Assessing Partial Overlap Costs In Declarative Working Memory

This study aims to investigate whether declarative working memory (WM) is affected by code occupation. Code occupation consists in worse performance when representations held in WM share some features compared to no features at all or when features fully overlap. Code occupation is consistently observed for procedural WM representations of action plans, when when maintaining plans that overlap only partially, so calle dpartial overlap costs. Declarative WM does not typically exhibit similar partial overlap costs. In two experiments, we will assess whether partial feature overlap leads to performance costs in both systems. In Experiment 1, participants will perform an action while holding another action plan in procedural WM, expecting to replicate the partial overlap cost observed in previous studies. In Experiment 2, participants will memorize a target and discriminate it from a lure while holding another stimulus in declarative WM. In both experiments, the competing representation held in WM can fully overlap, share no features or partially overlap with the currently relevant action or target. Assessing the presence of partial overlap costs in declarative WM allows to furthe rour understanding of the processes underling the crucial ability to maintain and manipulate information in WM, while shedding light on the similarities and differences between procedural and declarative WM systems.

[The experiment registered here is a direct replication of Experiment 2 preregistered here: https://doi.org/10.23668/psycharchives.16160, except we used slightly different arrows stimuli.] This study aims to investigate whether declarative working memory (WM) is affected by code occupation. Code occupation consists in worse performance when representations held in WM share some features compared to no features at all or when features fully overlap. Code occupation is consistently observed for procedural WM representations of action plans, when when maintaining plans that overlap only partially, so calle dpartial overlap costs. Declarative WM does not typically exhibit similar partial overlap costs. In two experiments, we will assess whether partial feature overlap leads to performance costs in both systems. In Experiment 1, participants will perform an action while holding another action plan in procedural WM, expecting to replicate the partial overlap cost observed in previous studies. In Experiment 2, participants will memorize a target and discriminate it from a lure while holding another stimulus in declarative WM. In both experiments, the competing representation held in WM can fully overlap, share no features or partially overlap with the currently relevant action or target. Assessing the presence of partial overlap costs in declarative WM allows to furthe rour understanding of the processes underling the crucial ability to maintain and manipulate information in WM, while shedding light on the similarities and differences between procedural and declarative WM systems.

[The experiment registered here is a close replication of the experiment preregistered here: https://doi.org/10.23668/psycharchives.16186]. This study aims to investigate whether declarative working memory (WM) is affected by code occupation. Code occupation consists in worse performance when representations held in WM share some features compared to no features at all or when features fully overlap. Code occupation is consistently observed for procedural WM representations of action plans, --when when maintaining plans that overlap only partially--, and shows in so called partial overlap costs. Declarative WM does not typically exhibit similar partial overlap costs. In this experiment, we will assess whether partial feature overlap leads to performance costs in declarative WM. To this aim, participants will memorize a target and discriminate it from a lure while holding another stimulus in declarative WM. The other-stimulus representation held in WM can fully overlap, share no features or partially overlap with the currently relevant action or target. Assessing the presence of partial overlap costs in declarative WM allows to further our understanding of the processes underling the crucial ability to maintain and manipulate information in WM, while shedding light on the similarities and differences between procedural and declarative WM systems.