Recovery of computation capability for neural networks from damaged states using self-organized criticality.

The article presents an investigation of the computational capability for the neural networks to recover their functions when damage through lesion or aging. It states the construction of 300 integrate-and-fire neurons with random connections. The investigation uses dynamic synapses model so that the neural networks will exhibit a self-organized criticality. It confirms that the features of self-organized criticality in the damaged neural networks could be maintained by dynamic synapses.