When convolutional neural networks are trained under experimental conditions, they are deceived by the brightness and color of a visual image in similar ways to the human visual system. Read More
A new machine-learning algorithm has uncovered new neural mechanisms and enhanced the decoding of behaviors directly from brain signaling data. Read More
Testing multiple computational models of the nervous system, researchers discover that just because a model can make accurate predictions about data, this doesn't always translate into the underlying logic of the biological system it represents. Read More
New artificial intelligence technology will analyze clinical data, brain images, and genetic information from Alzheimer's patients to look for new biomarkers associated with the neurodegenerative disease. Read More
A new machine learning algorithm can accurately predict how long people will spend viewing an exhibit at a museum. Read More
A new computational model predicts how information deep inside the brain could flow from one network to another, and how neural network clusters can self optimize over time. Read More
A novel AI system recognizes a neuron in microscope images of the brain more efficiently than any previous approach. The system improves current methods of tracing neurons and their connections, which can help improve brain mapping. Read More
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
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
Personality traits, such as empathy and extraversion, could be predicted from specific network features. Other personality traits, lifestyle, and mental health status can be predicted from language use on social media platforms. Read More
A new artificial intelligence algorithm can detect a person's risk of heart disease by analyzing a selfie. The technology examines specific facial features, such as wrinkles, xanthelasmata, and the rings on the outer edges of the cornea, which are already known to be associated with heart disease, to determine a person's risk factor. Read More
Researchers test machine learning algorithms to determine the metal workload and affective states of the human brain. Read More
