Several models in the verbal domain of short-term memory (STM) consider a dissociation between item and order processing. This view is supported by data demonstrating that different types of time-based interference have a greater effect on memory for the order of to-be-remembered items than on memory for the items themselves. The present study investigated the domain-generality of the item versus serial order dissociation by comparing the differential effects of time-based interfering tasks, such as rhythmic interference and articulatory suppression, on item and order processing in verbal and musical STM domains. In Experiment 1, participants had to maintain sequences of verbal or musical information in STM, followed by a probe sequence, this under different conditions of interference (no-interference, rhythmic interference, articulatory suppression). They were required to decide whether all items of the probe list matched those of the memory list (item condition) or whether the order of the items in the probe sequence matched the order in the memory list (order condition). In Experiment 2, participants performed a serial order probe recognition task for verbal and musical sequences ensuring sequential maintenance processes, under no-interference or rhythmic interference conditions. For Experiment 1, serial order recognition was not significantly more impacted by interfering tasks than was item recognition, this for both verbal and musical domains. For Experiment 2, we observed selective interference of the rhythmic interference condition on both musical and verbal order STM tasks. Overall, the results suggest a similar and selective sensitivity to time-based interference for serial order STM in verbal and musical domains, but only when the STM tasks ensure sequential maintenance processes.
Long-term memory knowledge is considered to impact short-term maintenance of item information in working memory, as opposed to short-term maintenance of serial order information. Evidence supporting an impact of semantic knowledge on serial order maintenance remains weak. In the present study, we demonstrate that semantic knowledge can impact the processing of serial order information in a robust manner. Experiment 1 manipulated semantic relatedness effect by using semantic categories presented in subgroups of items (leaftreebranchcloudskyrain). This semantic grouping manipulation was compared to a temporal grouping manipulation whose impact on the processing of serial order information is wellestablished. Both the semantic and temporal grouping manipulations constrained the occurrence of serial order errors in a robust manner: when migrating to a non-target serial position, items tended to do so most of the time toward the position of a semantically related item or within the same temporal group. Critically, this impact of semantic knowledge on the pattern of migration errors was not observed anymore in Experiment 2, in which we broke-up the semantic groups, by presenting the semantically related items an interleaved fashion (leafcloudtreeskybranchrain). Both semantic and temporal grouping factors may reflect a general mechanism through which information is represented hierarchically. Alternatively, both factors could result from the syntactic and/or semantic regularities that naturally structure linguistic information.These results support models considering direct interactions between serial order and linguistic components of WM.
The lexicality effect in verbal short-term memory (STM), in which word lists are better recalled than nonwords lists, is considered to reflect the influence of linguistic long-term memory (LTM) knowledge on verbal STM performance. The locus of this effect remains, however, a matter of debate. The redintegrative account considers that degrading phonological traces of memoranda are reconstructed at recall by selecting lexical LTM representations that match the phonological traces. According to a strong version of this account, redintegrative processes should be strongly reduced in recognition paradigms, leading to reduced LTM effects. We tested this prediction by contrasting word and nonword memoranda in a fast encoding probe recognition paradigm. We observed a very strong lexicality effect, with better and faster recognition performance for words as compared to nonwords. These results do not support a strong version of the redintegrative account of LTM effects in STM which considers that these LTM effects would be the exclusive product of reconstruction mechanisms. If redintegration processes intervene in STM recognition tasks, they must be very fast, which at the same time provides support for models considering direct activation of lexico-semantic knowledge during verbal STM tasks.
Compression, the ability to recode information in a denser format, is a core property of working memory (WM). Previous studies have shown that the ability to compress information largely benefits WM performance. Importantly, recent evidence also suggests compression as freeing up WM resources, thus enhancing recall performance for other, less compressible information. Contrary to the traditional view positing that between-item similarity decreases WM performance, this study shows that between-item similarity can be used to free up WM resources through compression. Across a series of four experiments, we show that between-item similarity not only enhances recall performance for similar items themselves, but also for other, less compressible items within the same list, and this in the semantic (Experiment 1), phonological (Experiment 2), visuospatial (Experiment 3), and visual (Experiment 4) domains. Across these different domains, a consistent pattern of results emerged: between-item similarity proactively–but not retroactively–enhanced WM performance for other items, and this as compared with a condition in which between-item similarity at the whole-list level was minimized. We propose that between-item similarity in any domain may impact WM using the same underlying machinery: via a compression mechanism, which allows an efficient reallocation of WM resources.
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