Researchers report relatively simple math logic underlies complex brain computations.
According to researchers, a new machine learning training method can enable neural networks to learn directly from human-defined rules.
90 percent of the population can be classified into one of four main personality types, and of those, 30 percent fall under the envious personality type, a new study reports.
Researchers use machine learning algorithms to train a computer to recognize the neural patters associated with various odors.
According to a new study, a computer program was almost twice as accurate as neuroradiologists in determining whether abnormal brain tissue seen on an MRI scan was due to radiation or brain cancer.
Researchers created a computer model based on direct brain recordings from epilepsy patients and discover the existence of a network of neural regions directly involved in seizures.
Researchers report they have identified individual neurons in the brain that support observational learning.
Researchers propose the human brain is disproportionately large as a result of sizing one another up in large cooperative social groups.
A new algorithm is able to predict future terror attacks by recognizing patterns from past attacks.
Teams of data scientists use crowdsourcing to analyze recordings of electrical activity in the brains of people and dogs before and during seizures.
Researchers investigate how the human brain implements hierarchical structures in order to design more clever algorithms for machine learning.
Researchers have developed a prediction model that can warn of an epileptic seizure up to 20 minutes in advance.