The present invention relates to predictive neuromarkers of Alzheimer's disease comprising at least one spectral feature obtained from EEG signals of a subject； and at least one Riemannian distance between a spatiofrequential covariance matrix computed from the EEG signals of said subject and at least one reference spatiofrequential covariance matrix. The present invention also relates to a non-invasive method of diagnosing the presence of Alzheimer's disease in a subject using the predictive neuromarkers of Alzheimer's disease； and to a method for self-paced modulation of EEG signals of a subject in order to alleviate symptoms of Alzheimer's disease using the predictive neuromarkers of Alzheimer's disease.
