The exponential distance rule-based network model predicts topology and reveals functionally relevant properties of the <i>Drosophila</i> projectome

Studying structural brain networks has witnessed significant advancement in recent decades. Findings revealed a geometric principle, the exponential distance rule (EDR) showing that the number of neurons decreases exponentially with the length of their axons. This neuron-level information was used to build a region-level EDR network model that was able to explain various characteristics of interareal cortical networks in macaques, mice, and rats. The complete connectome of the <i>Drosophila</i> has recently been mapped providing information also about the network of neuropils (projectome). A recent study demonstrated the presence of the EDR in the <i>Drosophila</i>. In our study, we first revisit the EDR itself and precisely measure the characteristic decay rate. Next, we demonstrate that the EDR model effectively accounts for numerous binary and weighted properties of the projectome. Our study illustrates that the EDR model is a suitable null model for analyzing networks of brain regions, as it captures properties of region-level networks in very different species. The importance of the null model lies in its ability to facilitate the identification of functionally significant features not caused by inevitable geometric constraints, as we illustrate with the pronounced asymmetry of connection weights important for functional hierarchy.