A remarkable property of most excitatory synapses in the central nervous system is their ability to undergo activity-dependent long-lasting changes in synaptic strength. In this context, phenomena like long-term potentiation (LTP) and long-term depression (LTD) have been most intensively studied as cellular models for learning and memory (Malenka and Bear, 2004). However, nonsupervised Hebbian forms of plasticity tend to run out of balance and consequently lead to unstable neuronal networks. This quandary is referred to as the “plasticity-stability dilemma.” Thus, a mechanism is needed that maintains an appropriate level of total excitation within a network but still allows Hebbian plasticity to occur.