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Pt. I | Basic experimental facts and theoretical tools | |
1 | Introduction | 3 |
2 | The neuron - building block of of the brain | 9 |
3 | Neuronal cooperativity | 17 |
4 | Spikes, phases, noise : how to describe them mathematically? : we learn a few tricks and some important concepts | 37 |
Pt. II | Spiking in neural nets | |
5 | The light house model : two coupled neurons | 77 |
6 | The lighthouse model : many coupled neurons | 103 |
7 | Integrate and fire models (IFM) | 141 |
8 | Many neurons, general case, connection with integrate and fire model | 151 |
App. 1 to chap. 8 : evaluation of (8.35) | 173 | |
App. 2 to chap. 8 : fractal derivatives | 177 | |
9 | Pattern recognition versus synchronization : pattern recognition | 181 |
10 | Pattern recognition versus synchronization : synchronization and phase locking | 207 |
Pt. III | Phase locking, coordination and spatio-temporal patterns | |
11 | Phase locking via sinusoidal couplings | 239 |
12 | Pulse-averaged equations | 251 |
Pt. IV | Conclusion | |
13 | The single neuron | 273 |
14 | Conclusion and outlook | 283 |
15 | Solutions to exercises | 287 |
References | 317 | |
Index | 329 |
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