Regression analysis of the empirical cross-correlation matrices. A, The weights of each model are plotted for areas V1, V2, V3d, and V3A. B, Model reconstructions based on the GLM β weights calculated in A with 2000 simulations. This result is confirmatory in allowing visualization of the features captured by the modeling approach. C, Goodness of fit of the GLM model in each region of interest with the associated noise ceiling bounds that estimate the minimum and maximum GLM performance that could be achieved given the noise in the data (Nili et al., 2014). The upper bound (red) is calculated by using the between-subjects mean matrix as a regressor for bootstrapped (10,000 samples) resampled averages of the subjects' data. The lower bound (blue) was calculated using single subjects' matrices as regressors for the bootstrapped resampled averages of the subjects' data. In both cases, the bounds were defined as the median value of the boostrapped R2 samples. D, GLM analyses conducted within subregions of the cross-correlation matrices. Error bars indicate ±SEM.
