Researchers trained an AI to determine which psychotropic agent a zebrafish had been exposed to based on the animal's behaviors and locomotion patterns.
A new artificial intelligence algorithm can detect the progression of glaucoma up to 18 months earlier than conventional methods.
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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.
A new deep learning system is able to predict, with great accuracy, how different brain areas respond to specific words. The model also found concepts localized to the auditory cortex are less dependent on context.
A new convolutional neural network uses PET brain scans to detect biological signs of Alzheimer's disease years before the symptoms appear, researchers report.
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Researchers are using big data and artificial intelligence to map neural networks in the brain. The new technology could help to better understand the progression of neurodegenerative diseases.
Researchers apply machine learning algorithms to EEG data to create a new method of predicting when epileptic seizures will strike.
Machine learning study reveals that, much like genetics, brain connectivity patterns are passed down from parents to children.
A new brain wiring map reconstructs the entire shape and position of more than 300 neurons in the mouse brain.
Researchers have created a convolutional neural network to better understand how the brain processes movies of natural scenes. This may be the first step in helping scientists decode how the brain makes sense of dynamic visual surroundings.
Researchers report a convolutional neural network has been used to decode brain signals from EEG data. Scientists believe deep learning systems could be important tools for neuroscience analysis and could help revolutionize brain research.
