Multimodal Integration of M/EEG and f/MRI Data in SPM12

• Main Authors: Richard N. Henson, Hunar Abdulrahman, Guillaume Flandin, Vladimir Litvak
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2019-04-01
• Series: Frontiers in Neuroscience
• Subjects: MEG; EEG; fMRI; multimodal; fusion; SPM
• Online Access: https://www.frontiersin.org/article/10.3389/fnins.2019.00300/full

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.