According to researchers, when learning a new task, the brain is less flexible than previously believed.
Researchers have successfully made an artificial connection from the brain to the locomotion center in the spinal cord by bypassing with a computer interface.
Researchers use direct brain control to allow a man paralyzed for five years to walk again.
Artificial IntelligenceDeep LearningFeaturedMachine LearningNeuroscienceNeuroscience VideosNeurotechOpen Neuroscience ArticlesRobotics··5 min read
Using EEG and brain computer interface technology, researchers have created a robotic arm that can be controlled without brain implants.
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Applying a nonlinear signal processing method to experimental data, a new study reveals a connection between motor behavior and brain activity. The findings could help with the development of new brain-computer interfaces and artificial intelligence technologies.
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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.
New advances in brain computer interface technology allows three people with movement impairments to control a cursor by imagining their hand movements.
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.
Researchers have developed a new method to record brain activity at scale. The new technique could help in the development of new neuroprosthetic devices to help amputees and those with movement restricting neurological conditions.