Decoding brain activity is conducive to the breakthrough of brain-computer interface (BCI)
technology. The development of artificial intelligence (AI) continually promotes the progress …

In the era of Artificial Intelligence Generated Content (AIGC), conditional multimodal
synthesis technologies (eg, text-to-image) are dynamically reshaping the natural content …

Image reconstruction and captioning from brain activity evoked by visual stimuli allow
researchers to further understand the connection between the human brain and the visual …

Visual images observed by humans can be reconstructed from their brain activity. However,
the visualization (externalization) of mental imagery is challenging. Only a few studies have …

Reconstructing visual experience from brain responses measured by functional magnetic
resonance imaging (fMRI) is a challenging yet important research topic in brain decoding …

Abstract Background and Objective Most studies used neural activities evoked by linguistic
stimuli such as phrases or sentences to decode the language structure. However, compared …

The graph neural network (GNN) has been widely used for graph data representation.
However, the existing researches only consider the ideal balanced dataset, and the …

Nanotechnology is an emerging field that is useful for various purposes. Numerous
neurological disorders, such as Parkinson's disease (PD), Alzheimer's disease (AD), stroke …

Previous studies have shown that it is possible to map brain activation data of subjects
viewing images onto the feature representation space of not only vision models (modality …

A central challenge in neuroscience is decoding brain activity to uncover the mental content
comprising multiple components and their interactions. Despite progress in decoding …