Spiking Neuron Models

This introduction to spiking neurons can be used in advanced-level courses in computational neuroscience, theoretical biology, neural modeling, biophysics, or neural networks. It focuses on phenomenological approaches rather than detailed models in order to provide the reader with a conceptual framework. The authors formulate the theoretical concepts clearly without many mathematical details. While the book contains standard material for courses in computational neuroscience, neural modeling, or neural networks, it also provides an entry to current research. No prior knowledge beyond undergraduate mathematics is required.

Sommario

1. Introduction; Part I. Single Neuron Models: 2. Detailed neuron models; 3. Two-dimensional neuron models; 4. Formal spiking neuron models; 5. Noise in spiking neuron models; Part II. Population Models: 6. Population equations; 7. Signal transmission and neuronal coding; 8. Oscillations and synchrony; 9. Spatially structured networks; Part III. Models of Synaptic Plasticity: 10. Hebbian models; 11. Learning equations; 12. Plasticity and coding; Bibliography; Index.

Riassunto

Aimed at courses in computational neuroscience, theoretical biology, biophysics, or neural networks, this 2002 text will suit students of physics, mathematics, or computer science, as well as biologists who are interested in mathematical modelling. A large number of worked examples are embedded in the profusely-illustrated text.

Dettagli sul prodotto

• Autori: W Gerstner, Wulfram Gerstner, Wulfram (Ecole Polytechnique Federale de Lausanne) Gerstner, Gerstner Wulfram, W Kistler, Werner Kistler, Werner M. Kistler, Werner M. (Erasmus Universiteit Rotterdam) Kistler, Kistler Werner M.
• Editore: Cambridge University Press Academic
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 15.08.2002
• EAN: 9780521890793
• ISBN: 978-0-521-89079-3
• Dimensioni: 175 mm x 246 mm x 25 mm
• Categorie: Scienze naturali, medicina, informatica, tecnica; Scienze sociali, diritto, economia > Scienze sociali, tematiche generali; SCIENCE / Life Sciences / Neuroscience, Neurosciences, COMPUTERS / Data Science / Neural Networks, Neural networks and fuzzy systems, Neural networks & fuzzy systems