Figure 1
From: Emergence of Visual Center-Periphery Spatial Organization in Deep Convolutional Neural Networks
Hierarchical correspondences between layers of DCNN and brain regions of interest along ventral visual pathway. (A) For each image, the activation of units in each of the 5 convolutional layers are vectorized. RDM representation for each layer is created by computing the pairwise distance of these image specific vector patterns (1-Pearson Corr). Then fMRI RDM representations in EVC, Fusiform, IT and PHC areas are compared with the RDM representations of each convolutional layer of Hybrid-CNN by computing Spearman’s correlations. (B) Neural representations along ventral visual pathway. RDM matrices, and 2D multidimensional scaling visualization of stimuli depicted for early visual cortex (EVC), fusiform gyrus (Fusiform), inferior temporal cortex (IT) and parahippocampal cortex (PHC). (C) The correlation values for brain ROIs and layers of DCNN are depicted with bar plots. The error bars indicate the standard error of the mean and the stars above each bar indicates significant correlation above zero (N = 15, P < 0.05, Bonferroni-corrected). The noise ceiling for each brain area is reported on the right side of the panel. The pictures used in this figure are not examples of the stimulus set due to copyright.
