Complementary Correlational Profiles between Slow Wave Brain Oscillations and Working Memory Capacity

Working memory involves a range of functions, including maintenance of information and processing that information undisturbed by distraction. Neuroscientific studies have observed critical contributions from frontal and parietal brain regions during processing of cognitive demanding tasks. However, less is known about individual differences in the resting state and their association with working memory capacity. In this study, electrophysiological recordings were taken from thirty volunteers in eyes closed and eyes open conditions after completing the automated version of the operation span task. The results reveal two clusters of correlations: a midline-theta cluster and a parieto-temporal alpha cluster. The theta and alpha clusters have a negative and a positive correlation with operation span performance, respectively. These results are interpreted as individual differences in cognitive preparedness, with the centro-parietal region being critical in switching between outward and inward attention, with the balance of theta and alpha spectral power at Pz indicating to where cognitive resources are directed.

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How do Individual Differences in Attention Control and Working Memory Capacity Relate to Monitoring Automation?

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181319631196 ◽

2019 ◽

Vol 63 (1) ◽

pp. 1409-1413

Author(s):

Cyrus K. Foroughi ◽

Ericka Rovira ◽

Kaley Rose ◽

DaShawn Davis ◽

Jaritzel J. Jurado ◽

...

Keyword(s):

Working Memory ◽

Individual Differences ◽

Positive Relationship ◽

Working Memory Capacity ◽

Memory Capacity ◽

Attention Control ◽

Automated System ◽

Significant Positive Relationship ◽

Operation Span ◽

Saccade Task

With the proliferation of automated tasks, software, and systems, humans are moving from an active participant in the function of a task to a passive monitor of an automated system that is completing that task. Unfortunately, humans are not well-suited for monitoring roles and there is a need to better understand the factors involved when humans successfully identify when an automated system fails. The goal for this research was to determine whether individual differences in attention control (as measured by the anti-saccade task) and working memory capacity (as measured by the shortened operation span) related to an individual’s ability to detect automation failures. In experiment 1, there was a significant positive relationship ( r = .31) between scores on the anti-saccade task and the number of automation failures that participants detected. In experiment 2, there was a significant positive relationship ( r = .32) between scores on the shortened operation span and the number of automation failures that participants’ detected. The results suggest that certain individuals are better suited for detecting automation failures. Selecting for these individuals may be a fruitful endeavor as automated systems continue to grow across society.

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