Our subjective experience appears to us in a continuous stream of integrated information, and in Chaos, researchers explore the question: Which characteristics should brain activity have to support this type of conscious experiences?
While studied for nearly a century, little is known about how cavefish brains differ. A study is the first to look inside their brains with millimeter resolution to start to understand how the individual neurons and brain regions that drive complex behaviors, including sleep and feeding have evolved. This work has broad implications for the understanding of how brains evolve in many different animal models and is hoped to be widely used by the scientific community.
A new UCLA study shows partially overlapping patterns of brain function in people with anorexia nervosa and those with body dysmorphic disorder, a related psychiatric condition characterized by misperception that particular physical characteristics are defective.
The Reward Positivity (∆RewP) event-related potential (ERP), generally quantified as the difference between neural responsiveness to monetary gains (RewP-Gain) and losses (RewP-Loss) is commonly used as an index of neural reward responsiveness. Despite the popularity of this ERP component in…
UCLA researchers have found that it is possible to assess a person’s ability to feel empathy by studying their brain activity while they are resting rather than while they are engaged in specific tasks.
Motor-related brain activity is of great interest to researchers looking for a better way to improve neurorehabilitation, and one factor to consider is the suppression of the specific rhythmic activity of neurons within the sensorimotor cortex of the brain. Studies indicate this feature suffers from variability when using traditional methods to explore it. In the journal Chaos, scientists in Russia are approaching the problem from a different angle to search for a more robust feature of brain activity associated with accomplishing motor tasks.
Using a mathematical framework with roots in artificial intelligence and robotics, UW researchers were able to uncover the process for how a person makes choices in groups. And, they also found they were able to predict a person’s choice more often than more traditional descriptive methods.