scholarly journals Isolating age-group differences in working memory load-related neural activity: Assessing the contribution of working memory capacity using a partial-trial fMRI method

NeuroImage ◽  
2013 ◽  
Vol 72 ◽  
pp. 20-32 ◽  
Author(s):  
Ilana J. Bennett ◽  
Hannah G. Rivera ◽  
Bart Rypma
Keyword(s):  
Working Memory ◽  
Neural Activity ◽  
Memory Load ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Group Differences ◽  
Age Group ◽  
Working Memory Load

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 Learning to suppress a distractor is not affected by working memory load

2019 ◽  
Vol 27 (1) ◽  
pp. 96-104 ◽  
Author(s):  
Ya Gao ◽  
Jan Theeuwes
Keyword(s):  
Working Memory ◽  
High Probability ◽  
Spatial Working Memory ◽  
Memory Load ◽  
Working Memory Capacity ◽  
Memory Task ◽  
Automatic Process ◽  
Long Term Memory ◽  
Working Memory Load ◽  
Statistical Regularities

AbstractWhere and what we attend to is not only determined by our current goals but also by what we have encountered in the past. Recent studies have shown that people learn to extract statistical regularities in the environment resulting in attentional suppression of high-probability distractor locations, effectively reducing capture by a distractor. Here, we asked whether this statistical learning is dependent on working memory resources. The additional singleton task in which one location was more likely to contain a distractor was combined with a concurrent visual working memory task (Experiment 1) and a spatial working memory task (Experiment 2). The result showed that learning to suppress this high-probability location was not at all affected by working memory load. We conclude that learning to suppress a location is an implicit and automatic process that does not rely on visual or spatial working memory capacity, nor on executive control resources. We speculate that extracting regularities from the environment likely relies on long-term memory processes.

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