Working Memory Load Selectively Influences Response Inhibition in a Stop Signal Task

2020 ◽  
pp. 003329412092827
Author(s):  
Leanne Boucher ◽  
Brandi Viparina ◽  
W. Matthew Collins
Keyword(s):  
Working Memory ◽  
Reaction Time ◽  
Memory Load ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Working Memory Load ◽  
Stop Signal Reaction Time ◽  
Load Conditions

Inhibitory control is a key executive function and has been studied extensively using the stop signal task. By applying a simple race model that posits an independent race between a GO process responsible for initiation of responses and a STOP process responsible for inhibition of responses, one can estimate how long it takes an individual to inhibit an ongoing response, the stop signal reaction time. Here, we examined how stop signal reaction time can be affected by working memory. Participants engaged in a dual task; they completed a stop signal task under low and high working memory load conditions. Working memory capacity was also measured. We found that the STOP process was lengthened in the high, compared to the low, working memory load condition, as evidenced by differences in stop signal reaction time. The GO process was unaffected and working memory capacity could not account for differences across the load conditions. These results indicate that inhibitory control can be influenced by placing demands on working memory.

scholarly journals Working Memory Capacity and Visual–Verbal Cognitive Load Modulate Auditory–Sensory Gating in the Brainstem: Toward a Unified View of Attention

2012 ◽  
Vol 24 (11) ◽  
pp. 2147-2154 ◽  
Author(s):  
Patrik Sörqvist ◽  
Stefan Stenfelt ◽  
Jerker Rönnberg
Keyword(s):  
Working Memory ◽  
Memory Load ◽  
Early Stage ◽  
Working Memory Capacity ◽  
Load Condition ◽  
Memory Capacity ◽  
Working Memory Load ◽  
Central Domain ◽  
Brainstem Response ◽  
Unified View

Two fundamental research questions have driven attention research in the past: One concerns whether selection of relevant information among competing, irrelevant, information takes place at an early or at a late processing stage; the other concerns whether the capacity of attention is limited by a central, domain-general pool of resources or by independent, modality-specific pools. In this article, we contribute to these debates by showing that the auditory-evoked brainstem response (an early stage of auditory processing) to task-irrelevant sound decreases as a function of central working memory load (manipulated with a visual–verbal version of the n-back task). Furthermore, individual differences in central/domain-general working memory capacity modulated the magnitude of the auditory-evoked brainstem response, but only in the high working memory load condition. The results support a unified view of attention whereby the capacity of a late/central mechanism (working memory) modulates early precortical sensory processing.

The role of working memory capacity in analytic and multiply-constrained problem-solving in demanding situations

2020 ◽  
Vol 73 (6) ◽  
pp. 920-928
Author(s):  
Derek M Ellis ◽  
B Hunter Ball ◽  
Nicole Kimpton ◽  
Gene A Brewer
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Memory Load ◽  
Item Difficulty ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Working Memory Load ◽  
Memory Processes ◽  
Constrained Problem

Working memory processes are important for analytic problem-solving; however, their role in multiply-constrained problem-solving is currently debated. This study explored individual differences in working memory and successful completion of analytic and multiply-constrained problem-solving by having participants solve algebra and compound remote associate (CRAT) problems of varying difficulty under low and high memory demand conditions. Working memory was predictive of both algebra and multiply-constrained problem-solving. Specifically, participants with high working memory solved more problems than those with low working. Memory load did not differentially affect performance for low and high working memory participants. However, for multiply-constrained problem-solving the effect of item difficulty was more detrimental for high-span participants than low-span participants. Together, these findings suggest that working memory processes are important for both types of problem-solving and that participants with low working memory capacity may need to offload internal memory demands onto the environment to efficiently solve problems.

scholarly journals Intensive Working Memory Training Produces Functional Changes in Large-scale Frontoparietal Networks

2016 ◽  
Vol 28 (4) ◽  
pp. 575-588 ◽  
Author(s):  
Todd W. Thompson ◽  
Michael L. Waskom ◽  
John D. E. Gabrieli
Keyword(s):  
Working Memory ◽  
Executive Control ◽  
Large Scale ◽  
Memory Load ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Neural Systems ◽  
Control Network ◽  
Working Memory Load ◽  
Executive Control Network

