To support computation the activity of neurons must vary within a useful range, which highlights one potential value of homeostatic plasticity. The interconnectedness of the brain, however, introduces the possibility that combinations of homeostatic mechanisms can produce over-constraint in which not all set points can be satisfied. We use a simulation of the cerebellum to investigate the potential for such conflict and its consequences. In this instance the conflict produces perpetual drift and eventual saturation of synaptic weights. We show that these problems can be resolved for this network by a particular combination of sites and rules for plasticity. We also show that simulations that implement these rules for homeostatic plasticity are more resistant to forgetting. These results illustrate the general principle that homeostatic plasticity within a system must not set up conflicts in which mutually exclusive set points exist and that one consequence can be perpetual induction of plasticity.

为了支持计算，神经元的活动必须在一个有用的范围内变化，这突出了稳态可塑性的一个潜在价值。但是，大脑的相互连接性带来了以下可能性：稳态机制的组合可能会产生过度约束，在这种约束中，并非所有设定点都能得到满足。我们使用小脑的模拟来研究这种冲突及其后果的潜力。在这种情况下，冲突会导致永久漂移并最终使突触权重饱和。我们表明，通过站点和可塑性规则的特定组合，可以针对此网络解决这些问题。我们还表明，实现这些规则的稳态可塑性的模拟更易于遗忘。