reconstructed and are hence the most consistent connections across subjects whereas long-range connections are more prone to error. Also  this method forces a user to choose  somewhat ad hoc   the threshold for including a con- nection in the group-average matrix. Instead  we use an alternative method for generating a group-average connectomes whose edge-length distribution matches that of the typical single-participant distribution (Miˇsi´ c et al.  2015). Briefly  this method begins by first estimating the average number of connections of a given length in a typical participant’s connectome. Next  all pairs of nodes sep- arated by a comparable distance are identified and  from among this subset  the most consistent connections are added to the group-average connectivity ma- trix. Repeating this process for all distances yields a representative connectome that matches  almost exactly  the typical edge length distribution  but features only the most consistently expressed edges at each connection length. In this report  we test the hypothesis that the human connectome emerges as a consequence of both topological and spatial constraints  which we model as power-law functions. In doing so  we assume that the material/metabolic cost of fiber tracts can be equated to Euclidean distance separating its endpoints  rather than the actual integrated length of the curved tract. The argument for doing so is threefold. First  estimates of fiber length can only be obtained for completed streamlines  meaning that no estimates exist for connections that were absent in the observed tractography data. In order to fill in the missing fiber lengths  one can resort to fiber interpolation (i.e. using the distance/fiber length relationship of existing connections to estimate the fiber length of missing connections)  which necessarily introduces an additional source of uncertainty. Second  the relationship of fiber length and Euclidean distance is rather strong across our datasets: the amount of variance in fiber length accounted for by 24 5.5. CHUV Group-average matrix with fiber length - See Figures S10-S11