2. Spike Train decoding

5. Summary Decoding of stimulus from response –Two choice case Discrimination ROC curves –Population decoding MAP and ML estimators Bias and variance Fisher information, Cramer-Rao bound –Spike train decoding

6. Chapter 4

7. Entropy

9. Mutual information H_noise< H

10. Mutual information

11. KL divergence

12. Continuous variables

13. Entropy maximization

15. Population of neurons

16. Retinal Ganglion Cell Receptive Fields

21. Temporal processing in LGN

24. Temporal vs spatial coding

25. Entropy of spike trains

28. Spike train mutual information measurements quantify stimulus specific aspects of neural encoding. Mutual information of bullfrog peripheral auditory neurons was estimated –1.4 bits/sec for broadband noise stimulus –7.8 bits/sec for bullfrog call-like stimulus

29. Summary Information theory quantifies how much a response says about a stimulus –Stimulus, response entropy –Noise entropy –Mutual information, KL divergence Maximizing information transfer yields biological receptive fields –Factorial codes –Equalization –Whitening Spike train mutual information