How is the intercept in the GLM represented in the analysis?
Every neuroimaging program accounts for the “whole-brain mean” somehow in its statistics, by which I mean whatever part of the signal that does not vary at all with time. That time-invariant point can be represented in the design matrix explicitly as a column of all ones, and SPM automatically includes a column like that for each session in a given design matrix. (AFNI and BrainVoyager don’t explicitly show this column in the design matrix, but they include it in their model in the same fashion.) During the model estimation, a parameter is fit at each voxel to this whole-experiment mean, as any other column of the design matrix, and its value represents the mean signal value around which the signal oscillates. This is the ‘intercept’ of the analysis – the starting value from which experimental manipulations cause deviations. This number is automatically saved at each voxel in SPM ( in the beta images corresponding to the block effect columns) and can be saved in AFNI or BrainVoyager if
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