GLM
Pronunciation: gee-el-em
Also written as: GLM — general linear model
Statistical framework used to analyze neuroimaging data and identify brain activation patterns.
Full Definition
The general linear model (GLM) is the primary statistical framework used in neuroinformatics to analyze neuroimaging data and identify patterns of brain activation. The GLM relates observed neural signals to experimental conditions or behavioral variables through a design matrix that specifies the expected neural response. In fMRI analysis, the GLM accounts for the hemodynamic response function and enables statistical testing for activation differences between conditions. The approach supports both univariate (voxel-wise) and multivariate analysis methods and forms the foundation for most neuroimaging statistical analyses.
Usage
Usage note: Uppercase when abbreviated; refers specifically to neuroimaging statistical model.
In Context
- "Statistical analysis was performed using a GLM with task regressors and motion parameters." — Methods section
- "The GLM design matrix included boxcar functions convolved with the canonical HRF." — Technical report