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...

This book constitutes the refereed proceedings of the 7th International Conference on Artificial Neural Networks, ICANN'97, held in Lausanne, Switzerland, in October 1997. The 201 revised papers presented were selected from a large number of submissions and give a unique documentation of the state of the art in the area. The papers are organized in parts on coding and learning in biology; cortical maps and receptive fields; learning: theory and applications; signal processing: blind source separation, vector quantization, and self-organization; robotics, autonomous agents, and control;...