title: Realignment of magnetoencephalographic data for group analysis in the sensor domain.
abstract: Magnetoencephalography (MEG) is a neuroimaging modality with high temporal resolution for studying functional brain processes in relatively small neural assemblies on the time scale of <100 milliseconds and with synchrony and coherence in the recorded signals at high frequencies. Advanced MEG signal analysis gained importance for clinical applications, e.g., as a sensitive classifier for the diagnosis of neuropsychiatric disorders. Despite tremendous improvements in magnetic source imaging, MEG analysis often does not require explicit source estimation and can be performed in the sensor domain. However, group analysis of MEG sensor data is complicated by variable positioning of the sensor array relative to the head and needs realignment of the sensor configuration. Here, the authors provide an algorithm for transforming the magnetic field data as recorded at various sensor positions onto a common sensor array. Based on the measured magnetic field at the original sensor position, they estimate a source distribution and project it onto a virtual sensor array using the leadfield description of the magnetic forward solution. First, they analyzed the variation of sensor positioning in a typical MEG study and reported the impact on the leadfield matrix. Then they evaluated the realignment algorithm and reported its properties. Including efficient regularization to the inverse solution, they demonstrated that the introduced error is in the order of the sensor noise, and smoothing of data is limited to the set of smallest eigenvalues of the data. They demonstrated the performance of the algorithm with dipole source modeling on group averaged MEG data and comparison of grand averaged auditory evoked responses with and without sensor realignment.
authors.affiliation: Rotman Research Institute, Baycrest Centre, 3560 Bathurst Street, Toronto, Ontario, Canada. bross@rotman-baycrest.on.ca
authors.forename: Bernhard
authors.initials: B
authors.lastname: Ross
authors.forename: Rebecca E M
authors.initials: RE
authors.lastname: Charron
authors.forename: Shahab
authors.initials: S
authors.lastname: Jamali
mesh_terms: D000161:Acoustic Stimulation; D000328:Adult; D000368:Aged; D000465:Algorithms; D003198:Computer Simulation; D004867:Equipment Design; D005072:Evoked Potentials, Auditory; D057918:Fiducial Markers; D006257:Head / Q000033:anatomy & histology*; D019416:Head Movements; D006801:Humans; D015225:Magnetoencephalography / Q000295:instrumentation*; D008875:Middle Aged; D008962:Models, Theoretical; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D014159:Transducers; D055815:Young Adult