Learn · Introduction to Neural Computation

Lecture 8 of 20Lecture Videos57 min

8. Spike Trains

Prof. Michale Fee and Daniel Zysman · Massachusetts Institute of Technology

At MIT OpenCourseWare Transcript

Credits and licence

From
Introduction to Neural Computation, Massachusetts Institute of Technology (at MIT OpenCourseWare)
Licence
CC BY-NC-SA 4.0, as MIT OpenCourseWare states it. Non-commercial use only.
Attribution
Prof. Michale Fee, Daniel Zysman. Introduction to Neural Computation. Spring 2018. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu/. License: Creative Commons BY-NC-SA.
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All the lectures

  1. 1. Overview and Ionic Currents 1 h 11 min · Video
  2. 2. RC Circuit and Nernst Potential 1 h 20 min · Video
  3. 3. Nernst Potential and Integrate and Fire Models 1 h 7 min · Video
  4. 4. Hodgkin-Huxley Model Part 1 1 h 15 min · Video
  5. 5. Hodgkin-Huxley Model Part 2 1 h 19 min · Video
  6. 6. Dendrites 1 h 7 min · Video
  7. 7. Synapses 1 h 19 min · Video
  8. 8. Spike Trains 57 min · Video
  9. 9. Receptive Fields 1 h 18 min · Video
  10. 10. Time Series 1 h 19 min · Video
  11. 11. Spectral Analysis Part 1 1 h 18 min · Video
  12. 12. Spectral Analysis Part 2 1 h 13 min · Video
  13. 13. Spectral Analysis Part 3 1 h 9 min · Video
  14. 14. Rate Models and Perceptrons 1 h 16 min · Video
  15. 15. Matrix Operations 1 h 18 min · Video
  16. 16. Basis Sets 1 h 13 min · Video
  17. 17. Principal Components Analysis​ 1 h 22 min · Video
  18. 18. Recurrent Networks 1 h 20 min · Video
  19. 19. Neural Integrators 1 h 8 min · Video
  20. 20. Hopfield Networks 1 h 14 min · Video