Despite of processing elements which are thousands of times faster than the neurons in the brain, modern computers still cannot match quite a few processing capabilities of the brain, many of which we even consider trivial (such as recognizing faces or voices, or following a conversation). A common principle for those capabilities lies in the use of correlations between patterns in order to identify patterns which are similar. Looking at the brain as an information processing mechanism with -- maybe among others -- associative processing capabilities together with the converse view of associative memories as certain types of artificial neural networks initiated a number of interesting results, ranging from theoretical considerations to insights in the functioning of neurons, as well as parallel hardware implementations of neural associative memories. This paper discusses three main aspects of neural associative memories: ffl theoretical investigations, e.g. on the information storage...