Electromagnetic brain activity was recorded using an Elekta Neuromag 306 MEG system, composed of 204 planar gradiometers and 102 magnetometers. Signals were sampled continuously at 1,000 Hz and band-pass filtered online between 0.1 and 330Hz. Offline preprocessing was done using the Elekta MaxFilter/MaxMove software, MATLAB (RRID:SCR_001622) and the FieldTrip analysis package (RRID:SCR_004849). Spatiotemporal signal space separation (tSSS) was performed to reduce noise originating from external (non-brain) signals, as well as noise produced by head motion, by exploiting certain properties of the solution to the Maxwell equations (Taulu and Simola 2006 (link)), as implemented by the Elekta MaxFilter/MaxMove software. Data were then demeaned, detrended, down-sampled to 100 Hz and time-locked to visual onset. The data were averaged across trials of the same exemplar across runs (excluding one-back trials, which were discarded), resulting in a total of 90 unique test trials throughout the main experiment (15 per condition), and 120 unique train/test trials throughout the intact scenes experiment (30 per condition). Except for the one-back trials, no trials were excluded and no additional artifact removal methods were used.
Brandman T, & Peelen M.V. (2023). Objects sharpen visual scene representations: evidence from MEG decoding. Cerebral Cortex (New York, NY), 33(16), 9524-9531.
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