The present research aims to investigate changes in trainees’ cognitive control levels during a pilot training process while they underwent basic flight maneuvers. EEG microstate analysis was applied together with spectral power features to quantitatively monitor trainees’ cognitive control under varied flight tasks during different training sessions. Comparisons were conducted between two types of tasks and among different training stages in terms of trainees' cognitive control.

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Mengting Zhao 8b2c7d4e8b Delete 'pre-processing/pre-process/BioSemi64.loc'		1 月之前
bandpower	6967b869bf Upload files to ''	1 月之前
microstates	9261af0552 Upload files to ''	1 月之前
LICENSE	72c78fa0c6 Initial commit	2 月之前
README.md	46851e5413 Update 'README.md'	1 月之前
datacite.yml	689bae07b3 Update 'datacite.yml'	1 月之前

Monitoring-pilot-trainees-cognitive-control-under-a-simulator-based-training-process

Description

This repository contains software for analyzing EEG data to investigate changes in cognitive control levels in pilot trainees during a training process involving basic flight maneuvers. The code is specifically tailored for applying EEG microstate analysis and spectral power feature extraction to monitor cognitive control under various flight tasks across multiple training sessions.

Data format

The software is designed to work with EEG data recorded using the 64-channel Biosemi system. The data should contain 64 channels labeled appropriately according to the Biosemi convention. Please ensure the data has undergone basic preprocessing before using it with this software.

Installation and Requirements

The code in this repository was developed and tested using Python 3.8. It is recommended to use a similar or newer version to ensure compatibility.

Dependencies

MNE: For EEG data handling and preprocessing. NumPy: For numerical operations. SciPy: For statistical analysis. Matplotlib: For visualizing EEG data.

datacite.yml
Title	Monitoring pilot trainees’ cognitive control under a simulator-based training process with EEG microstate analysis
Authors	Zhao,Mengting;Concordia University Jia,Wenjun;Concordia University Jennings,Sion;National Research Council of Canada Law,Andrew;National Research Council of Canada Bourgon,Alain;CAE Inc. Su,Chang;Concordia University Larose,Marie-Helene;Marinvent Corporation Grenier,Hugh;CAE Inc. Bowness,David;CAE Inc. Zeng,Yong;Concordia University
Description	The present codes aim to monitor variations in pilot trainees’ cognitive control during a pilot training process using EEG microstate analysis and traditional bandpower.
License	Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References
Funding	NSERC CRD project Mitacs Accelerate program
Keywords	Cognitive control pilot training EEG microstate analysis
Resource Type	Software

README.md

Monitoring-pilot-trainees-cognitive-control-under-a-simulator-based-training-process

Description

Data format

Installation and Requirements

Dependencies