Hippocampus Single Cell Models

Related lectures (32)

Page 3 of 4

Discusses challenges in building physical neural networks, focusing on depth, connections, and trainability.

Explores the logic of neuronal function, the Perceptron model, deep learning applications, and levels of abstraction in neural models.

Explores Rall's cable model, synaptic potential spread in dendrites, and compartmental modeling for neural simulations.

Explores the modeling of synaptic potentials and the factors influencing their amplitude.

Explores stochastic synaptic transmission modeling, parameters, inhibitory effects, and synaptic reliability.

Discusses dendrites as cables, covering the cable equation derivation and current conservation in coupled compartments.

Explores rate-based Hebbian learning, covariance rules, and weight vector growth in neural networks.

Explores synaptic transmission, neurotransmitters, and neural plasticity principles.

Explores the differences between electrical and chemical synapses, synaptic plasticity, and receptor behavior.