Abstract

This article reviews theories explaining the formation of neuronal assemblies and the functions that assemblies can have, presents computational models of oscillatory neural networks, and shows how they can carry information. The basic idea of a model, “correlation theory of brain function” is that, within a network of anatomical connections, smaller topological networks—cell assemblies in other words—can develop by means of synaptic modulation. This modulation is supposed to occur on two different timescales. Correlated activation of a set of neurons activates the synaptic connections between these neurons, while uncorrelated activation deactivates them. The correlation theory is neutral with regard to the neurophysiological types of correlated activity. The original idea refers to correlations between irregular spike trains or bursts of single neurons. A special case is the temporal correlation of rhythmic, or oscillatory, activity, which can be observed on the single neuron level as well as on the macroscopic level.