Visual object recognition is a complex, dynamic process. Multivariate pattern analysis
methods, such as decoding, have begun to reveal how the brain processes complex visual …

Relationships between neuroimaging measures and behavior provide important clues about
brain function and cognition in healthy and clinical populations. While …

What if we could effectively read the mind and transfer human visual capabilities to computer
vision methods? In this paper, we aim at addressing this question by developing the first …

Brain-computer interface (BCI) is oriented toward intuitive systems that users can easily
operate. Imagined speech and visual imagery are emerging paradigms that can directly …

Different categories of visual stimuli evoke distinct activation patterns in the human brain.
These patterns can be captured with EEG for utilization in application such as Brain …

A recent paper [1] claims to classify brain processing evoked in subjects watching ImageNet
stimuli as measured with EEG and to employ a representation derived from this processing …

Recent advancements in generative adversarial networks (GANs), using deep convolutional
models, have supported the development of image generation techniques able to reach …

The neural basis of object recognition and semantic knowledge has been extensively
studied but the high dimensionality of object space makes it challenging to develop …

Multivariate pattern analysis of magnetoencephalography (MEG) and
electroencephalography (EEG) data can reveal the rapid neural dynamics underlying …

Representational similarity analysis (RSA) is a multivariate method that can be used to
extract information about distributed patterns of representations across the brain. It is related …