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Home » Applied Sciences » Computer Science » Introduction to Neural Computation (M-I-T) » 8: Spike Trains (M-I-T)

8: Spike Trains (M-I-T)

Course:Introduction to Neural Computation (M-I-T)
Discipline:Applied Sciences
Institute:MIT
Instructor(s): Prof. Michale Fee, Daniel Zysman
Level:Undergraduate

Introduction to Neural Computation (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)
13: Spectral Analysis Part 3 (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)
1: Course Overview and Ionic Currents (M-I-T)
20: Hopfield Networks (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)

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