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-==== fScan versus other fMRI analysis software ====
-fScan differs from other fMRI analysis software in 3 important ways: 1) organization of
-multimodal data in coherent XML-based “workspace” descriptor files and the ability to compare
-two workspaces simltaneously, 2) integration and interoperability of fScan’s large repertoire of
-intrinsic processing features with the ability to run programs and read data from other software
-packages all within a single fScan interactive session, 3) emphasis on data visualization
-capabilities, multimodal data integration, and a comprehensive and user-friendly graphical user
-interface. The relevance of each of these for the proposed study is briefly discussed.
-) Workspaces – A workspace is a collection of any number of related data_sets. Within a
-workspace, all spatial data can be registered to a common spatial coordinate system so that
-any location in one data set can be directly mapped onto any other data set. Examples of
-spatial data can be a single 2-dimensional JPEG image, or a large 3-D, 4-D (or even 5-D or
--D) series of MR images, or a 3D surface reconstruction graphics data set. A workspace
-also binds multiple time series data sets to a common temporal coordinate system. For
-example, it can link stimulus and behavioral response timing files, physiological oscillation
-data, eye-tracking data, and fMRI functional imaging data so that the relative timing is
-accurately known across all data collected for each brain scan. All information describing a
-workspace can be saved in a single XML text file. fScan can load two different workspaces
-simultaneously and the spatial coordinate systems of both can be registered, which then
-allows any data set in one workspace to be overlaid or compared to spatial data in the other.
-Originally designed to facilitate comparison between a subject exam workspace and a
-standard brain atlas workspace, this ability to compare two sessions will be invaluable in the
-proposed longitudinal study for comparing and quantifying changes in brain function (or
-structure) across multiple scan sessions of a single subject.
-) Interoperability – fScan's processing capabilities are not limited to its own internally
-programmed features. It also supports in-line execution of other software packages. For
-example, to use FSL's motion correction program (MCFLIRT) a user simply clicks an icon in
-the "FSL" taskbar to start a a shell script that automatically reformats the appropriate data file
-to NIfTI format if necessary, runs the MCFLIRT program, and then returns to the waiting
-fScan process to automatically load the newly created data set into a new fScan window.
-New data sets produced in that way are automatically registered to the common workspace
-coordinate system. This shell scripting option provides enormous flexibility to combine
-fScan's own internal features with complementary features available in other software
-packages. Simple graphical taskbars currently provide access to most major FSL package
-features and provide full integration of FreeSurfer 3-D brain reconstruction data. Additional
-interoperability taskbars are being added to integrate AFNI (Cox et al., 1996) software
-programs as well as DTI programs and data structures.
-) Visualization environment – fScan’s taskbar GUI interface is designed to be intuitively easy to
-use, and fScan's help features are simple and always available via direct access to a web-
-based Wiki that can be easily kept up-to-date. By providing immediate access to all data
-components via a common workspace, a simple graphical interface to processing features in
-fScan and multiple other programs, and extensive data visualization tools fScan can make
-functional brain mapping very accessible even to non-expert users. As part of our preliminary
-studies and preparation for the current proposal we have been directly involved in improving
-fScan’s user interface, user tutorials, and other on-line documentation. The result is a
-powerful brain image analysis platform that will provide the foundation for our image data
-analyses. It will also be used as a valuable teaching tool for providing students and others
-with direct access to the data collected in this study and to brain mapping methods more
-generally.

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