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Lecture
Simple Hebbian learning rules and correlated inputs
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Related lectures (32)
Analyzing Hebbian Learning Rule
Explores rate-based Hebbian learning, covariance rules, and weight vector growth in neural networks.
Synapses: Neuronal Dynamics
MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons
Explores the role of synapses in computational neuroscience and the models of excitatory and inhibitory synapses.
Synaptic Transmission: Diffusive Component
Explores the diffusive component of synaptic transmission and its impact on brain function.
Inhibitory synaptic conductances
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Explores GABAergic inhibition, postsynaptic potentials, shunting inhibition, and target structures in the brain.
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Synaptic Transmission: Electrical vs Chemical
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Compares electrical and chemical synapses, emphasizing their properties and behavior, including the neuromuscular junction and synapses in the CNS.
Synaptic Transmission: Electrical vs. Chemical
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Explores the differences between electrical and chemical synapses, synaptic plasticity, and receptor behavior.
Computational Neuroscience: Biophysics
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Covers modern neuroscience synthesis, biophysical modeling, and brain building blocks with practical applications.
Synaptic Plasticity: Forms and Mechanisms
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Explores different forms of synaptic plasticity and the mechanisms behind them, emphasizing the role of calcium in inducing and maintaining plastic changes.
Synaptic Plasticity: Mechanisms and Models
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Explores different forms of synaptic plasticity and computational models to understand its mechanisms and induction protocols.
Neuronal Signaling: Action Potentials and Conduction
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Covers the terminology, generation, and conduction of action potentials in neuronal signaling, along with bioelectric signals and synaptic currents.
Engineering Neurons: Light, Chemicals, Sound
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Explores optogenetics, chemogenetics, and sonogenetics to engineer neural activity using light, chemicals, and sound.
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