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9. Intro - Information processing in living organisms |
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9.1. Biological Neural Systems
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9.1.2. The First Generation
of Models
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9.1.4.3. Hypothesis for Biological Neural Systems |
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SNNs have enough computational power to
compute arbitrary functions. However the proofs underlying these
results are done on a rather abstract level and furthermore
do not provide hints how to construct a network of spiking neurons
which computes a concrete function.
The question about the computational power is investigated at
the Institute for Theoretical Computer Science (Graz).
They are also interested how concrete function which are likely
to be performed in real biological neural systems could be implemented
efficiently in a network of spiking neurons.
An example of such a function is the associative recall of stored memories.
In the work of Maass and Natschläger (1997) it is show how such
a associative memory can be implemented with a biological
rather realistic network of spiking neurons. How a
simple form of pattern recognition might be implemented with
a network of spiking neurons.
Source:
Networks of Spiking Neurons: A New Generation of Neural Network Models, Thomas Natschläger, December 1998 
