Table 3.

Different types of simulation bricks available in pyhrf.

Simulation item	Available generation process
Experimental paradigm	Localizer, random event-related
Activation labels	Hand-drawn 2D maps, 3D Potts realizations
Response levels	Bi/tri mixture of Gaussian or Gamma components
Hemodynamic response function	Canonical, Bezier curve, Gaussian smooth
Low frequency drift	Polynomial, cosine
Noise	White, auto-regressive of order p

The “localizer” paradigm is described in Pinel et al. (2007). Hand-drawn maps for activation labels are in the form of png images. Gaussian smooth generation of HRFs stands for the regularized prior used in the JDE model.