (Saint-Aubin et al., 2021, 2023). The model has already been successful in accounting for memory performance in the verbal domain, both in paradigms associated with memory over the short-term (immediate serial recall and immediate order reconstruction) and over the long-term (e.g., delayed free recall; Cyr et al, 2022; Poirier et al, 2019).…”

“…We call upon a view of primary memory where distinctiveness, interference, long-term memory, and rehearsal are all important. This view’s main ideas are embodied in a computational model known as the Revised Feature Model (RFM; Saint-Aubin et al, 2021, 2023). The RFM owes a lot to the proposals of Nairne (1988, 1990) and Nosofsky (2011) and the work of others on rehearsal (Bhatarah et al, 2009; Grenfell-Essam et al, 2013; Murray, 1967).…”

“…Following Poirier et al (2019), Saint-Aubin et al (2021, 2023), and Cyr et al (2022), we used ABC Partial Rejection Control (ABC-PRC; Sisson et al, 2007, 2009). ABC-PRC works by repeatedly sampling from a prior over the parameter space until it finds a set of parameters that generate a set of summary statistics (in our case serial position curves) sufficiently close to the data, as determined by the discrepancy function.…”