From: Visualizing fMRI BOLD responses to diverse naturalistic scenes using retinotopic projection Journal of Vision. 2017;17(6):18. doi:10.1167/17.6.18 Figure Legend: RP-images of four photos, pooling V1 and V2 voxels. (Column 1) Photographs of real scenes. (Columns 2–4) Data RP-images for the three subjects. The degree of similarity across subjects would not be easily apparent if voxel responses were viewed in anatomical space, in which each subject has a unique layout for V1 and V2. (Rightmost column) Model RP-images based on output of the local contrast integration model; model RP-images shown here pool receptive fields from all three subjects. As described in Methods, the receptive fields are based on subject data, but the responses used with these receptive fields in retinotopic projection can be based on model data or subject data. There is a strong similarity of the data RP-images and model RP-images for the first three photos. The photo in the bottom row is an example for which the model is a poor fit to the data. First three photos are modified from the copyright-free Berkeley Segmentation Dataset (Martin et al., 2001), https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html; bottom photo by Kendrick Kay who has made his images available for research and publication; see https://crcns.org/data-sets/vc/vim-1. Date of download: 12/27/2017 The Association for Research in Vision and Ophthalmology Copyright © 2017. All rights reserved.