Peter Dayan and LF Abbott
Part I: Neural Encoding and Decoding
1 Neural encoding I: Firing rates and spike
statistics
2 Neural encoding II: Reverse correlation and
visual receptive fields
3 Neural decoding
4 Information theory
Part II: Neurons and Neural Circuits
5 Model neurons I: Neuroelectronics
6 Model neurons II: Conductances and morphology
7 Network models pdf ps.gz
Part III: Adaptation and Learning
8 Plasticity and learning
9 Classical conditioning and reinforcement learing
10 Representational learning
Mathematical appendix
References