Nilearn parametric modulation

I wonder how to run parametric modulation using nilearn. I know that this function, nilearn.glm.first_level.make_first_level_design_matrix, has a parameter events that describes the experimental paradigm. Event has a condition, ‘modulation’, which specifies the amplitude of each event. I know that using FSL, I need to include two regressors: one is the task mean regressor which is a column including all 1s; and a parametric regressor, which is a column that specify the amplitude of each event. Do I need to include two regressors using nilearn? If yes, how? If not, how should I run parametric modulation. Many thanks. Xiuyi

Hi Xiuyi,

The following thread may help you: Parametric Modulation in nistats - #2 by tsalo.

Note that Nistats functions are now incorporated in Nilearn; the code may be slightly different but the general idea is the same.

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Hi Ivbrussel,

Many thanks. That’s very helpful. I will try this solution.