Before revision:  Estimating connectivity where the data are lacking generally relies on statistical relationships with known quantities and may be referred to as `predictive connectomics' . In addition, we touch upon the most prominent features of URLanization that are likely to influence predicted neuronal network dynamics, with a focus on  mammalian cerebral cortex.
After revision:  Estimating connectivity where the data are lacking generally relies on statistical relationships with known quantities . It is instructive, and in certain cases necessary, to URLanizational principles that link the plethora of data within a unifying framework where regularities of brain structure can be exploited to inform computational models . In addition, we touch upon the most prominent features of URLanization that are likely to influence predicted neuronal network dynamics, with a focus on mammalian cerebral cortex.