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Over the past decade extensive research has examined the segregation of the human brain into large-scale functional networks. The resulting network maps, i.e. parcellations, are now commonly used for the a priori identification of functional networks. However, the use of these parcellations, particularly in developmental and clinical samples, hinges on four fundamental assumptions: (1) the various parcellations are equally able to recover the networks of interest; (2) adult-derived parcellations well represent the networks in children's brains; (3) network properties, such as within-network connectivity, are reliably measured across parcellations; and (4) parcellation selection does not impact the results with regard to individual differences in given network properties. In the present study we examined these assumptions using eight common parcellation schemes in two independent developmental samples. We found …