Brain Activity Patterns While Viewing Construction Signs: AN EEG Study of Attention and Memory Encoding

To support efforts to improve safety communication within a construction setting, this study investigated the neural correlates of attention and memory encoding from subjects viewing construction signs to observe whether neural oscillations during viewing relate to participants’ subsequent recall of the safety information. The study recruited seventeen participants with construction-related backgrounds and collected electroencephalography (EEG) data as participants viewed construction signs. A subsequent memory test using hit rates categorized participants into groups with excellent versus poor memory of the signs. Event-related time-frequency analyses examined frontal gamma (associated with attention) and prefrontal theta (associated with memory encoding) oscillations as a function of the two groups. Results indicate that participants with excellent memory performance exhibited significantly higher frontal gamma activity during the 900–1000 ms post-stimulus window, suggesting enhanced attentional engagement. In contrast, participants with poor memory performance showed elevated prefrontal theta activity during the 800–1000 ms window, indicative of increased cognitive effort and less-efficient memory encoding. No significant differences manifest in the parietal alpha and temporal theta between the two groups. These findings highlight the importance of attentional processes and efficient memory encoding when comprehending construction signs, with design implications (i.e., pictogram + text condition) for more effective safety signage to improve workers' cognitive processing and memory retention.

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Publication Details

Journal
CIB Conferences
Published
2025-06-19
DOI
https://doi.org/10.7771/3067-4883.1418
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.43
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article

Brain Activity Patterns While Viewing Construction Signs: AN EEG Study of Attention and Memory Encoding

Minghao Dong, Behzad Esmaeili, Yu‐Chin Chiu
1 citations
CIB Conferences
EEG and Brain-Computer Interfaces
1.43
article

Brain Activity Patterns While Viewing Construction Signs: AN EEG Study of Attention and Memory Encoding

Minghao Dong, Behzad Esmaeili, Yu‐Chin Chiu
article en
1 citations

Abstract

To support efforts to improve safety communication within a construction setting, this study investigated the neural correlates of attention and memory encoding from subjects viewing construction signs to observe whether neural oscillations during viewing relate to participants’ subsequent recall of the safety information. The study recruited seventeen participants with construction-related backgrounds and collected electroencephalography (EEG) data as participants viewed construction signs. A subsequent memory test using hit rates categorized participants into groups with excellent versus poor memory of the signs. Event-related time-frequency analyses examined frontal gamma (associated with attention) and prefrontal theta (associated with memory encoding) oscillations as a function of the two groups. Results indicate that participants with excellent memory performance exhibited significantly higher frontal gamma activity during the 900–1000 ms post-stimulus window, suggesting enhanced attentional engagement. In contrast, participants with poor memory performance showed elevated prefrontal theta activity during the 800–1000 ms window, indicative of increased cognitive effort and less-efficient memory encoding. No significant differences manifest in the parietal alpha and temporal theta between the two groups. These findings highlight the importance of attentional processes and efficient memory encoding when comprehending construction signs, with design implications (i.e., pictogram + text condition) for more effective safety signage to improve workers' cognitive processing and memory retention.

CIB ConferencesVol. 1(1)
Purdue University West Lafayette (US)
Sustainable cities and communities
Openalex Percentile: Top 18%
EEG and Brain-Computer Interfaces
1.43
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