Evidence map›Paper›PMID 41394942›Full record

ArticleFrontiers in human neuroscience2025

Impact of visual distractors in virtual reality environments on sustained attention behavioral performance and EEG characteristics.

Xiaowen Ai, Yuhao Wang, Peng Wang, Suogang Wang

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xiaowen AiNeuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
Yuhao WangNeuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
Peng WangInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China.
Suogang WangNeuroengineering Laboratory, School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: This study investigates the effects of visual distractors in virtual reality (VR) environments on sustained attention, focusing on how visual distraction modulates neural mechanisms of attentional allocation and regulation. Methods: Behavioral and electroencephalographic (EEG) data were collected from 66 participants performing a Go/No-go continuous performance test (CPT) in a virtual classroom under conditions with (Y-D) and without (N-D) visual distractors. We analyzed behavioral performance (commission/omission errors, multipress, reaction time), event-related potential (P300) characteristics (latency, amplitude), and nonlinear dynamics (sample entropy, fuzzy entropy) of the EEG signals. Results: Behavioral results revealed that visual distractors significantly increased commission errors, omission errors, and multipress (all Discussion: These findings indicate that visual distractors disrupt cognitive processes related to visual information integration, attentional control, and decision-making, leading to decreased behavioral performance and increased neural complexity. This study deepens the understanding of the neural mechanisms of attention processing under ecological conditions and provides a scientific basis for optimizing educational environments and developing attention assessment tools based on neuroengineering.

Indexed as

EEGentropyP300sustained attentionvirtual realityvisual distractors

Identifiers

PMID41394942
PMCPMC12698649

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.