The representational hierarchy in human and artificial visual systems in the presence of object-scene regularities
Fig 2
The representational hierarchy for separation and interaction of objects and scenes in the brain.
The ROI-based (A, B) and whole-brain (C) RSA results for the 4 models (GIST, condition, domain, co-occurrence) are shown for brain data. Results reveal a strong separation for domain (scene and animal) representations in most ventral regions. The effect for animal-scene co-occurrence emerges in frontoparietal areas. (A) For group-averaged results, filled bars indicate significant values against baseline (p < 0.001) computed with permutation tests (10,000 randomizations of stimulus labels). (B) For individual subject results, reliability boundaries (in gray) indicate the highest expected correlation considering signal noise (see Methods) and error bars indicate SEM. Filled bars indicate significant values against baseline (p <0.005, corrected for n. or ROIs) calculated with pairwise t-tests across subjects (n = 19). For each ROI, the neural dissimilarity matrix (1—r) is shown below. (C) The random-effects whole-brain RSA results corrected with Threshold-Free Cluster Enhancement [TFCE; 37] are displayed separately for each individual model against baseline [BrainNet Viewer; 38]. Note that for some of these maps (e.g., co-occurrence vs domain), the direct contrast did not reveal a significant difference.