Computational protocol: Language Differences in the Brain Network for Reading in Naturalistic Story Reading and Lexical Decision

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Protocol publication

[…] Functional data were analyzed using AFNI ([], program names appearing in parentheses below are part of the AFNI suite). Cortical surface models were created with FreeSurfer (available at http://surfer.nmr.mgh.harvard.edu/), and functional data projected into anatomical space using SUMA ([ ], AFNI and SUMA are available at http://afni.nimh.nih.gov/afni).Surface-based spatial normalization of anatomical and functional data was accomplished using Freesurfer [] and SUMA []. Anatomical data were reconstructed (to3d), and a surface model for each participant was made with Freesurfer: cortical meshes were extracted from the structural volumes, and then inflated to a sphere and registered anatomically []. Using the surface atlas, an averaged subject was created by averaging surfaces, curvatures, and volumes from all participants both from Chinese and English. The averaged surface was converted into SUMA [] as a standard mesh on the SUMA surfaces. The standard mesh was then converted to a volume and transformed to Talairach space (@auto_tlrc), using the N27 template [] for visualization and reference purposes. Functional data were normalized by transforming volumes resulting from AFNI into surface representations using the standardized surfaces, and computing averages over surfaces. Reported Talairach coordinates are reported based on creating a 2x2x2mm AFNI volume from the average surface in each experiment (3dSurf2Vol). […]

Pipeline specifications

Software tools AFNI, FreeSurfer
Applications Magnetic resonance imaging, Functional magnetic resonance imaging
Organisms Homo sapiens