Cognitive Control of Working Memory: A Model-Based Approach

Abstract

Working memory (WM)-based decision making depends on a number of cognitive control processes that control the flow of information into and out of WM and ensure that only relevant information is held active in WM’s limited-capacity store. Although necessary for successful decision making, recent work has shown that these control processes impose performance costs on both the speed and accuracy of WM-based decisions. Using the reference-back task as a benchmark measure of WM control, we conducted evidence accumulation modeling to test several competing explanations for six benchmark empirical performance costs. Costs were driven by a combination of processes, running outside of the decision stage (longer non-decision time) and showing the inhibition of the prepotent response (lower drift rates) in trials requiring WM control. Individuals also set more cautious response thresholds when expecting to update WM with new information versus maintain existing information. We discuss the promise of this approach for understanding cognitive control in WM-based decision making.

Investigating working memory updating processes of the human subcortex using 7T MRI

“…We replicated many behavioral results from previous reference-back studies (e.g., Boag et al, 2021; Jongkees, 2020; Rac-Lubashevky & Kessler, 2016a, 2016b, 2018). However, we did not replicate the gate closing cost (for accuracy nor RT) that other studies have reported (e.g., Boag et al, 2021; Jongkees, 2020; Rac-Lubashevky & Kessler, 2016a, 2016b, 2018). This may have been due to our ultra-high field scanning protocol, which allowed for fewer trials than are typically collected in reference-back studies.…”

“…The first trial from each block, which did not require a response, was excluded, as well as any trials with response times faster than 0.150 seconds or slower than 3 seconds, following the exclusion criteria used in Boag et al (2021). For RT analysis, error trials were excluded.…”

Joint modelling of latent cognitive mechanisms shared across decision-making domains

“…Furthermore, these studies also found a sequencing effect in that participants were faster when previous trial's trial type (i.e., reference or comparison) was repeated compared to a switch in the trial type sequence (e.g. Boag et al, 2021;Jongkees, 2020;Rac-Lubashevsky and Frank, 2021;Rac-Lubashevsky and Kessler, 2016b). In the current study we also found that participants performed better following stimulus-identity (e.g., X or O) repetitions between trials compared to switches in stimulus identity.…”

“…Furthermore, cognitive psychologists assume that the type of evidence accumulated differs between types of decisions. For example, the strength of accumulation for decisions involving working memory is assumed to be based on strength of working memory representations (Boag et al, 2021), whereas the accumulation process for value-based decision making may depend on subjective preference for alternate values (Ratcliff et al, 2016). Nevertheless, the underlying architecture of accumulating evidence for various choice options until a threshold is met, remains the same.…”

Beyond Reactive Inhibition: Unpacking the Multifaceted Nature of Motor Inhibition

“…Alternatively, could they emerge from the cooperation between different executive functions? This last position is that held by Boag et al [7]. Using a model-based approach, the authors showed that the performance in a working-memory decision task depends upon the interplay of cognitive functions, including reactive inhibition.…”