Biological Implications of Regional Graph Properties in the Adult Drosophila Brain Connectome

Abstract

The recently completed Drosophila hemibrain connectome presents a large and detailed set of information about neural structure (Scheffer et al., 2020). This thesis conducts a computational analysis via graph theory of the hemibrain connectome as a network. Through contextualizing analyses in past functional research, we grant insight into previously functionally unexplored areas of the connectome and their possible biological functions. Regionally focused graph analyses conducted in R define the network properties of areas such as the superior neuropils (SNP), ventrolateral neuropils (VLNP), ventromedial neuropils (VMNP), and inferior neuropils (INP) in the Drosophila connectome alongside the mushroom body, central complex, and antennal lobe. We establish high connectivity of the SNP, VLNP, VMNP, and INP with the rest of the hemibrain, suggesting functional importance. We also determine that hemibrain structure (many interconnections and highly defined subdivisions) enables potential information-processing efficiency of the hemibrain network as a whole. These and other analyses demonstrate that a computationally driven connectomic analysis can be combined effectively with conclusions from functional data to better understand biological neural networks.