Figure 3. Compressive Spatial Summation (CSS) model across modalities.

(a) The CSS model consists of (1) converting the stimulus into a sequence of binary contrast apertures, (2) projecting the contrast apertures onto the best-fitting 2D isotropic Gaussian population receptive field (pRF), and (3) passing the output through a static nonlinearity (power function) to predict the response. The CSS model was fit to data from V1, V2 and V3 using ECoG broadband and ECoG stimulus-locked responses (S1, S2, S3) and fMRI (S5, S6, S7). (b) The CSS model fits to the two types of ECoG responses are shown for each electrode (lines connect results from the same electrode); the pRF center locations are similar. PRF centers are in the left visual field because subjects had electrodes in the right hemisphere. (c) The exponent (n) from the model fits is highly compressive (n < 1) for BOLD fMRI and for ECoG broadband responses, but close to linear (n ~ 1) for the stimulus-locked response. All estimates come from model fits thresholded at 30% variance explained. For ECoG data, the plotted values represent the mean exponent +/− standard error across 15 electrodes in 3 subjects. For fMRI data, the plotted value represents the mean +/− standard error across 3 subjects, where the value for each subject was computed as the mean across 3 ROIs, and the value for each ROI was the median across voxels within the ROI. The pRF exponent and size of each of the 15 electrodes is reported in Table S2 and summarized in Figure S2.