The second half of the past century saw the emergence of a theory of cortical associative
memory function originating in Donald Hebb's hypotheses on activity-dependent synaptic …

Neural associative networks with plastic synapses have been proposed as computational
models of brain functions and also for applications such as pattern recognition and …

The hippocampal CA3 region plays a key role in learning and memory. Recurrent CA3–CA3
synapses are thought to be the subcellular substrate of pattern completion. However, the …

Movement imitation requires a complex set of mechanisms that map an observed movement
of a teacher onto one's own movement apparatus. Relevant problems include movement …

The theoretical, practical and technical development of neural associative memories during
the last 40 years is described. The importance of sparse coding of associative memory …

To accommodate structured approaches of neural computation, we propose a class of
recurrent neural networks for indexing and storing sequences of symbols or analog data …

Coded recurrent neural networks with three levels of sparsity are introduced. The first level is
related to the size of messages that are much smaller than the number of available neurons …

Information coding by precise timing of spikes can be faster and more energy efficient than
traditional rate coding. However, spike-timing codes are often brittle, which has limited their …

Donald Hebb's concept of cell assemblies is a physiology-based idea for a distributed
neural representation of behaviorally relevant objects, concepts, or constellations. In the late …

The nature of the basins of attraction of a Hopfield network is as important as the capacity.
Here a new learning rule is re-introduced. This learning rule has a higher capacity than that …