Researchers propose a novel computational framework that uses artificial intelligence technology to disentangle the relationship between perception and memory in the human brain.
Researchers created a new human brain model using machine learning-based optimization of required user profile information.
Combining brain activity data with artificial intelligence, researchers generated faces based upon what individuals considered to be attractive features.
A new artificial neural network based on the human brain sheds light on how we process moving images.
Even without a concussion, repetitive impacts experienced by those who play contact sports have clear effects on the brain. Rugby players who reported no concussions had alterations in the microstructure of the brain, specifically in the brain stem. Alterations in the functional organization of the brain were also discovered in MRI images of those who played contact sports.
A new convolutional neural network uses PET brain scans to detect biological signs of Alzheimer's disease years before the symptoms appear, researchers report.
Researchers at MIT have developed a new deep learning neural network that can identify speech patterns indicative of depression from audio data. The algorithm, researchers say, is 77% effective at detecting depression.
A new study links folic acid intake in pregnant women with epilepsy and language development in children. Researchers report among children whose mothers with epilepsy did not take folic acid, 34% had delayed language skills at 18 months.
Researchers say machine learning is up to 85% accurate at predicting the severity of small vessel disease, a condition associated with stroke and dementia.
Researchers speculate what the future may hold for artificial intelligence technologies, and us.