Theoretical Neuroscience
Computational and Mathematical Modeling of Neural Systems

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