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Population Receptive Field Mapping (Matlab)
In the population receptive field mapping approach to retinotopy, receptive fields are formalized as parametric models (e.g. isotropic Gaussian). The parameters for each voxel are fit such that a BOLD signal predicted from moving a stimulus (according to the stimulation protocol of the retinotopy experiment) across the receptive field (RF) model matches the BOLD observed for that voxel. In the pRF tool provided in the CNI toolbox, a grid search is used to find the best parameters for all voxels in an isotropic 2D Gaussian model. After linear encoding of the stimulus using this model, compressive spatial summation may be applied.
The three parameters fit by the tool are the location of the RF (in Cartesian coordinates) and its size. However, the grid does not explore a set of size values. Rather it exploits that RF sizes are linearly related to eccentricity and explores a range of slopes for the size-eccentricity relationship. This effectively allows for exploration of a greater range of receptive field sizes. In terms of RF location, the visual field is split into a circular grid points, whose density decays exponentially with eccentricity. Close to the fovea, the grid is thus denser than in the periphery, thus taking cortical magnification into account. It is, however, also possible with the pRF tool to generate a linear grid of RF locations.