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High Working Memory Load Impairs Language Processing during a Simulated Piloting Task: An ERP and Pupillometry Study

Overview of attention for article published in Frontiers in Human Neuroscience, May 2016
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  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

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Title
High Working Memory Load Impairs Language Processing during a Simulated Piloting Task: An ERP and Pupillometry Study
Published in
Frontiers in Human Neuroscience, May 2016
DOI 10.3389/fnhum.2016.00240
Pubmed ID
Authors

Mickaël Causse, Vsevolod Peysakhovich, Eve F. Fabre

Abstract

Given the important amount of visual and auditory linguistic information that pilots have to process, operating an aircraft generates a high working-memory load (WML). In this context, the ability to focus attention on relevant information and to remain responsive to concurrent stimuli might be altered. Consequently, understanding the effects of WML on the processing of both linguistic targets and distractors is of particular interest in the study of pilot performance. In the present work, participants performed a simplified piloting task in which they had to follow one of three colored aircraft, according to specific written instructions (i.e., the written word for the color corresponding to the color of one of the aircraft) and to ignore either congruent or incongruent concurrent auditory distractors (i.e., a spoken name of color). The WML was manipulated with an n-back sub-task. Participants were instructed to apply the current written instruction in the low WML condition, and the 2-back written instruction in the high WML condition. Electrophysiological results revealed a major effect of WML at behavioral (i.e., decline of piloting performance), electrophysiological, and autonomic levels (i.e., greater pupil diameter). Increased WML consumed resources that could not be allocated to the processing of the linguistic stimuli, as indexed by lower P300/P600 amplitudes. Also, significantly, lower P600 responses were measured in incongruent vs. congruent trials in the low WML condition, showing a higher difficulty reorienting attention toward the written instruction, but this effect was canceled in the high WML condition. This suppression of interference in the high load condition is in line with the engagement/distraction trade-off model. We propose that P300/P600 components could be reliable indicators of WML and that they allow an estimation of its impact on the processing of linguistic stimuli.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 97 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Turkey 1 1%
Unknown 94 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 23%
Student > Master 15 15%
Researcher 11 11%
Student > Bachelor 7 7%
Student > Doctoral Student 5 5%
Other 10 10%
Unknown 27 28%
Readers by discipline Count As %
Psychology 23 24%
Engineering 13 13%
Neuroscience 7 7%
Linguistics 5 5%
Social Sciences 4 4%
Other 13 13%
Unknown 32 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 March 2017.
All research outputs
#7,121,622
of 22,721,584 outputs
Outputs from Frontiers in Human Neuroscience
#3,052
of 7,130 outputs
Outputs of similar age
#113,748
of 335,509 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#93
of 196 outputs
Altmetric has tracked 22,721,584 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,130 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 335,509 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 196 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.