2 papers
cs.LG2021
On the interpretation of linear Riemannian tangent space model parameters in M/EEG
Reinmar J. Kobler, Jun-Ichiro Hirayama, Lea Hehenberger Catarina Lopes-Dias +2
Riemannian tangent space methods offer state-of-the-art performance in magnetoencephalography (MEG) and electroencephalography (EEG) based applications such as brain-computer inter…
stat.AP2019
Interpretable brain age prediction using linear latent variable models of functional connectivity
Ricardo Pio Monti, Alex Gibberd, Sandipan Roy +6
Neuroimaging-driven prediction of brain age, defined as the predicted biological age of a subject using only brain imaging data, is an exciting avenue of research. In this work we…