Sofie S. Meyer

This paper introduces myelin-informed forward models for M/EEG source reconstruction, showing improved accuracy using myelin density estimates from MRI.

This paper investigates the use of mouth-based sensors in magnetoencephalography (MEG) to study the human hippocampus, finding that mouth sensors show unique task-related activity and anti-correlation with temporal lobe sensors.

This study investigates how the brain plans motor sequences by analyzing MEG data, finding that competitive queuing of sequential representations predicts performance accuracy.

The paper evaluates MEG source reconstruction methods using resting state data, finding that the Empirical Bayesian Beamformer provides the best anatomical discrimination.

This paper compares MEG source inversion algorithms and fit metrics to determine the laminar origin of neural activity, finding that sparsity-constrained methods and specific fit metrics improve discrimination accuracy.

The paper uses MEG to show laminar-specific frequency activity in human visual and sensorimotor cortices, with distinct roles for alpha/beta and gamma bands.