Working memory is central to human cognition, and intensive cognitive training has been shown to expand working memory capacity in a given domain. It remains unknown, however, how the neural systems that support working memory are altered through intensive training to enable the expansion of working memory capacity. We used fMRI to measure plasticity in activations associated with complex working memory before and after 20 days of training. Healthy young adults were randomly assigned to train on either a dual n-back working memory task or a demanding visuospatial attention task. Training resulted in substantial and task-specific expansion of dual n-back abilities accompanied by changes in the relationship between working memory load and activation. Training differentially affected activations in two large-scale frontoparietal networks thought to underlie working memory: the executive control network and the dorsal attention network. Activations in both networks linearly scaled with working memory load before training, but training dissociated the role of the two networks and eliminated this relationship in the executive control network. Load-dependent functional connectivity both within and between these two networks increased following training, and the magnitudes of increased connectivity were positively correlated with improvements in task performance. These results provide insight into the adaptive neural systems that underlie large gains in working memory capacity through training.

scholarly journals Is motor inhibition involved in the processing of sentential negation? An assessment via the Stop-Signal Task

2021 ◽  
Author(s):  
Martina Montalti ◽  
Marta Calbi ◽  
Valentina Cuccio ◽  
Maria Alessandra Umiltà ◽  
Vittorio Gallese
Keyword(s):  
Reaction Time ◽  
Language Processing ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Motor Inhibition ◽  
Good Tool ◽  
Scientific Debate ◽  
Sentential Negation ◽  
Stop Signal Reaction Time ◽  
Methodological Considerations

AbstractIn the last decades, the embodied approach to cognition and language gained momentum in the scientific debate, leading to evidence in different aspects of language processing. However, while the bodily grounding of concrete concepts seems to be relatively not controversial, abstract aspects, like the negation logical operator, are still today one of the main challenges for this research paradigm. In this framework, the present study has a twofold aim: (1) to assess whether mechanisms for motor inhibition underpin the processing of sentential negation, thus, providing evidence for a bodily grounding of this logic operator, (2) to determine whether the Stop-Signal Task, which has been used to investigate motor inhibition, could represent a good tool to explore this issue. Twenty-three participants were recruited in this experiment. Ten hand-action-related sentences, both in affirmative and negative polarity, were presented on a screen. Participants were instructed to respond as quickly and accurately as possible to the direction of the Go Stimulus (an arrow) and to withhold their response when they heard a sound following the arrow. This paradigm allows estimating the Stop Signal Reaction Time (SSRT), a covert reaction time underlying the inhibitory process. Our results show that the SSRT measured after reading negative sentences are longer than after reading affirmative ones, highlighting the recruitment of inhibitory mechanisms while processing negative sentences. Furthermore, our methodological considerations suggest that the Stop-Signal Task is a good paradigm to assess motor inhibition’s role in the processing of sentence negation.

scholarly journals Cognitive Modeling Suggests That Attentional Failures Drive Longer Stop-Signal Reaction Time Estimates in Attention Deficit/Hyperactivity Disorder

2019 ◽  
Vol 7 (4) ◽  
pp. 856-872 ◽  
Author(s):  
Alexander Weigard ◽  
Andrew Heathcote ◽  
Dóra Matzke ◽  
Cynthia Huang-Pollock
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Reaction Time ◽  
Attention Deficit ◽  
Cognitive Modeling ◽  
Stop Signal ◽  
Stop Signal Task ◽  
Unbiased Estimation ◽  
Children With Adhd ◽  
Hyperactivity Disorder ◽  
Stop Signal Reaction Time

Mean stop-signal reaction time (SSRT) is frequently employed as a measure of response inhibition in cognitive neuroscience research on attention deficit/hyperactivity disorder (ADHD). However, this measurement model is limited by two factors that may bias SSRT estimation in this population: (a) excessive skew in “go” RT distributions and (b) trigger failures, or instances in which individuals fail to trigger an inhibition process in response to the stop signal. We used a Bayesian parametric approach that allows unbiased estimation of the shape of entire SSRT distributions and the probability of trigger failures to clarify mechanisms of stop-signal task deficits in ADHD. Children with ADHD displayed greater positive skew than their peers in both go RT and SSRT distributions. However, they also displayed more frequent trigger failures, which appeared to drive ADHD-related stopping difficulties. Results suggest that performance on the stop-signal task among children with ADHD reflects impairments in early attentional processes, rather than inefficiency in the stop process.

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