OPM-FLUX: A Pipeline for OPM MEG Data Analysis

Opfically pumped magnetometer-based magnetoencephalography (OPM-MEG) has recently emerged as a powerful neuroimaging approach in cognifive neuroscience, extending beyond the limitafions of convenfional cryogenic systems with greater experimental flexibility and wearable recording. Despite these advantages, standardised data analysis frameworks specifically tailored to OPM technology are sfill lacking, leading to variability in processing choices and reduced reproducibility across laboratories and hardware plafforms. 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, arfifact handling, spectral analysis, evoked response analysis along with recommended parameter seftings. It also includes source reconstrucfion to idenfify where in the brain the signals originate. In addifion, OPM-FLUX supports mulfivariate paftern analysis (MVPA), enabling fime-resolved decoding of cognifive processes from sensor level data. OPM-FLUX is implemented in MNE-Python and distributed as interacfive Jupyter Notebooks that combine executable code with detailed methodological explanafions and graphical outputs. The pipeline further provides standardized reporfing templates and a data acquisifion Standard Operafing Procedure to facilitate preregistrafion, consistent documentafion, and standard pracfices across research sites. The workflow is demonstrated using openly available datasets acquired from both Cerca/QuSpin and FieldLine OPM systems during a visuospafial aftenfion paradigm that modulates alpha, beta, and gamma oscillafions and elicits event-related responses. By supporfing mulfiple OPM plafforms and promofing consistent methodological choices, OPM-FLUX enhances transparency, comparability, and replicafion in OPM-MEG research. The pipeline also serves as an educafional resource for students and researchers entering the field and is designed to evolve alongside ongoing technological and methodological advances in OPM-based brain imaging.