Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Models of Long-Term Plasticity: Hebbian Learning
Graph Chatbot
Related lectures (32)
Previous
Page 3 of 4
Next
Understanding Learning Dynamics of Neural Networks
Explores neural network learning dynamics, covering optimization, interference, and continual learning challenges.
Analyzing Hebbian Learning Rule
Explores rate-based Hebbian learning, covariance rules, and weight vector growth in neural networks.
Learning of Associations
Delves into associative memory, Hebbian learning, and hierarchical organization in neural networks.
Scientific Computing in Neuroscience
Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.
Building Physical Neural Networks
Discusses challenges in building physical neural networks, focusing on depth, connections, and trainability.
Challenge of even bigger models
Explores simulating large-scale neural network models and optimizing memory efficiency in neural simulations using NEURON and CoreNEURON.
Dendrite as a Cable
Discusses dendrites as cables, covering the cable equation derivation and current conservation in coupled compartments.
Learning and synaptic plasticity
Covers sensory stimulation, learning, synaptic plasticity, and Hebb's postulate in neurorobotics.
General Introduction to Artificial Neural Networks
Covers the history and inspiration behind artificial neural networks, the structure of neurons, learning through synaptic connections, and the mathematical description of artificial neurons.
Neural Networks for Action Learning: Three-Factor Rules and Dopamine
Explores neural networks learning by reward, actor-critic structures, synaptic plasticity, and the role of dopamine in synaptic changes.