The paper presents a method to identify natural images from human brain activity using functional magnetic resonance imaging (fMRI). The authors developed a decoding method based on quantitative receptive field models, which characterize the relationship between visual stimuli and fMRI activity in early visual areas. These models describe the tuning of individual voxels for space, orientation, and spatial frequency, and are estimated directly from responses evoked by natural images. The study demonstrates that these receptive field models enable the identification of specific images from a large set of novel natural images. The identification performance is significantly better when orientation and spatial frequency tuning are included in the model, rather than simpler spatial tuning models. The results suggest that it may soon be possible to reconstruct a person's visual experience from brain activity measurements alone, with potential applications in understanding differences in perception, studying covert mental processes, and accessing visual content of mental phenomena like dreams and imagery.The paper presents a method to identify natural images from human brain activity using functional magnetic resonance imaging (fMRI). The authors developed a decoding method based on quantitative receptive field models, which characterize the relationship between visual stimuli and fMRI activity in early visual areas. These models describe the tuning of individual voxels for space, orientation, and spatial frequency, and are estimated directly from responses evoked by natural images. The study demonstrates that these receptive field models enable the identification of specific images from a large set of novel natural images. The identification performance is significantly better when orientation and spatial frequency tuning are included in the model, rather than simpler spatial tuning models. The results suggest that it may soon be possible to reconstruct a person's visual experience from brain activity measurements alone, with potential applications in understanding differences in perception, studying covert mental processes, and accessing visual content of mental phenomena like dreams and imagery.