A Complex Network-Based Approach for Detecting and Characterizing Power Neurons in Drosophila.

Connectome analysis investigates the connections in the brain to understand how brain regions communicate with each other and how brain structure relates to its function. In recent years, researchers have reconstructed the structural connectome of several organisms, the most complex being Drosophila melanogaster. Two research groups have reconstructed the larval and adult connectomes of this organism and have applied network analysis to learn more about the Drosophila brain and its behavior. In this paper, we aim to continue the work of these two research groups at the larval and adult stages. Specifically, we construct several derived network representations and define a set of techniques that use the main concepts and measures of complex network analysis to extract new knowledge about Drosophila connectomes at the larval and adult stages. First, we conduct an Exploratory Data Analysis on the larval and adult connectomes to detect similarities and differences between them. Then, we define the concept of power neurons and illustrate an approach to detect them. Next, we demonstrate that power neurons represent a limited set of highly interconnected neurons that form a backbone and that, given their peculiar connectivity properties, may play a strategic role in brain functions. Finally, we extract a set of connectome motifs that allow us to learn about various features characterizing power neurons. We demonstrate that complex network analysis can allow the extraction of relevant knowledge about connectomes. Furthermore, we show that a very small number of power neurons can strongly influence all other neurons in the Drosophila brain.