Simplified intersubject averaging on the cortical surface using SUMA

Authors

  • Brenna D. Argall,

    1. Graduate Program, The Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania
    2. Laboratory of Brain and Cognition, National Institute of Mental Health Intramural Research Program, Bethesda, Maryland
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  • Ziad S. Saad,

    1. Scientific and Statistical Computing Core, National Institute of Mental Health Intramural Research Program, Bethesda, Maryland
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  • Michael S. Beauchamp

    Corresponding author
    1. Laboratory of Brain and Cognition, National Institute of Mental Health Intramural Research Program, Bethesda, Maryland
    2. Department of Neurobiology and Anatomy, University of Texas Health Science Center at Houston, Houston, Texas
    • Department of Neurobiology and Anatomy, University of Texas Health Science Center at Houston, 6431 Fannin St., Houston, TX 77030
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Abstract

Task and group comparisons in functional magnetic resonance imaging (fMRI) studies are often accomplished through the creation of intersubject average activation maps. Compared with traditional volume-based intersubject averages, averages made using computational models of the cortical surface have the potential to increase statistical power because they reduce intersubject variability in cortical folding patterns. We describe a two-step method for creating intersubject surface averages. In the first step cortical surface models are created for each subject and the locations of the anterior and posterior commissures (AC and PC) are aligned. In the second step each surface is standardized to contain the same number of nodes with identical indexing. An anatomical average from 28 subjects created using the AC–PC technique showed greater sulcal and gyral definition than the corresponding volume-based average. When applied to an fMRI dataset, the AC–PC method produced greater maximum, median, and mean t-statistics in the average activation map than did the volume average and gave a better approximation to the theoretical-ideal average calculated from individual subjects. The AC–PC method produced average activation maps equivalent to those produced with surface-averaging methods that use high-dimensional morphing. In comparison with morphing methods, the AC–PC technique does not require selection of a template brain and does not introduce deformations of sulcal and gyral patterns, allowing for group analysis within the original folded topology of each individual subject. The tools for performing AC–PC surface averaging are implemented and freely available in the SUMA software package. Hum Brain Mapp, 2005. © 2005 Wiley-Liss, Inc.

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