In modern neuroscience and clinical study, neuroscientists and clinicians often use non-
invasive imaging techniques to validate theories and computational models, observe brain …

The allocation of attention to objects raises several intriguing questions: What are objects,
how does attention access them, what anatomical regions are involved? Here, we review …

The mental contents of perception and imagery are thought to be encoded in hierarchical
representations in the brain, but previous attempts to visualize perceptual contents have …

Deep neural networks (DNNs) have recently been applied successfully to brain decoding
and image reconstruction from functional magnetic resonance imaging (fMRI) activity …

Although distinct categories are reliably decoded from fMRI brain responses, it has proved
more difficult to distinguish visually similar inputs, such as different faces. Here, we apply a …

Unless adequate measures are taken for waste litter, the ecological balance may deteriorate
over time. The wastes disposed of the trash can be divided into two classes that are organic …

The human visual system uses two parallel pathways for spatial processing and object
recognition. In contrast, computer vision systems tend to use a single feedforward pathway …

Reconstructing natural images and decoding their semantic category from fMRI brain
recordings is challenging. Acquiring sufficient pairs of images and their corresponding fMRI …

Reconstructing perceived stimulus (image) only from human brain activity measured with
functional Magnetic Resonance Imaging (fMRI) is a significant task in brain decoding …

Decoding and reconstructing images from brain imaging data is a research area of high
interest. Recent progress in deep generative neural networks has introduced new …