(A) Top panel: Schematic representation of seven regions (V1, V2, V4, MT, DP, TEO, 7A) used for defining visual hierarchy. Bottom panel: Each bar shows the fixed effect of the LMEM where the PF/CT was defined as a response variable and the visual hierarchy as an independent variable. We found a significant decrease of PF (t = −10.1, p<<0.001) but a significant increase of CT (t = 54.9, p<<0.001) along the visual hierarchy. To impose the hierarchical order of the seven ROIs in an LMEM, we defined a seven-element hierarchy vector for each participant and hemisphere (V = [1, 2, 3, …, 7]), whose elements refer to the hierarchical level of the corresponding ROI. The random effect was specified as in Equation 1. PF/CT values were standardized before LMEM analysis. This model tests the significance of PF/CT changes along the specified hierarchy. (B) Fixed effect per network obtained from linear mixed effect modeling of CT (top panel) and PF (bottom panel) as a function of networks (independent variable), where networks were specified as a categorical variable. The random structure was defined as in Equation 1. Fixed effect per network indicates the effect of that network on PF/CT. The network variable was defined as a categorical variable by assigning cortical regions to eight functional resting-state networks comprising three sensory (‘VIS’, visual; ‘AUD’, auditory; and ‘SOM’, somatomotor) and five association (‘DAN’, dorsal 670 attention; ‘FPN’, frontoparietal; ‘VAN’, ventral attention; ‘DMN’, default mode; and ‘CON’, cingulo-opercular) networks. We applied ANOVA on LMEM fit and computed F-stat for the fixed effect. (PF: F-stats = 264, p<<0.001; CT: F-stats = 746, p<<0.001). PF values were significantly lower in association RSNs (except for DAN) than in sensory RSNs (t = −11.1, p<<0.001), whereas CT values were significantly higher in association RSNs than in sensory RSNs (t = 14.1, p<<0.001). Error bar indicates the lower and upper bounds of LMEM for the fixed effect.