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 ...

A machine learning model can effectively predict a patient’s risk for a sleep disorder using demographic and lifestyle data, physical exam results and laboratory values, according to a new study ...