A study of dynamic functional connectivity changes in flight trainees based on a triple network model
Abstract The time-varying functional connectivity of the Central Executive Network (CEN), Default Mode Network (DMN), and Salience Network (SN) in flight trainees during a resting state was investigated using dynamic functional network connectivity (dFNC). The study included 39 flight trainees and 3...
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Nature Portfolio
2025-03-01
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| Online Access: | https://doi.org/10.1038/s41598-025-89023-y |
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| author | Lu Ye¹ Liya Ba¹ Dongfeng Yan¹ |
| author_facet | Lu Ye¹ Liya Ba¹ Dongfeng Yan¹ |
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| description | Abstract The time-varying functional connectivity of the Central Executive Network (CEN), Default Mode Network (DMN), and Salience Network (SN) in flight trainees during a resting state was investigated using dynamic functional network connectivity (dFNC). The study included 39 flight trainees and 37 age- and sex-matched healthy controls. Resting-state fMRI data and behavioral test outcomes were obtained from both groups. Independent component analysis (ICA), sliding window, and K-means clustering approaches were utilized for evaluating functional network connectivity (FNC) and temporal metrics based on the triple networks. Correlation analyses were performed on the behavioral assessments and these metrics. The flight trainees demonstrated a significantly enhanced functional connection linking the CEN and DMN in state 2 (P < 0.05, FDR corrected). Additionally, flight trainees spent less time in state 5, while they exhibited a protracted mean dwell time and fractional windows in state 2, which were significantly correlated with accuracy on the Berg Card Sorting Test (BCST) and Change Detection Test (all P < 0.05). The improved connectivity of flight trainees between the CEN and DMN following the completion of rigorous flight training resulted in increased stability. This enhancement may be relevant to cognitive abilities such as decision-making, memory, and information integration. When multitasking, flight trainees displayed superior visual processing skills and enhanced cognitive flexibility. dFNC research provides a unique perspective on the sophisticated cognitive capabilities that are required in high-demand, high-stress occupations such as piloting, thereby providing significant insights into the intricate brain mechanisms that are inherent in these domains. |
| format | Article |
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| spelling | doaj-art-8785a216d3dd494caf0e7aafc9bcfd3c2025-08-20T03:05:53ZengNature PortfolioScientific Reports2045-23222025-03-0115111210.1038/s41598-025-89023-yA study of dynamic functional connectivity changes in flight trainees based on a triple network modelLu Ye¹0Liya Ba¹1Dongfeng Yan¹2¹Institute of Flight Technology, Civil Aviation Flight University of China¹Institute of Flight Technology, Civil Aviation Flight University of China¹Institute of Flight Technology, Civil Aviation Flight University of ChinaAbstract The time-varying functional connectivity of the Central Executive Network (CEN), Default Mode Network (DMN), and Salience Network (SN) in flight trainees during a resting state was investigated using dynamic functional network connectivity (dFNC). The study included 39 flight trainees and 37 age- and sex-matched healthy controls. Resting-state fMRI data and behavioral test outcomes were obtained from both groups. Independent component analysis (ICA), sliding window, and K-means clustering approaches were utilized for evaluating functional network connectivity (FNC) and temporal metrics based on the triple networks. Correlation analyses were performed on the behavioral assessments and these metrics. The flight trainees demonstrated a significantly enhanced functional connection linking the CEN and DMN in state 2 (P < 0.05, FDR corrected). Additionally, flight trainees spent less time in state 5, while they exhibited a protracted mean dwell time and fractional windows in state 2, which were significantly correlated with accuracy on the Berg Card Sorting Test (BCST) and Change Detection Test (all P < 0.05). The improved connectivity of flight trainees between the CEN and DMN following the completion of rigorous flight training resulted in increased stability. This enhancement may be relevant to cognitive abilities such as decision-making, memory, and information integration. When multitasking, flight trainees displayed superior visual processing skills and enhanced cognitive flexibility. dFNC research provides a unique perspective on the sophisticated cognitive capabilities that are required in high-demand, high-stress occupations such as piloting, thereby providing significant insights into the intricate brain mechanisms that are inherent in these domains.https://doi.org/10.1038/s41598-025-89023-yFlight traineesResting-state fMRIDynamic functional network connectivityIndependent component analysis |
| spellingShingle | Lu Ye¹ Liya Ba¹ Dongfeng Yan¹ A study of dynamic functional connectivity changes in flight trainees based on a triple network model Scientific Reports Flight trainees Resting-state fMRI Dynamic functional network connectivity Independent component analysis |
| title | A study of dynamic functional connectivity changes in flight trainees based on a triple network model |
| title_full | A study of dynamic functional connectivity changes in flight trainees based on a triple network model |
| title_fullStr | A study of dynamic functional connectivity changes in flight trainees based on a triple network model |
| title_full_unstemmed | A study of dynamic functional connectivity changes in flight trainees based on a triple network model |
| title_short | A study of dynamic functional connectivity changes in flight trainees based on a triple network model |
| title_sort | study of dynamic functional connectivity changes in flight trainees based on a triple network model |
| topic | Flight trainees Resting-state fMRI Dynamic functional network connectivity Independent component analysis |
| url | https://doi.org/10.1038/s41598-025-89023-y |
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