Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).

Brain–machine interfaces (BMIs) represent a transformative field at the intersection of neuroscience, engineering and computer science, allowing for direct communication between the brain and external ...

Seemingly unrelated diseases and conditions like Alzheimer's disease, obesity, chronic pain, traumatic brain injury, and ...

SAN DIEGO — Artificial intelligence (AI) is transforming the field of neuroscience, enabling scientific breakthroughs previously out of reach. New applications of AI and machine learning techniques ...

The idea of “reading minds” has shifted from science fiction to a concrete engineering challenge, and the latest breakthroughs suggest the brain’s private code is finally yielding. Researchers are not ...

Explore how brain computer interface technology and advanced brain-computer interfaces are transforming digital interaction, ...

A new machine learning algorithm developed by researchers from the USC Viterbi School of Engineering and NYU's Center for Neural Science can isolate brain signals and decode how neural dynamics in the ...

One of the biggest myths in neuroscience is that a singular brain region—such as the amygdala or insula—is responsible for a specific aspect of social cognition. This week, a team of Stanford and Duke ...

Within the brain, chemical neurotransmitters like dopamine and norepinephrine regulate mood, emotions and many physiological and behavioral processes. Their imbalance can contribute to anxiety, ...