Neurofeedback training based fNIRS enhances the flight performance of pilots during long-term flight
Poster No:
43
Submission Type:
Abstract Submission
Authors:
Mengshan Li1,2, Wenchao Zhang1,2, Guanya Li1,2, Yang Hu1,2, Yi Zhang1,2
Institutions:
1Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China, 2International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
First Author:
Mengshan Li
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Co-Author(s):
Wenchao Zhang
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Guanya Li
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Yang Hu
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Yi Zhang
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education|International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University
Xi'an, Shaanxi 710126, China|Xi'an, Shaanxi 710126, China
Introduction:
Long-term flight missions cause cognitive fatigue in pilots, leading to flight illusions, sluggish responses, and other problems, which could result in serious flight accidents. It's an emergency to develop techniques to alleviate cognitive fatigue in pilots. Neurofeedback training (NFT) based on functional near-infrared spectroscopy (fNIRS) is an endogenous neuromodulation that could improve spatial working memory, attention performance through regulating brain regional activity in healthy participants (Li, 2023), and sustained attention in children with attention deficit hyperactivity disorder (Janssen, 2017; Wu, 2022). However, whether NFT could alleviate cognitive fatigue and enhance pilots' long-term flight performance remains unclear. Thus, the current study aims to investigate the effectiveness of NFT in improving long-term flight performance of pilots. Furthermore, it is worth noting that the feedback signals in NFT are critical for the modulation effect. Activity in the dorsolateral prefrontal cortex (DLPFC) was chosen as the feedback signal because it plays an important role in various cognitive functions, including attention and memory (Barbey, 2013; Michel, 2024) and is associated with skill in successfully flying an aircraft (Gougelet, 2020).
Methods:
The current study recruited twenty-four pilots (male = 24, age = 19.01 ± 0.24 years) from Xi'an Aeronautical Institute. On the first day, participants performed a 1-hour airfield traffic pattern task to evaluate their long-time flight performance (Fig.1 (A)). The Shimadzu LABNIRS device collected the participant's brain activity, and optrodes were placed on the frontal-parietal brain regions according to the international 10-20 system (Fig.1 (B)). Then, the participants were randomly assigned to the neurofeedback group (NF) and control group. The NF group engaged in NFT once daily for the next five days, while the control group received no intervention. NFT included resting and training phases, and participants watched at "+" on the screen during the resting phase, and searched for the numbers for a 5×5 Schulte Grid shown on the screen during the training phase (Fig.1 (C)). The level of numerical ambiguity varied based on the activation strength of DLPFC (CH1, 5, 6, 11). Participants were required to quickly search for numerical order while improving their clarity, reflecting the increased activation of DLPFC. Finally, both groups performed the 1-hour airfield traffic pattern task again to assess the long-time flight performance. An ANOVA analysis was utilized to investigate the impact of NFT on pilots' long-time flight performance and brain function.
Results:
There was no difference in long-time flight performance between NF and Control groups at baseline. NFT significantly enhanced the final approach's performance (t = 3.635, P = 0.004) and total performance (t = 2.841, P = 0.016) of NF group in the long-time flight task, while there was no difference in control group. After NFT, the total performance of NF group was significantly higher than that of control group (t = 3.060, P = 0.035, Fig.2 (A)).
NFT significantly increased the activation of frontal lobe (t = 2.562, P = 0.023) in NF group, which was significantly higher than that of Control group at PostNF (t = 2.148, P = 0.034). The activity of frontal lobe was positively correlated with the crosswind leg's performance at PreNF (r = 0.540, P = 0.035), as well as the performance of down leg at PostNF (r = 0.524, P = 0.040). In addition, there was a significant increase in functional connectivity between the frontal and parietal lobes (t = 3.842, P = 0.002) in NF group which is higher than that in Control group at PostNF (t = 2.221, P = 0.034, Fig.2 (B)).
NFT significantly increased the activation of frontal lobe (t = 2.562, P = 0.023) in NF group, which was significantly higher than that of Control group at PostNF (t = 2.148, P = 0.034). The activity of frontal lobe was positively correlated with the crosswind leg's performance at PreNF (r = 0.540, P = 0.035), as well as the performance of down leg at PostNF (r = 0.524, P = 0.040). In addition, there was a significant increase in functional connectivity between the frontal and parietal lobes (t = 3.842, P = 0.002) in NF group which is higher than that in Control group at PostNF (t = 2.221, P = 0.034, Fig.2 (B)).
Conclusions:
The current study demonstrated that fNIRS-based NFT could promote flight performance through enhancing the activity of frontal lobe and its functional connectivity with parietal lobe during long-term missions.
Brain Stimulation:
Non-Invasive Stimulation Methods Other 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Novel Imaging Acquisition Methods:
NIRS 2
Keywords:
Other - Neurofeedback; fNIRS; pilots; flight performance
1|2Indicates the priority used for review
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Gougelet, R. J. (2020). Cerebellum, Basal Ganglia, and cortex mediate performance of an Aerial Pursuit Task. Frontiers in Human Neuroscience, 14, 29.
Janssen, T. (2017). Learning curves of theta/beta neurofeedback in children with ADHD. European Child & Adolescent Psychiatry, 26(5), 573-582.
Li, K. (2023). Functional near-infrared spectroscopy neurofeedback of dorsolateral prefrontal cortex enhances human spatial working memory. Neurophotonics, 10(2), 25011.
Michel, C. A. (2024). Neural correlates of deceased-related attention during acute grief in suicide-related bereavement. Journal of Affective Disorders, 347, 285-292.
Wu, W. J. (2022). A parallel-group study of near-infrared spectroscopy-neurofeedback in children with attention deficit hyperactivity disorder. Psychiatry Research, 309, 114364.