statistical parametric mapping
Voxel-wise statistical analysis framework for neuroimaging data that creates maps showing regions of significant activation or group differences.
Full Definition
Statistical Parametric Mapping (SPM) is a comprehensive framework for analyzing neuroimaging data using mass univariate statistical approaches. The method performs statistical tests at each voxel independently, creating statistical maps that highlight brain regions showing significant effects. SPM addresses the multiple comparisons problem inherent in analyzing thousands of voxels simultaneously through various correction methods including family-wise error rate and false discovery rate controls. The approach encompasses preprocessing steps, statistical modeling using the general linear model, and inference procedures. SPM has become the foundation for most neuroimaging analyses and provides standardized tools for group-level comparisons and longitudinal studies.
Usage
Usage note: Commonly abbreviated as SPM; refers both to the method and the software package.
In Context
- "Statistical parametric mapping revealed significant activation in Broca's area during language tasks." — fMRI research findings
- "The analysis was performed using SPM12 with standard preprocessing and first-level modeling." — Neuroimaging methods section