On the relevance of time in neural computation and learning

We discuss models for computation in biological neural systems that are bas ed on the current stare of knowledge in neurophysiology. Differences and si milarities to traditional neural network models are highlighted. It turns o ut that many important questions regarding computation and learning in biol ogical neural systems cannot be adequately addressed in traditional neural network models. In particular, the role of time is quite different in biolo gically more realistic models, and many fundamental questions regarding com putation and learning have to be rethought for this context. Simultaneously , a somewhat related new generation of VLSI-chips is emerging ("pulsed VLSI ") where new ideas about computing and learning with temporal coding can be tested in an engineering context. Articles with details to models and resu lts that are sketched in this article can be found at http://www.tu-graz.ac .at/igi/maass/. We refer to Maass and Bishop (Eds., Pulsed Neural Network. MIT Press, Cambridge, MA. 1999) for a collection of survey articles that co ntain further details and references. (C) 2001 Elsevier Science B.V. All ri ghts reserved.