A process of active, item-wise removal of information from working memory (WM) has been proposed as the core component process of WM updating. Consequently, we investigated the associations between removal efficiency, WM capacity, and fluid intelligence (gF) in a series of three individual-differences studies via confirmatory factor analysis. In each study, participants completed a novel WM updating task battery designed to measure removal efficiency. In Study 1, participants additionally completed a WM capacity task battery. In Study 2, participants completed a battery of well-established measures of gF in addition to the updating battery. In Study 3, participants completed the updating, WM capacity, and gF task batteries. The results suggested that removal efficiency was related to both WM capacity and gF. Furthermore, based on a mediation analysis, the relationship between removal efficiency and gF was found to be entirely indirect via removal's influence on WM capacity. The results were interpreted to suggest that removal ability may contribute to performance in reasoning tasks effectively through increasing WM capacity, presumably through reducing interference from distracting information.
Working memory (WM) is a system for maintenance of and access to a limited number of goal-relevant representations in the service of higher cognition. Because of its limited capacity, WM requires interference-control processes, allowing us to avoid being distracted by irrelevant information. Recent research has proposed two interference-control processes, which are conceptually similar: (1) an active, item-wise removal process assumed to remove no-longer relevant information from WM, and (2) an inhibitory process assumed to suppress the activation of distractors against competing, goal-relevant representations. The purpose of this study was to determine the extent to which the tasks used to assess removal and inhibition measure the same interference-control construct. Results showed acceptable to good reliabilities for nearly all measures. Similar to previous studies, a structural equation modeling approach identified a reliable latent variable of removal. However, also similar to some previous studies, no latent variable of inhibition could be established. This was the case even when the correlation matrix used to compute the latent variable of inhibition was disattenuated for imperfect reliability. Critically, the individual measures of inhibition were unrelated to the latent variable of removal. These results provide tentative support for the notion that removal is not related to the interference-control processes assessed in inhibition tasks. This suggests that the removal process should be conceptualized as a process independent of the concept of inhibition, as proposed in computational WM models that implement removal as the “unbinding” of a WM item from the context in which it occurred.
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