MIT 9.40 Introduction to Neural Computation, Spring 2018 (English)

   Friday, December 06, 2024   

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Lecture 1: 1: Course Overview and Ionic Currents - Intro to Neural Computation

Lecture 2: 2: Resistor Capacitor Circuit and Nernst Potential - Intro to Neural Computation

Lecture 3: 3: Resistor Capacitor Neuron Model - Intro to Neural Computation

Lecture 4: 4: Hodgkin-Huxley Model Part 1 - Intro to Neural Computation

Lecture 5: 5: Hodgkin-Huxley Model Part 2 - Intro to Neural Computation

Lecture 6: 6: Dendrites - Intro to Neural Computation

Lecture 7: 7: Synapses - Intro to Neural Computation

Lecture 8: 8: Spike Trains - Intro to Neural Computation

Lecture 9: 9: Receptive Fields - Intro to Neural Computation

Lecture 10: 10: Time Series - Intro to Neural Computation

Lecture 11: 11: Spectral Analysis Part 1 - Intro to Neural Computation

Lecture 12: 12: Spectral Analysis Part 2 - Intro to Neural Computation

Lecture 13: 13: Spectral Analysis Part 3 - Intro to Neural Computation

Lecture 14: 14: Rate Models and Perceptrons - Intro to Neural Computation

Lecture 15: 15: Matrix Operations - Intro to Neural Computation

Lecture 16: 16: Basis Sets - Intro to Neural Computation

Lecture 17: 17: Principal Components Analysis_ - Intro to Neural Computation

Lecture 18: 18: Recurrent Networks - Intro to Neural Computation

Lecture 19: 19: Neural Integrators - Intro to Neural Computation

Lecture 20: 20: Hopfield Networks - Intro to Neural Computation