Using electrocorticogram technology to capture brain waves, researchers found the meaning of what people imagine can be determined from brain wave patterns, even if the image differs from what a person is looking at.
Combining machine learning with neuroprosthetic technology allowed a patient with paralysis to learn to control a computer cursor by utilizing brain activity without extensive daily retraining.
When people listen to music, the neural tracking of the frontal lobe lags behind the temporal lobe, but during music recall, the frontal lobe precedes that of the temporal lobe. The findings demonstrate bottom-up and top-down processes in the cerebral cortex during music listening and recall. The study provides important insights into how the human brain processes music.
Using ECoG and machine learning, researchers decoded spoken words and phrases in real-time from brain signals that control speech. The technology could eventually be used to help those who have lost vocal control to regain their voice.
Responsive neurostimulation can remodel neural networks, leaving the brain less susceptible to epileptic seizures.
Findings about how the speech center is organized and how fluid speech occurs could lead to the development of neuroprosthetics capable of translating thoughts into speech, researchers report.
A new study explores which of the two main patterns of brain activity may be seen during the onset of an epileptic seizure.
Technological advances allow researchers to observe how the brain processes semantic information.
A new study reports researchers have successfully used brain stimulation to provide touch feedback and direct movement. The findings could benefit those with spinal cord injury to regain movement.
Brain-to-text system could help people with speech difficulties to communicate, researchers report.