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.
EmoNet, a new convolutional neural network, can accurately decode images into eleven distinct emotional categories. Training the AI on over 25,000 images, researchers demonstrate image content is sufficient to predict the category and valence of human emotions.
The brain quickly transitions from one network to another in regular patterns. The transition trajectories constitute a temporal circuit where the conscious brain cycles through a structured pattern of states over time.
Using advances in machine learning, researchers have created a new model that predicts the ease with which individuals produce and comprehend complex sentences.
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.
Researchers have developed a new, fully automated prosthetic arm that learns during normal use and adapts to varying conditions.
The patterns of reasoning deceptive people use may serve as indicators of truthfulness, a new AI algorithm discovered. Researchers say reasoning intent is more reliable than verbal changes and personal differences when trying to determine deception.
Rat R222 was born with hydrocephalus. Neuroimaging revealed most of its brain had compressed and collapsed as it filled with fluid. However, despite its condition, the animal was still able to see, hear, smell, and feel like other animals. The study sheds new light on neuroplasticity, and the findings could have implications for the development of new machine learning technologies.
Researchers have developed a smart onesie that accurately measures the spontaneous and voluntary movements of infants from five months. The smart-clothing could help assess abnormal neurological and motor development in infants.
Widely used music algorithms are more likely to recommend and select music by male artists, at the detriment of female musicians. A new study addresses gender disparities in music-based algorithms.