Neuroscience has entered a critical phase, with several international large-scale efforts devoted to the analysis and understanding of brain function. Studies exploiting new technologies for defining the connections in the brain, driving neuronal activity and modeling of neuronal processing are each hampered by our incomplete knowledge of the brain’s constituent parts. Fortunately, a bevy of single cell analyses are now being deployed to better understand the cells that constitute the functioning nervous system. These approaches offer insights into how cells function individually as the building blocks for understanding how they work in ensemble to create functional pathways. A set of emerging tools are available to assess the molecular and cell biology of single cells, including genomic analyses of somatic mutations, epigenomics to explain the influence of the environment upon genome expression, and transcriptomics to gain insight into the capacity of a cell to synthesize proteins and modulate its environment. Powerful technologies permit a variety of cell constituents to be addressed, including proteins, post-translational modifications, peptides and metabolites. Novel biosensors offer parallel analyses of cellular physiological states, reporting on the pH, membrane voltage and metabolic state. Multiplexed together, such methodologies offer a far more complete biological understanding than the more typical gene expression analyses, providing a rich picture of each single cell’s biology in their normal context – information needed to fully interpret the meaning of results from transcriptomics and proteomics studies.This Advanced Course is designed to provide the foundational knowledge needed to critically evaluate the design and execution of single cell omic studies, through daily lectures by the Faculty, critical reading of papers and extensive didactic discussion sessions. In the sessions, discussion will focus on the proper framing of scientific questions to best utilize these techniques, the limitations and advantages of each technique, and what the data can tell us about neuronal function.