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Updated: Apr 10, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Spectral dynamic causal modeling of effective connectivity across multiple brain networks in pilot trainees
Lu Ye1,2, Yang Zhang1, Dongfeng Yan1
1Civil Aviation Flight University of China, Deyang, Sichuan, China.
None:
Pilots operate in complex, time-varying environments, relying on specific causal brain-network dynamics to support their cognitive skills. Resting-state functional magnetic resonance imaging and structural imaging were collected from healthy male flight cadets (n = 39) and healthy male controls (n = 37), alongside a card-sorting measure of executive function and a visual change-detection task. Spectral dynamic causal modeling with hierarchical Bayesian inference was used to quantify effective connectivity within and between large-scale networks. Compared with controls, flight cadets exhibited significant differences in within-network and between-network effective connectivity spanning the default mode, sensorimotor, ventral attention, dorsal attention, and visual networks. Connectivity-behavior relationships also differed between groups, including a flight-cadet-specific positive association within the ventral attention network. These findings link long-term flight training with distinctive patterns of brain-network causal interactions related to executive performance, and offer a potential biological perspective for understanding neuroadaptation during early-stage flight training and for informing training optimization.
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