A Theory for the Emergence of Neocortical Network Architecture

Developmental programs that guide neurons and their neurites into specific subvolumes of the mammalian neocortex give rise to lifelong constraints for the formation of synaptic connections. To what degree do these constraints affect cortical wiring diagrams? Here we introduce an inverse modeling approach to show how cortical networks would appear if they were solely due to the spatial distributions of neurons and neurites. We find that neurite packing density and morphological diversity will inevitably translate into non-random pairwise and higher-order connectivity statistics. More importantly, we show that these non-random wiring properties are not arbitrary, but instead reflect the specific structural organization of the underlying neuropil. Our predictions are consistent with the empirically observed wiring specificity from subcellular to network scales. Thus, independent from learning and genetically encoded wiring rules, many of the properties that define the neocortex’ characteristic network architecture may emerge as a result of neuron and neurite development.