From further coverage at Space Daily: Most neural network models to date have been based on the Hebbian network, a simplified version of the real neural networks based exclusively on connectivity properties between neurons.

Ccortex adds to classical Hebbian connections a time-sensitive, analog representation of the shape of “spikes,” the pulsing patterns that enable neuron populations to communicate with each other. This allows Ccortex to tune vast populations of neurons and the information they hold to complex spiking patterns, adding a much higher level of complexity to a highly realistic simulation.

The Ccortex software emulation applies its Spiking Neuron Software Engine to a database that has a representation of the layered distribution of neural nets and detailed interconnections in the brain. The data closely emulates specialized regions of the human cortex, corpus callosum, anterior commissure, amygdale and hippocampus.

The emulation aims to actualize the estate of each neuron and its connections several times per second, maintaining a myriad of competing spiking patterns, while providing feedback and limited interaction with simplified versions of other nervous and sensory systems.