Inter‐subject alignment of MEG datasets in a common representational space

• Published in: Human brain mapping Vol. 38; no. 9; pp. 4287 - 4301
• Main Authors: Zhang, Qiong, Borst, Jelmer P., Kass, Robert E., Anderson, John R.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.09.2017; John Wiley and Sons Inc
• Subjects: Algorithms; Alignment; Anatomy; Brain; Brain - physiology; Brain Mapping - methods; Bypasses; canonical correlation analysis; common representational space; Computer Simulation; Correlation analysis; Humans; Inverse problems; Localization; Magnetoencephalography; Magnetoencephalography - methods; Multivariate Analysis; Neuroimaging; Position (location); Principal Component Analysis; Regularization; Sensors; Structure-function relationships; subject alignment; common representational space; canonical correlation analysis; magnetoencephalography; subject alignment

Pooling neural imaging data across subjects requires aligning recordings from different subjects. In magnetoencephalography (MEG) recordings, sensors across subjects are poorly correlated both because of differences in the exact location of the sensors, and structural and functional differences in t...