This tool supports
- Partial Least Squares GUI for PET, fMRI & EEG/MEG
- Rotman Res Inst - Baycrest Centre, Univ of Toronto
- Partial Least Squares (PLS) is a multivariate analysis tool that can be applied to neuroimaging data. The analytical focus is to determine which aspects of the signal in one matrix (e.g., imaging data) are related directly to signals in another matrix (e.g., experimental design, behaviour). It can be applied to spatial and spatiotemporal data, and has been used to identify task-dependent changes in activity, changes in the relations between brain activity and behaviour, and to examine functional connectivity of one or more brain regions. PLS has similarities to Canonical Correlation in its general configuration, but is much more flexible and robust.
This GUI is the first major release of PLS for neuroimaging. The GUI has been in development for some time, and although this version appears stable, there are always things that can be improved. A command-line application is also included for users with special imaging datasets (e.g., ROI analysis). We are also planning several enhancements, such as univariate testing of means and correlations, advanced plotting routines and higher-order analyses. Please check our website regularly to see if there are updates.
- NIfTI-1 support
- PLSgui now supports NIFTI data format. This includes file extension support for both single file (.nii) and dual file (.img/.hdr); temporal dimension support (4th dimension in the data); and data value scaling support (Y = scl_slope * X + scl_inter). It also supports some of the sform or qform affine transforms. This includes any scaling (to get voxel_size), any translation (to get origin), any flipping, and small Rotations (only N*90 degrees, where N must be integer).
- Randy McIntosh, Nancy Lobaugh, Wilkin Chau, Jimmy Shen
- How to get
- Download from website after registration
- Current version
- Current version release date
- July 2005
- Open source
- GNU General Public License (GPL)
- Available free of charge
- Runs on Matlab v5.x or higher, v6.x recommended.
- Technical publications
- McIntosh AR, Bookstein FL, Haxby JV, Grady CL (1996) Spatial pattern analysis of functional brain images using Partial Least Squares. Neuroimage 3:143-157.
Lobaugh NJ, West R, McIntosh AR (2001) Spatiotemporal analysis of experimental differences in event-related potential data with partial least squares. Psychophysiology 38:517-530.
McIntosh AR, Lobaugh NJ (2004) Partial least squares analysis of neuroimaging data: applications and advances. Neuroimage 23 Suppl 1:S250-263.
McIntosh AR, Chau WK, Protzner AB (2004) Spatiotemporal analysis of event-related fMRI data using partial least squares. Neuroimage 23:764-775.
- Applications publications
Addis DR, McIntosh AR, Moscovitch M, Crawley AP, McAndrews MP (2004) Characterizing spatial and temporal features of autobiographical memory retrieval networks: a partial least squares approach. Neuroimage 23:1460-1471.
Della-Maggiore V, Sekuler AB, Grady CL, Bennett PJ, Sekuler R, McIntosh AR (2000) Corticolimbic interactions associated with performance on a short-term memory task are modified by Age. Journal of Neuroscience 20:8410-8416.
Duzel E, Habib R, Schott B, Schoenfeld A, Lobaugh N, McIntosh AR, Scholz M, Heinze HJ (2003) A multivariate, spatiotemporal analysis of electromagnetic time- frequency data of recognition memory. Neuroimage 18:185-197.
Grady CL, Furey ML, Pietrini P, Horwitz B, Rapoport SI (2001) Altered brain functional connectivity and impaired short-term memory in Alzheimer's disease. Brain 124:739-756.
Grady CL, McIntosh AR, Bookstein F, Horwitz B, Rapoport SI, Haxby JV (1998) Age-related changes in regional cerebral blood flow during working memory for faces. Neuroimage 8:409-425.
Leibovitch FS, Black SE, Caldwell CB, McIntosh AR, Ehrlich LE, Szalai JP (1999) Brain SPECT imaging and left hemispatial neglect covaried using partial least squares: the Sunnybrook Stroke study. HBM 7:244-253.
Lobaugh, N.J., Chevalier, H., Batty, M., Taylor, M.J. 2005. Accelerated and amplified neural responses in visual discrimination: Two features are processed faster than one. Neuroimage. 26:986-995.
McIntosh AR, Sekuler AB, Penpeci C, Rajah MN, Grady CL, Sekuler R, Bennett PJ (1999) Recruitment of unique neural systems to support visual memory in normal aging. Curr Biol 9:1275-1278.
McIntosh AR, Rajah MN, Lobaugh NJ (1999) Interactions of prefrontal cortex related to awareness in sensory learning. Science 284:1531-1533.
McIntosh AR, Rajah MN, Lobaugh NJ (2003) Functional connectivity of the medial temporal lobe relates to learning and awareness. J Neurosci 23:6520-6528.
- Other information
- functional, multimodal, multivariate, NIfTI-1 support, statistical
- Linux, MacOS, MATLAB, SunOS, UNIX, Windows
- IATR listing last updated
- 24 Aug 2005
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