Reviews: From voxels to pixels and back: Self-supervision in natural-image reconstruction from fMRI

The paper's writing and figures are of very high clarity and quality. The method is novel and the basic innovation is in the new objective function, which has encoder-decoder dynamics that are intriguing. The area of research is tackling the difficult problem of trying to reconstruct images from human brain activity with recent machine learning and neural network techniques, which is a strong fit for the NeurIPS conference. The results in Figure 4e) are impressive and look like a convincing improvement over Shen et al. 2019 as they do not need a generative model prior at all, but train an end-to-end architecture. The only ImageNet statistics in their network are pretrained low-level AlexNet features (thus also further lowering the potential influence of category set statistics).