Cross Time Coherence Mapping Gradient Analysis for Alzheimer's Disease Assessment

These findings reveal significant alterations in CTCM gradients across NC, MCI, and AD, reflecting the progressive dysconnectivity in AD. Key networks, including the Default Mode, Dorsal Attention, Salience, and Limbic networks, exhibited marked differences. Combining CTCM gradients with demographic features demonstrates strong potential as a biomarker for AD progression and classification, offering new insights for diagnosis and understanding disease mechanisms.