Spike-Timing Models of plasticity

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Models of Long-Term Plasticity: Hebbian Learning

Explores Hebbian learning, synaptic plasticity, and models for long-term plasticity.

Synaptic Plasticity: Online Memory Learning

Explores synaptic plasticity, spike-timing models, and online memory learning challenges in computational neuroscience.

Introduction to synaptic plasticity

Covers synaptic plasticity, types of synapses, Hebb's postulate, LTP, LTD, and network oscillations in the hippocampus.

Introduction to Systems Neuroscience: Memory Systems Overview

Introduces systems neuroscience, focusing on neural circuits, memory systems, and course logistics.

Neuromorphic Computing: Concepts and Hardware Implementations

Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.

From Spiking Models to Rate Models

Explores the transition from spiking to rate models in synaptic plasticity.

Brain Intelligence: Continual Learning of Representational Models

Delves into the continual learning of representational models after deployment, highlighting the limitations of current artificial neural networks.

Attractor Networks and Spiking Neurons

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

Classification of Plasticity: Short-term vs. Long-term Changes

Explores short-term and long-term synaptic changes, Hebbian learning, and the role of neuromodulators.