| Neuronal morphology is a key mediator of neuronal function, defining the profile of connectivity and shaping signal integration and propagation. Reconstructing neurite processes is technically challenging and thus data has historically been relatively sparse. Data collection and curation along with more efficient and reliable data production methods provide opportunities for the application of informatics to find new relationships and more effectively explore the field. This dissertation presents a method for aiding the development of data production as well as a novel representation and set of analyses for extracting morphological patterns.;The DIADEM Challenge was organized for the purposes of determining the state of the art in automated neuronal reconstruction and what existing challenges remained. As one of the co-organizers of the Challenge, I developed the DIADEM metric, a tool designed to measure the effectiveness of automated reconstruction algorithms by comparing resulting reconstructions to expert-produced gold standards and identifying errors of various types. It has been used in the DIADEM Challenge and in the testing of several algorithms since.;Further, this dissertation describes a topological sequence representation of neuronal trees amenable to various forms of sequence analysis, notably motif analysis, global pairwise alignment, clustering, and multiple sequence alignment. Motif analysis of neuronal arbors shows a large difference in bifurcation type proportions between axons and dendrites, but that relatively simple growth mechanisms account for most higher order motifs. Pairwise global alignment of topological sequences, modified from traditional sequence alignment to preserve tree relationships, enabled cluster analysis which displayed strong correspondence with known cell classes by cell type, species, and brain region. Multiple alignment of sequences in selected clusters enabled the extraction of conserved features, revealing mouse neocortical pyramidal cell axons and rodent neocortical dendritic targeting interneurons to be substantially more asymmetric than perisomatic-targeting interneurons. With optimization techniques adapted from the field of genomic alignment, these methods compose a framework with the potential to be made orders of magnitude more efficient. Moreover, the framework is capable of handling expanded sequence representations that include additional branch features, enabling analysis of correspondence and joint conservation of various morphological characteristics. |
