The challenge involved in developing models for small, medium, and large networks is one of reducing the complexity by making valid simplifying assumptions in and extending the Hodgkin-Huxley neuronal model appropriately to design those models ( see Chapter 9 of Sterratt, D., Graham, B., Gillies, A., & Willshaw, D. (2011),[1] Kotter, R., Nielson, P., Dyhrfjeld-Johnson, J., Sommer, F. T., & Northoff, G. (2002),[2] and Chapter 9 of Gerstner, W., & Kistler, W. (2002)[3]). Network models can be classified as either network of neurons propagating through different levels of cortex or neuron populations interconnected as multilevel neurons. The spatial positioning of neuron could be 1-, 2- or 3-dimensional; the latter ones are called small-world networks as they are related to local region.