A neural cocktail-party processor
Biological Cybernetics
Pattern segmentation in associative memory
Neural Computation
Assemblies as Phase-Locked Pattern Sets That Collectively Win the Competition for Coherence
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Temporal coding: competition for coherence and new perspectives on assembly formation
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Neuronal assembly dynamics in supervised and unsupervised learning scenarios
Neural Computation
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Temporal coding is studied for an oscillatory neural network model with synchronization and acceleration. The latter mechanism refers to increasing (decreasing) the phase velocity of each unit for stronger (weaker) or more coherent (decoherent) input from the other units. It has been demonstrated that acceleration generates the desynchronization that is needed for self-organized segmentation of two overlapping patterns. In this letter, we continue the discussion of this remarkable feature, giving also an example with several overlapping patterns. Due to acceleration, Hebbian memory implies a frequency spectrum for pure pattern states, defined as coherent patterns with decoherent overlapping patterns. With reference to this frequency spectrum and related frequency bands, the process of pattern retrieval, corresponding to the formation of temporal coding assemblies, is described as resulting from constructive interference (with frequency differences due to acceleration) and phase locking (due to synchronization).