Sleep Brain and Cardiac Activity Predict Cognitive Flexibility and Conceptual Reasoning Using Deep Learning

This study introduces CogPSGFormer, a multi-modal deep learning model that predicts individual cognitive performance, such as executive functions, based on sleep microstructure data from ECG and EEG signals. Evaluated on 817 participants, the model achieved 80.3% accuracy in classifying cognitive performance levels, demonstrating the potential of sleep-derived physiological signals for cognitive assessment.