How the Human Brain Solves Complex Decision-Making Problems

A new study on meta reinforcement learning algorithms helps us understand how the human brain learns to adapt to complexity and uncertainty when learning and making decisions. A research team succeeded in discovering both a computational and neural mechanism for human meta reinforcement learning, opening up the possibility of porting key elements of human intelligence into artificial intelligence algorithms. This study provides a glimpse into how it might ultimately use computational models to reverse engineer human reinforcement learning.

Synchronization of Memory Cells Critical for Learning and Forming Memories

Sleep Deficits May Affect Kids’ Mental Health

Study Sheds New Light on Genetic Relationship Between Three Mood Disorders

Researchers shed new light on the genetic relationship between three mood disorders associated with depression--major depression and bipolar disorder types 1 and 2, in a new study in the journal Biological Psychiatry, published by Elsevier.