Combining EEG brain function data, brain-computer interface technology, and artificial intelligence, researchers have created a system that can generate an image of what a person is thinking. Read More
Color emotion may be a universal phenomenon, a new study reveals. People from different parts of the world often associate the same color with the same emotions. Read More
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. Read More
A new blood test could help doctors monitor those who are at risk of developing psychiatric disorders. The test looks for specific protein biomarkers in blood samples of those with risk factors for psychiatric illnesses and can help to predict who is most likely to develop psychosis in the future. Read More
Researchers test machine learning algorithms to determine the metal workload and affective states of the human brain. Read More
Deep layers of artificial neural networks can be edited to generate surprising and abstract images. Read More
Using data from MRI brain scan images, machine learning was 85% accurate at providing a diagnosis of psychiatric disorders that matched psychiatrists' assessments. The algorithm could also distinguish between patients with ASD, schizophrenia, risk factors for psychosis, and those with no history of mental health problems. Read More
Focusing on genes associated with psychiatric and neurological disorders, and drugs approved for use in other diseases, a new AI system can increase the effectiveness of drug repurposing. Read More
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New artificial intelligence technology can accurately predict how any chemical is going to smell to humans. Read More
Using artificial intelligence and neuroimaging, researchers have identified a link between mental imagery and vision. The brain uses similar visual areas for mental imagery and vision but uses low-level visual areas less precisely for mental imagery than vision. Read More
The human brain avoids taking unnecessary effort while reading by regulating the resources used in order to identify the most essential information. Read More
AI network simulations become unstable following continuous periods of unsupervised learning. When the networks were exposed to states that are analogous to human brain waves during sleep, the stability was restored. Read More
