Surfing is a Matlab / Octave toolbox for surface-based voxel neighborhood selection on the cerebral cortex, intended for informationg mapping of functional magnetic resonance imaging (fMRI) data.
- voxel selection based on cortical surface reconstruction.
- support for Euclidian, Dijkstra and geodesic distance metrics.
- selection of voxels across the brain based on either a fixed radius or a fixed number of voxels.
- support for twin surfaces (FreeSurfer; pial and white) and single surfaces (Caret and BrainVoyager).
- no GUI: commands are entered in the Matlab command window, or in a matlab script.
- no full processing pipeline: preprocessing, surface reconstruction, classification, statistical analyses, and visualization are not part of the toolbox. Many other programs can be used for this, for example FSL, AFNI, SPM for preprocessing and regression; Freesurfer and Caret for surface reconstruction; several online toolboxes for classification and statistical analyses; and AFNI, Freesurfer and Caret for visualization.
A working installation of Matlab or Octave
Using a geodesic distance metric (for measuring distances on the surface), a working mex compiler environment may be required. An alternative metric (that gives similar results but does not require mex) is the dijkstra metric.
externals have only been tested on Matlab:
- Nikolaas N. Oosterhof [NNO], nikolaas.oosterhof at unitn.it
- Tobias Wiestler [TW], tobias.wiestler at googlemail.com
- Joern Diedrichsen [JD], j.diedrichsen at ucl.ac.uk
- add the "surfing", "misc" and "toolbox_fast_marching" directories (and their subdirectories) to the Matlab / Octave path.
- run "compile_mex" in the "surfing" root directory.
- view the surfing_voxelselection.m function, or consider the examples in the "examples" directory.
The "surfing" toolbox is copyright (c) 2009-2014 Nikolaas N. Oosterhof, Tobias Wiestler, Joern Diedrichsen. All rights reserved. The toolbox "fast marching" (in the toolbox_fast_marching directory) is copyright 2009, Gabriel Peyre. All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
If you use this toolbox for a scientific publication, please cite: Oosterhof, N.N., Wiestler, T, Downing, P.E., & Diedrichsen, J. (in press). A comparison of volume- based and surface-based information mapping. Neuroimage. Available online http://dx.doi.org/10.1016/j.neuroimage.2010.04.270
If you use geodesic distances, please also cite: Gabriel Peyre (2008), Toolbox Fast Marching. https://www.ceremade.dauphine.fr/~peyre/matlab/fast-marching/content.html