Identifying patterns of neuronal connectivity is critical for understanding functional and anatomical circuits that mediate pain perception. However, knowledge about the types and distribution of neurons in joint tissues have generally been limited to traditional 2-dimension histopathological and immunohistopathological approaches, and little to no information is available on connectivity and neuronal phenotypes. New technologies have emerged that allow for both trans-synaptic circuit analysis and precise control of neuronal firing, including the use of retrogradely transported viral vectors (i.e., pseudotyped rabies virus) and heterologous receptor activation. At the same time, 3-dimensional visualization of neuronal and vascular patterns have been advanced by tissue clearing techniques in conjunction with cell type specific fluorescent markers generated by intercrossing cell type specific Cre recombinase mouse lines with a variety of conditionally activated reporters. Finally, the advent of single cell RNA sequencing has allowed for extending cellular phenotyping to a molecular level that has not only increases analytic resolution, but also therapeutic targeting with greater disease specificity than previously possible. The development of high resolution spatial transcriptomics, i.e., MERFISH, allows for correlation and validation of scRNA-seq data. In this context, osteoarthritis of the knee joint is an optimal model for applying these tools as abundant genetic and surgical models are available for orthogonal validation of findings. Moreover, in the preclinical context, various therapeutic approaches including gene therapy have been shown to impact pain measures, and as such, they constitute an important interventional validation of molecular changes that are identified in neurons in the disease state. The fact that some of these therapies are now in clinical trial adds to the potential translational impact of the proposed preclinical findings here. Ultimately, the combination of both anatomic, 3-D, and molecular signatures will facilitate the translation into human tissues and biopsies, while maximizing the likelihood of relevant new therapeutic targets.