Maciej J Szul

The paper investigates how beta bursts in the supplementary motor area (SMA) are linked to anticipatory muscle inhibition during voluntary load-lifting.

The paper develops a beta burst extraction pipeline using Helium-OPMs to study motor preparation and execution, finding similar waveform patterns to SQUID-MEG with task-related modulations.

This paper introduces a multilayer MEG source modelling framework to enable depth-resolved laminar inference in humans, showing it aligns with known neural circuit motifs.

This paper introduces a new method, lagged Hilbert autocoherence (LHaC), to better quantify neural rhythmicity compared to existing Fourier-based methods.

The paper investigates beta burst activity in motor imagery tasks, showing that burst-based features can match or exceed traditional beta power methods in decoding brain signals.

This paper improves motor imagery-based BCI by analyzing beta burst waveforms instead of beta power, showing better classification performance and information transfer rates.

The paper examines how sensorimotor beta burst activity develops from infancy to adulthood using EEG recordings and a novel analysis method.

The paper identifies diverse beta burst waveform motifs in human MEG data during movement tasks and shows they reflect distinct computational processes.

This study evaluates six source reconstruction algorithms for resting-state MEG, finding that eLORETA provides zero localization error, high spatial resolution, and superior sensor-level activity prediction.

The paper shows that individual variability in brain connectivity is consistent across modalities and linked to microstructural properties.

This study compares perceptual decision-making using joystick movements and key presses, finding no significant difference in accuracy or reaction time, and no effect on decision processes.