Hebbian Plasticity

Hebbian plasticity, the principle that synaptic connections strengthen when neurons fire together, is a cornerstone of neuroscience, driving research into how learning and memory occur in biological systems and how to replicate these processes in artificial intelligence. Current research focuses on developing biologically plausible neural network models incorporating Hebbian learning, including spiking neural networks and recurrent networks with various architectures like predictive attractor models and dynamic nets, to achieve robust unsupervised learning and memory formation. These advancements hold significant promise for improving the efficiency and biological realism of AI algorithms, as well as providing deeper insights into the mechanisms underlying learning and memory in the brain.