Statistical Plug-In Neuroimaging Network (SPINN)

SPINN is intended to be a stable and coherent yet highly extensible programming, analysis, and image-producing environment for neuroimaging researchers. The primary goals of SPINN are: 1) to spur the development and implementation of cutting-edge neuroimaging algorithms and statistical models by lowering barriers to participation and dissemination among methodologists from diverse disciplines;

2) to facilitate implementation of these algorithms and statistical models among applied neuroimaging researchers by providing a central repository of user-contributed downloadable plug-ins; these plug-ins will follow a reliably consistent format and will be easily searched and retrieved, well-documented, and user-friendly;

3) to seamlessly incorporate these plug-ins into the core distribution, which will include standardized functions for image-generation, visualization, and graphical display of outputs and output summaries.

Some SPINN Advantages:

1) SPINN will democratize neuroimaging research by providing a central repository of plug-ins containing algorithms, statistical models, and example applications and datasets which any member of the neuroimaging community can use and contribute to. These plug-ins will hew to a consistent set of standards for format, implementation, compatibility with the core distribution, and documentation (including appropriate references to the peer-reviewed literature).

2) This central repository of plug-ins will enable applied researchers to find and implement algorithms and statistical models which are well-tailored to address the scientific hypotheses specific to their research rather than being constrained by the handful of off-the-shelf methods currently available in widely-used packages (e.g., SPM and FSL). Methodology which may be quite effective in certain contexts but is currently not well publicized or available to applied researchers will become more widely disseminated. Thus, a key feature of SPINN will be the ability to efficiently match interests of a diverse network of methodological and applied neuroimaging researchers.

3) The easy availability of many user-contributed plug-ins implemented within a common framework will facilitate the comparison of the performance of different algorithms and statistical models in different contexts and experimental designs. This will foster a healthy competition among different methodologies and a greater understanding of their advantages and disadvantages.

SCN_Core_Tools is the preliminary development version of what will become SPINN. It is implemented in MATLAB.

Common tasks and how-tos

help/spinn_scn_core_tools.txt · Last modified: 2016/08/19 18:00 (external edit)
CC Attribution-Noncommercial-Share Alike 4.0 International
Driven by DokuWiki Recent changes RSS feed Valid CSS Valid XHTML 1.0