Pupil Trend Reflects Suboptimal Alertness Maintenance over 10 s in Vigilance and Working Memory Performance: An Exploratory Study

Maintaining concentration on demanding cognitive tasks, such as vigilance (VG) and working memory (WM) tasks, is crucial for successful task completion. Previous research suggests that internal concentration maintenance fluctuates, potentially declining to suboptimal states, which can influence trial-by-trial performance in these tasks. However, the timescale of such alertness maintenance, as indicated by slow changes in pupil diameter, has not been thoroughly investigated. This study explored whether "pupil trends"-which selectively signal suboptimal tonic alertness maintenance at various timescales-negatively correlate with trial-by-trial performance in VG and WM tasks. Using the psychomotor vigilance task (VG) and the visual-spatial two-back task (WM), we found that human pupil trends lasting over 10 s were significantly higher in trials with longer reaction times, indicating poorer performance, compared with shorter reaction time trials, which indicated better performance. The attention network test further validated that these slow trends reflect suboptimal states related to (tonic) alertness maintenance rather than suboptimal performance specific to VG and WM tasks, which is more associated with (phasic) responses to instantaneous interference. These findings highlight the potential role of detecting and compensating for nonoptimal states in VG and WM performance, significantly beyond the 10 s timescale. Additionally, the findings suggest the possibility of estimating human concentration during various visual tasks, even when rapid pupil changes occur due to luminance fluctuations.

Authors

Institutions

Publication Details

Journal
eNeuro
Published
2024-11-18
DOI
https://doi.org/10.1523/eneuro.0250-24.2024
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.64

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pupil Trend Reflects Suboptimal Alertness Maintenance over 10 s in Vigilance and Working Memory Performance: An Exploratory Study

Jumpei Yamashita, Takatsune Kumada, Makoto Yoneya, Kazushi Maruya et al.
1 citations
eNeuro
Human-Automation Interaction and Safety
0.64
article

Pupil Trend Reflects Suboptimal Alertness Maintenance over 10 s in Vigilance and Working Memory Performance: An Exploratory Study

Jumpei Yamashita, Takatsune Kumada, Makoto Yoneya, Kazushi Maruya, Hiroki Terashima, Haruo Oishi
article en
1 citations

Abstract

Maintaining concentration on demanding cognitive tasks, such as vigilance (VG) and working memory (WM) tasks, is crucial for successful task completion. Previous research suggests that internal concentration maintenance fluctuates, potentially declining to suboptimal states, which can influence trial-by-trial performance in these tasks. However, the timescale of such alertness maintenance, as indicated by slow changes in pupil diameter, has not been thoroughly investigated. This study explored whether "pupil trends"-which selectively signal suboptimal tonic alertness maintenance at various timescales-negatively correlate with trial-by-trial performance in VG and WM tasks. Using the psychomotor vigilance task (VG) and the visual-spatial two-back task (WM), we found that human pupil trends lasting over 10 s were significantly higher in trials with longer reaction times, indicating poorer performance, compared with shorter reaction time trials, which indicated better performance. The attention network test further validated that these slow trends reflect suboptimal states related to (tonic) alertness maintenance rather than suboptimal performance specific to VG and WM tasks, which is more associated with (phasic) responses to instantaneous interference. These findings highlight the potential role of detecting and compensating for nonoptimal states in VG and WM performance, significantly beyond the 10 s timescale. Additionally, the findings suggest the possibility of estimating human concentration during various visual tasks, even when rapid pupil changes occur due to luminance fluctuations.

eNeuroVol. 11(12)
Kyoto University (JP), NTT (Japan) (JP), NTT (United States) (US)
Nippon Telegraph and Telephone
No poverty
Openalex Percentile: Top 25%
Human-Automation Interaction and Safety
0.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.