Evidence map›Paper›PMID 36979183›Full record

ArticleBrain sciences2023

Efficiency of the Brain Network Is Associated with the Mental Workload with Developed Mental Schema.

Heng Gu, He Chen, Qunli Yao, Wenbo He, Shaodi Wang, Chao Yang, Jiaxi Li, Huapeng Liu, Xiaoli Li, Xiaochuan Zhao and 1 more

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Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

11 authors.

Heng GuCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
He ChenCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
Qunli YaoCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
Wenbo HeCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
Shaodi WangCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
Chao YangCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
Jiaxi LiCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.
Huapeng LiuInstitute of Computer Applied Technology of China North Industries Group Corporation Limited, Beijing 100821, China.
Xiaoli LiCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.ORCID 0000-0003-1359-5130
Xiaochuan ZhaoInstitute of Computer Applied Technology of China North Industries Group Corporation Limited, Beijing 100821, China.
Guanhao LiangCenter for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China.

Funding

the National Defense Basic Scientific Research Program of China JCKY2019208C025
6 · The paper itself

Abstract

The study of mental workload has attracted much interest in neuroergonomics, a frontier field of research. However, there appears no consensus on how to measure mental workload effectively because the mental workload is not only regulated by task difficulty but also affected by individual skill level reflected as mental schema. In this study, we investigated the alterations in the functional brain network induced by a 10-day simulated piloting task with different difficulty levels. Topological features quantifying global and local information communication and network organization were analyzed. It was found that during different tests, the global efficiency did not change, but the gravity center of the local efficiency of the network moved from the frontal to the posterior area; the small-worldness of the functional brain network became stronger. These results demonstrate the reconfiguration of the brain network during the development of mental schema. Furthermore, for the first two tests, the global and local efficiency did not have a consistent change trend under different difficulty levels, but after forming the developed mental schema, both of them decreased with the increase in task difficulty, showing sensitivity to the increase in mental workload. Our results demonstrate brain network reconfiguration during the motor learning process and reveal the importance of the developed mental schema for the accurate assessment of mental workload. We concluded that the efficiency of the brain network was associated with mental workload with developed mental schema.

Indexed as

functional brain networkglobal efficiencylocal efficiencymental schemamental workloadsmall-worldness

Identifiers

PMID36979183
PMCPMC10046556

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