Before revision:  Results show that (1) the proposed estimator is consistent with theoretical predictions for total correlation, ( 2 ) the capacity increases substantially along the layers of the model, and (3) the capacity of the cortical representation follows the PDF of natural scenes over the chromatic and achromatic dimensions of the stimulus space . In theoretical neuroscience, the proposed capacity measure based on Gaussianization is useful to check the Efficient Coding Hypothesis and to assess the relative relevance of the chromatic and spatial elements of the models. From an applied perspective, in image compression, the proposed measure suggest which visual features should be addressed first; and in image quality, the proposed measure can generalize the visual information fidelity concept .
After revision:  Results show that (1) the proposed estimator is consistent with theoretical predictions for total correlation, ( 2 ) the capacity increases substantially along the layers of the model, and (3) the capacity of the cortical representation follows the PDF of natural scenes over the chromatic and achromatic dimensions of the stimulus space , (3) the contribution of spatial transforms to capture visual information is substantially bigger than the contribution of chromatic transforms, and (4) nonlinearities of the responses contribute substantially to the transmitted information but less than the linear transforms .