Integrated Tool for Biological Parametric Mapping

Grant Start Date: 2004-08-01
Grant End Date: 2008-05-31

Principal Investigator:
Joseph A. Maldjian, M.D.

Investigators and Personnel:
Ramon Casanova Luis, Ph.D.
Funded By:

Grant Numbers: (more info)

WFU Biological Parametric Mapping Toolbox

In recent years, multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality-specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in Matlab with a user-friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely used T-field, has been implemented in the correlation analysis for more accurate results. An example with in vivo data is presented, demonstrating the potential of the BPM methodology as a tool for multimodal image analysis.

Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, NC
Funded through R01EB004673 under the Human Brain Project and NIBIB

Ramon Casanova, Ryali Srikanth, Aaron Baer, Paul J. Laurienti, Jonathan H. Burdette, Satoru Hayasaka, Lynn Flowers, Frank Wood and Joseph A. Maldjian
Biological parametric mapping: A statistical toolbox for multimodality brain image analysis
SHORT COMMUNICATION - NeuroImage Volume 34, Issue 1, 1 January 2007, Pages 137-143

Current Release: BPM Beta Release 1.5d

SPM2 or SPM5
MATLAB version 6.5 or higher

Download Readme User's Guide Change Log Feedback: bwagner@wfubmc.edu

SPM8 Compatibilty

BPM is not Compatible with SPM8. The recommended way to analyze SPM8 data is to run BPM in SPM5 with the data that has been processed in SPM8.

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