#Mapping onto vs one to one Patch

The individual sphere is warped match a sphere representing an average folding pattern (2). Automated Spherical Warping (ASW): Creates explicit representation of cortical surface and transforms it to a spherical form. Not based on explicit sulcal and gyral landmarks. Nonlinear volumetric warping: Matches voxel intensity in volumes. Relatively poor accuracy (~10 mm to 15 mm). Alignment Methods Talairach normalization (TL): Volumetric method based on linear transformations, common, and easy to use (1).

These patches were deformed using fluid deformation (3) and aligned with the N 27 brain using Caret (4). Four landmarks (outlining HG, STG, MTG, and IFG) were selected as anatomical markers on each patch, as shown below.

#Mapping onto vs one to one Patch

Fluid Deformation (FD): A patch of left perisylvian regions, including HeschlвЂ™s gyrus (HG), the superior temporal gyrus (STG) and sulcus (STS), the planum temporale (PT), the middle temporal gyrus (MTG), the Sylvian fissure (SF), and the inferior frontal gyrus (IFG) was cut from the inflated surface and flattened. The functional data was projected onto the N 27 brain using the same transformations. The inflated white matter surface was transformed into a sphere, and warped to a spherical representation of an averaged brain (2). Automated Spherical Warping (ASW): Anatomical surface models were created for each subject and the N 27 brain using Free. Vol 2 Surf, which takes into account all the voxels along the segments connecting the white matter and the pial surfaces. The functional volumes were then projected onto the surface model of a canonical (N 27) brain, using the AFNI program 3 d. No intensity or cluster thresholds were applied. Since smoothing of functional data to account for anatomical variation is a common practice when using Talairach transformations, a smoothed version (TLB) of the functional data was also created by applying a Gaussian filter with FWHM of 4 mm. Talairach: Individual subject anatomies and functional maps were projected into the standard stereotaxic space defined by Talairach and Tournoux (1) using AFNI. A variety of alignment techniques address this problem. In order to compare and overlay anatomies and functional activations, a one-to-one mapping needs to be specified so that each location in one brain corresponds to a unique location in another brain. This renders pooling data across different anatomies, a common task for group analysis of neuroimaging data, non-trivial. Binder Department of Neurology, Medical College of Wisconsin, Milwaukee, WI Introduction Intersubject Alignment Brain structures vary in their size, shape, position, and relative orientation. Surface-based Intersubject Alignment for Localization of Auditory Cortex Activation Rutvik Desai, Einat Liebenthal, Edward T.