A novel neurophysiological approach to evaluate the impact of virtual training on skills acquisition

Objective. Objective evaluation of operational training remains challenging, particularly when comparing physical training with virtual reality (VR) training. Behavioral and subjective measures capture performance and perceived workload but provide limited insight into the underlying neurocognitive adaptation. This study proposes and validates a synthetic EEG-derived cognitive training index (CTI) that integrates multiple training-sensitive neurometrics into a single composite metric, with two aims: to validate CTI as an objective marker of training progression in a physical training group, and to test whether VR-based training leads to neurocognitive adaptation comparable to physical training when participants subsequently execute the task in the real environment. Approach. Participants completed three repetitions of a realistic confined-space industrial maintenance procedure structured into Entrance, Rolling shutter, and Pipe replacement phases. Behavioral outcomes (execution time, procedural errors) and subjective workload NASA Task Load Index (NASA-TLX) were collected after each trial. Wearable EEG was recorded continuously; six neurometrics were computed from cleaned EEG using band-specific Global Field Power over predefined electrode sets. CTI was obtained via principal component analysis applied at the trial level to the multivariate neurometric time series, followed by segment-wise analysis. Temporal specificity of CTI was assessed through phase-randomized surrogate-data analyses. Main results. Execution time decreased across trials (F = 14.82, p <.001, η2p = 0.35), procedural errors decreased similarly (F = 10.31, p <.001, η2p = 0.27), and NASA-TLX declined (F = 11.94, p <.001, η2p = 0.30). CTI increased significantly with training (F = 18.21, p <.001, η2p = 0.39) and was selectively higher in learning-relevant phases (Entrance and Pipe replacement), while remaining near baseline in the low-demand Rolling shutter phase. Surrogate analyses showed that real CTI exceeded null expectations, supporting temporal specificity. Repeated-measures correlations indicated significant negative associations between CTI and procedural errors (R = − 0.42, p <.01) and between CTI and NASA-TLX (R = − 0.38, p <.01), while CTI was not significantly related to execution time (R = 0.18, p =.12). Significance. CTI provides a psychologically grounded, multivariate EEG marker that tracks training progression and aligns with operationally meaningful outcomes, namely procedural accuracy and perceived workload, rather than task speed alone. This approach supports objective comparison of cognitive adaptation across training modalities and provides a practical basis for neurophysiologically informed training evaluation and future adaptive training systems.