Synaptic Plasticity: Online Memory Learning

This lecture covers the computational neuroscience aspects related to synaptic plasticity and learning, focusing on models of short-term and long-term plasticity, spike-timing models, and online learning of memories through Hebbian assemblies. The instructor discusses the challenges of learning memories in bistable networks and the induction of plasticity using homosynaptic and heterosynaptic mechanisms. The lecture also explores rate models of Hebbian learning, the functional consequences of synaptic plasticity, and the plasticity models in feedforward and recurrent connections. Emphasis is placed on stable memory recall despite ongoing plasticity and activity, aiming to develop models that enable learning while avoiding synapse homeostasis and energy inefficiency.