Introduction to Neural Computation (M-I-T)

• 1: Course Overview and Ionic Currents (M-I-T)
• 2: Resistor Capacitor Circuit and Nernst Potential (M-I-T)
• 3: Resistor Capacitor Neruon Model (M-I-T)
• 4: Hodgkin-Huxley Model Part 1 (M-I-T)
• 5: Hodgkin-Huxley Model Part 2 (M-I-T)
• 6: Dendrites (M-I-T)
• 7: Synapses (M-I-T)
• 8: Spike Trains (M-I-T)
• 9: Receptive Fields (M-I-T)
• 10: Time Series (M-I-T)
• 11: Spectral Analysis Part 1 (M-I-T)
• 12: Spectral Analysis Part 2 (M-I-T)
• 14: Rate Models and Perceptrons (M-I-T)
• 15: Matrix Operations (M-I-T)
• 16: Basic Sets (M-I-T)
• 17: Principal Components Analysis (M-I-T)
• 18: Recurrent Networks (M-I-T)
• 19: Neural Integrators (M-I-T)
• 20: Hopfield Networks (M-I-T)