TY - JOUR T1 - Are Sources of EEG and MEG rhythmic activity the same? An analysis based on BC-VARETA JF - bioRxiv DO - 10.1101/748996 SP - 748996 AU - Qi Yuan AU - Usama Riaz AU - Fuleah A. Razzaq AU - Pedro A. Valdes-Sosa Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/08/29/748996.abstract N2 - In the resting state (closed or open eyes) electroencephalogram (EEG) and the magnetoencephalogram (MEG), rhythmic brain activity is very evident, typically the 10 Hz alpha rhythm. It has a topographic frequency spectral distribution that is, at first sight, quite similar for both modalities--something not surprising since both EEG and MEG are generated by the same basic oscillations in thalamocortical circuitry which produce primary current densities (PCD). However, different aspects (divergence and curl) of this PCD vector field underpin the two types of signals. Does this difference lead to a different distribution of reconstructed sources for EEG and MEG rhythms? This question is important for the transferal of results from one imaging modality to the other but has surprisingly received scant attention till now. We address this issue by comparing eyes open EEG source spectra recorded from 77 subjects from the Cuban Human Brain Mapping project with the MEG of 63 subjects from the Human Connectome Project. Source spectra for each voxel and frequency were obtained via a novel sparse-covariance inverse method: BC-VARETA based on individualized BEM head models with subject-specific regularization parameters (noise to signal ratio). While curtailing source leakage, the sparse BC VARETA estimator produces a large number of zero activations (zero inflation or ZI) which generates severe problems for traditional statistical methods. We circumvent the ZI problems by employing a novel dimensionality reduction technique known as Zero-inflated Factor Analysis (ZIFA). Both minimum energy and Hotelling’s T-2 tests showed that ZIFA scores for MEG and EEG sources were significantly different at all frequency bands. These results exclude a simple identification of the MEG and EEG sources of resting-state EEG rhythms. Further study is required to determine the relative contribution of instrumental, physical or physiological mechanisms to these differences. ER -