Several popular Transformer based language models have been found to be successful for
text-driven brain encoding. However, existing literature leverages only pretrained text …

Can we obtain insights about the brain using AI models? How is the information in deep
learning models related to brain recordings? Can we improve AI models with the help of …

Intracranial human recordings are a valuable and rare resource of information about the
brain. Making such data publicly available not only helps tackle reproducibility issues in …

Neural representations of visual perception are affected by mental imagery and attention.
Although attention is known to modulate neural representations, it is unknown how imagery …

Artificial intelligence (AI) is a fast-growing field focused on modeling and machine
implementation of various cognitive functions with an increasing number of applications in …

Over the past few decades, a variety of significant scientific breakthroughs have been
achieved in the fields of brain encoding and decoding using the functional magnetic …

Semantic decoding, understood as predicting the semantic information carried by stimuli
presented to subjects based on neural signals, is an active area of research. Previous …

Intracranial recordings in epilepsy patients are increasingly utilized to gain insight into the
electrophysiological mechanisms of human cognition. There are currently several practical …

Artificial intelligence (AI) is a fast-growing field focused on modeling and machine
implementation of various cognitive functions with an increasing number of applications in …

Speech decoding from brain activity can enable development of brain-computer interfaces
(BCIs) to restore naturalistic communication in paralyzed patients. Previous work has …