OPM-FLUX: A Pipeline for OPM MEG Data Analysis

Abstract

Optically pumped magnetometer-based magnetoencephalography (OPM-MEG) has recently emerged as a powerful neuroimaging approach in cognitive neuroscience, extending beyond the limitations of conventional cryogenic systems with greater experimental flexibility and wearable recording. Despite these advantages, standardised data analysis frameworks specifically tailored to OPM technology are still lacking, leading to variability in processing choices and reduced reproducibility across laboratories and hardware platforms. We introduce OPM-FLUX, a comprehensive and fully documented end-to-end analysis pipeline developed for OPM-MEG data. The pipeline defines a clear sequence of preprocessing, noise suppression, artifact handling, spectral analysis, evoked response analysis along with recommended parameter settings. It also includes source reconstruction to identify where in the brain the signals originate. In addition, OPM-FLUX supports multivariate pattern analysis (MVPA), enabling time-resolved decoding of cognitive processes from sensor level data. OPM-FLUX is implemented in MNE-Python and distributed as interactive Jupyter Notebooks that combine executable code with detailed methodological explanations and graphical outputs. The pipeline further provides standardized reporting templates and a data acquisition Standard Operating Procedure to facilitate preregistration, consistent documentation, and standard practices across research sites. The workflow is demonstrated using openly available datasets acquired from both Cerca/QuSpin and FieldLine OPM systems during a visuospatial attention paradigm that modulates alpha, beta, and gamma oscillations and elicits event-related responses. By supporting multiple OPM platforms and promoting consistent methodological choices, OPM-FLUX enhances transparency, comparability, and replication in OPM-MEG research. The pipeline also serves as an educational resource for students and researchers entering the field and is designed to evolve alongside ongoing technological and methodological advances in OPM-based brain imaging.