Surface-based analysis methods for high-resolution functional magnetic resonance imaging

  • Authors:

  • Rez Khan;Qin Zhang;Shayan Darayan;Sankari Dhandapani;Sucharit Katyal;Clint Greene;Chandra Bajaj;David Ress

  • Affiliations:

  • Imaging Research Center, 3925B West Braker Lane, University of Texas at Austin, Austin, TX 78757, USA;Center for Computational Visualization, 201 E 24th Street, University of Texas at Austin, Austin, TX 78712, USA;Imaging Research Center, 3925B West Braker Lane, University of Texas at Austin, Austin, TX 78757, USA;Imaging Research Center, 3925B West Braker Lane, University of Texas at Austin, Austin, TX 78757, USA;Imaging Research Center, 3925B West Braker Lane, University of Texas at Austin, Austin, TX 78757, USA;Imaging Research Center, 3925B West Braker Lane, University of Texas at Austin, Austin, TX 78757, USA;Center for Computational Visualization, 201 E 24th Street, University of Texas at Austin, Austin, TX 78712, USA;Imaging Research Center, 3925B West Braker Lane, University of Texas at Austin, Austin, TX 78757, USA

  • Venue:
  • Graphical Models
  • Year:
  • 2011

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Abstract

Functional magnetic resonance imaging (fMRI) has become a popular technique for studies of human brain activity. Typically, fMRI is performed with 3-mm sampling, so that the imaging data can be regarded as two-dimensional samples that average through the 1.5-4-mm thickness of cerebral cortex. The increasing use of higher spatial resolutions,