Approaching homeostasis in a binary neural network

Homeostasis-maintaining binary neural networks such as hierarchical temporal memories are provided. In various embodiments, a region of an artificial neural network is initialized. The region comprises a plurality of neurons and has a permanence value associated with each potential synaptic connection between neurons. The initialization comprises connecting a subset of the potential synaptic connections by synapses. A plurality of time-ordered inputs to the region is received. Some of the plurality of neurons are thereby caused to fire upon receipt of each time-ordered input. Upon receipt of each time-ordered input, for each potential synaptic connection between neurons, the permanence value is adjusted according to a firing sequence of the plurality of neurons. Those potential synaptic connections having a permanence value above a predetermined permanence threshold are connected when the total number of connected synapses in the region does not exceed a predetermined connectivity threshold. Synapses whose associated pre-synaptic neuron or post-synaptic neuron have more than a predetermined number of connected synapses are disconnected.