Statistical Parametric Mapping

Definition: Statistical Parametric Mapping (SPM) is an analysis technique used in functional neuroimaging to identify regions of brain activation related to an experimental task. This is quantified as a parametric map -a voxel-wise collection of statistical values (typically beta- or t-values) obtained using the general linear model (GLM) framework. The term SPM also refers to a free MATLAB toolbox developed at Wellcome Centre for Human Neuroimaging that implements preprocessing and modeling functionality that can be used to generate statistical parametric maps.Definition: Statistical Parametric Mapping (SPM) is an analysis technique used in functional neuroimaging to identify regions of brain activation related to an experimental task. This is quantified as a parametric map -a voxel-wise collection of statistical values (typically beta- or t-values) obtained using the general linear model (GLM) framework. The term SPM also refers to a free MATLAB toolbox developed at Wellcome Centre for Human Neuroimaging that implements preprocessing and modeling functionality that can be used to generate statistical parametric maps.

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Related terms: General Linear Model