The exponential distance rule based network model predicts topology and reveals functionally relevant properties of the Drosophila projectome

TL;DR

This study demonstrates that the exponential distance rule (EDR) accurately models the topology of the Drosophila brain network, revealing properties relevant to brain function and providing a null model for identifying significant features beyond geometric constraints.

Contribution

The paper shows that the EDR model applies to Drosophila, extending its validity across species and offering a null model to analyze brain network properties and functional hierarchy.

Findings

EDR holds true in Drosophila brain networks

EDR model explains various network properties

Identifies functionally relevant asymmetries in connections

Abstract

Studying structural brain networks has witnessed significant advancement in recent decades. Findings have revealed a geometric principle, the exponential distance rule (EDR) showing that the number of neurons decreases exponentially with the length of their axons. An EDR based network model explained various characteristics of inter-areal cortical networks in macaques, mice, and rats. The complete connectome of the Drosophila fruit fly has recently been mapped at the neuronal level. Our study demonstrates that the EDR holds true in Drosophila, and the EDR model effectively accounts for numerous binary and weighted properties of neuropil networks, also called projectome. Our study illustrates that the EDR model is a suitable null model for analyzing networks of brain regions, as it captures geometric and physical constraints in very different species. The importance of the null model lies in its ability to facilitate the identification of functionally significant features that are not caused by inevitable geometric constraints, as we illustrate with the pronounced asymmetry of connection weights important for functional hierarchy.