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• The Schrödinger Bridge Problem (SBP) provides a principled probabilistic framework to model the most efficient evolution between brain states, interpreted as a measure of cognitive energy cost.method 95%
• Using SBP-derived transport cost as a metric shows that GAN-generated EEG retains the distributional geometry necessary for energy-based modeling of cognitive state transitions.method 90%
• Transition energies derived from real and synthetic EEG collected during Stroop tasks demonstrate strong agreement across group and participant-level analyses.result 90%
• Synthetic EEG preserves the transition structure required for SBP-based modeling, enabling its use in data-efficient neuroadaptive systems.result 85%
• SBP-derived cognitive energy can serve as a control signal for adaptive human-machine systems, supporting real-time adjustment of system behavior.technical 80%
• Modeling how cognitive and emotional states evolve in real time and quantifying the energy required for such transitions remains a major challenge.limitation 95%
• It remains unclear whether synthetic EEG preserves the underlying dynamical structure required for transition-based analysis.limitation 90%
• The proposed framework supports real-time adjustment of system behavior in response to user cognitive and affective state.technical 75%

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