Predicting subject traits from brain spectral signatures

CECILIA JARNE; DIEGO VIDAURRE

Oxford

Exposición; Group Talk for the Oxford Centre for Human Brain Activity Analysis Group; 2023

Oxford Centre for Human Brain Activity, Department of Psychiatry, Oxford Universit

We presented the preliminary results of our mathematically principled method to predict subject traits from M/EEG spectrograms. The idea is to interpret a spectrogram as a probability distribution and apply the Kernel Mean Embedding of distributions, a powerful kernel-based approach that takes probability distributions as inputs. Focusing on both accuracy and robustness, we demonstrate its use and improvement for age estimation over a baseline method like ridge regression by leveraging the HarMNqEEG dataset—a multinational compilation of EEG recordings—, which we assessed using leave-one-country-out cross-validation.”