Testing multiple computational models of the nervous system, researchers discover that just because a model can make accurate predictions about data, this doesn't always translate into the underlying logic of the biological system it represents.
When learning a new task, brain activities alter over time as mice transition to an expert from a novice. The changes are reflected in neural networks and neural activity. As the animal's knowledge grows, neural networks become more focused.
Learning is best predicted by both curiosity and an objective measure of knowledge. Researchers suggest it is uncertainty, or when you think you know something then discover you don't, that leads to curiosity and learning outcomes.
Researchers report the brain's reward network could play an influential role in evaluating the opportunity to gain new information, just as it does to evaluate rewards such as food or financial gain.
People who think their beliefs are superior to other people's view points are prone to overestimating what they actually know, a new study reports.
Researchers report the web might be affecting how we think as people are less willing to rely on their knowledge when they have access to the internet.