%A Henson,Richard N. %A Abdulrahman,Hunar %A Flandin,Guillaume %A Litvak,Vladimir %D 2019 %J Frontiers in Neuroscience %C %F %G English %K MEG,EEG,fMRI,multimodal,Fusion,SPM,inversion %Q %R 10.3389/fnins.2019.00300 %W %L %M %P %7 %8 2019-April-24 %9 Methods %# %! Data Fusion in SPM12 %* %< %T Multimodal Integration of M/EEG and f/MRI Data in SPM12 %U https://www.frontiersin.org/articles/10.3389/fnins.2019.00300 %V 13 %0 JOURNAL ARTICLE %@ 1662-453X %X We describe the steps involved in analysis of multi-modal, multi-subject human neuroimaging data using the SPM12 free and open source software (https://www.fil.ion.ucl.ac.uk/spm/) and a publically-available dataset organized according to the Brain Imaging Data Structure (BIDS) format (https://openneuro.org/datasets/ds000117/). The dataset contains electroencephalographic (EEG), magnetoencephalographic (MEG), and functional and structural magnetic resonance imaging (MRI) data from 16 subjects who undertook multiple runs of a simple task performed on a large number of famous, unfamiliar and scrambled faces. We demonstrate: (1) batching and scripting of preprocessing of multiple runs/subjects of combined MEG and EEG data, (2) creation of trial-averaged evoked responses, (3) source-reconstruction of the power (induced and evoked) across trials within a time-frequency window around the “N/M170” evoked component, using structural MRI for forward modeling and simultaneous inversion (fusion) of MEG and EEG data, (4) group-based optimisation of spatial priors during M/EEG source reconstruction using fMRI data on the same paradigm, and (5) statistical mapping across subjects of cortical source power increases for faces vs. scrambled faces.