Time-varying EEG spectral power predicts evoked and spontaneous fMRI motor brain activity
Journal:
arXiv
Published Date:
Apr 14, 2025
Abstract
Simultaneous EEG-fMRI recordings are increasingly used to investigate brain
activity by leveraging the complementary high spatial and high temporal
resolution of fMRI and EEG signals respectively. It remains unclear, however,
to what degree these two imaging modalities capture shared information about
neural activity. Here, we investigate whether it is possible to predict both
task-evoked and spontaneous fMRI signals of motor brain networks from EEG
time-varying spectral power using interpretable models trained for individual
subjects with Sparse Group Lasso regularization. Critically, we test the
trained models on data acquired from each subject on a different day and obtain
statistical validation by comparison with appropriate null models as well as
the conventional EEG sensorimotor rhythm. We find significant prediction
results in most subjects, although less frequently for resting-state compared
to task-based conditions. Furthermore, we interpret the model learned
parameters to understand representations of EEG-fMRI coupling in terms of
predictive EEG channels, frequencies, and haemodynamic delays. In conclusion,
our work provides evidence of the ability to predict fMRI motor brain activity
from EEG recordings alone across different days, in both task-evoked and
spontaneous conditions, with statistical significance in individual subjects.
These results present great potential for translation to EEG neurofeedback
applications.
