Researchers propose highly selective neural representations are well suited to co-activating multiple things at the same time in short terms memory.
Researchers have developed an artificial neural network that has been able to communicate with and learn human language.
Researchers demonstrate how memristors could be used to power artificial systems to mimic the human brain.
New findings about how the brain processes information in verbal working memory could have implications for the development of new AI systems, researchers report.
Researchers have developed a new algorithm that integrates Alzheimer's indicators from MRI measurements to predict patients with the neurodegenerative disease.
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.
Researchers applied a computer algorithm to 3D facial images of children diagnosed with ASD. The algorithm detected both males and females with autism had more masculine features than children not on the spectrum.
Researchers report humans often miss objects in plain sight, especially if the size is inconsistent with the rest of the scene.
Researchers from UT Austin utilize deep learning and supercomputing to help identify brain tumors.
A new deep learning algorithm can interpret EEG data from preterm babies and estimate the child's brain functional maturity, researchers report.
A new brain wiring map reconstructs the entire shape and position of more than 300 neurons in the mouse brain.
Machine learning study reveals that, much like genetics, brain connectivity patterns are passed down from parents to children.
