Temporal coding: Competition for coherence and new perspectives on assembly formation

Recent progress towards modeling temporal coding based on networks of coupled phase model oscillators (with amplitude dynamics that generalizes classical neural networks) is reviewed and possible directions of future research are sketched. The review concentrates on models that complement synchronization with so-called acceleration. The latter mechanism implies an increased phase velocity of neural units in case of stronger and/or more coherent input from the connected units. Assuming Hebbian storage of patterns, it is demonstrated that the inclusion of acceleration introduces a competition for coherence that has a profound and favorable effect on pattern recognition. Temporal assemblies, understood as phase-locked sets of coherent patterns, win the competition, while the other patterns become de-coherent or off-state. Outlook is given on paths towards including inhibition, hierarchical processing, and zero-lag synchronization despite time delays. We also mention possible relations to recent neurophysiological experiments that study the recoding of excitatory drive into phase shifts.