A reusable benchmark of brain-age prediction from M/EEG resting-state signals

A reusable benchmark of brain-age prediction from M/EEG resting-state signals

Population-level modeling can define quantitative measures of individual aging by applying machine learning to large volumes of brain images. These measures of brain age, obtained from the general population, helped characterize disease severity in neurological populations, improving estimates of di...

Full description

Bibliographic Details
Main Authors: Denis A. Engemann, Apolline Mellot, Richard Höchenberger, Hubert Banville, David Sabbagh, Lukas Gemein, Tonio Ball, Alexandre Gramfort
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:NeuroImage
Subjects:
Clinical neuroscience
Brain age
Electroencephalography
Magnetoencephalography
Machine learning
Population modeling
Online Access:http://www.sciencedirect.com/science/article/pii/S105381192200636X

Internet

http://www.sciencedirect.com/science/article/pii/S105381192200636X

Similar Items