Well, step down a few levels, if you want to put it that way. This model describes how connections between individual neurons (real physical cells, not abstrac

Well, step down a few levels, if you want to put it that way. This model describes how connections between individual neurons (real physical cells, not abstract "voting units") work. Inter-neuron connections (aka synapses) are the basis of long term memories/learning. The human cortex is a thin sheet (scrunched up in our head) that would stretch out to about the size of a tea towel, that has 6 layers of neurons, with a specific inter-layer connect pattern. A cortical column is what you'd get if you took a cookie cutter and cut a small cylindrical section, like a cookie, through the cortical sheet. It'll have those 6 layers of neurons, but maybe 100 neurons total (not 6) depending on what size cookie/column you're talking about. Any model of the brain (cortex) based on cortical columns is going to be a high level functional model of that mostly abstracts away what the individual neurons are doing. At this level of abstraction, you don't really care about the detailed behavior of individual neurons, since you're assuming that their aggregate behavior can adequately be described by your higher level model.