The goal of neuroscience is to determine how the brain controls behavior – in essence to establish the neural “wiring diagram” that underlies function. Progress towards this goal has been stymied by the brain’s complexity, and the fact that we lack a “parts list” for the brain, i.e. a detailed understanding of the many different types of neurons that comprise each brain region. Our team of neuroscientists (led by John Campbell) and bioinformaticians (led by Linus Tsai) are using high throughput single cell transcriptomics combined with computational analyses to establish the neuronal “parts lists” for brain regions controlling interesting motivational drives (for example hunger) and metabolism. For an example see Campbell JN et al., Nat Neurosci 20: 484-496, 2017 (PMID: 28166221). By analyzing all genes expressed by each neuron and comparing this with genes expressed by all the other neurons, we are establishing the “parts list” of neurons for key regions of the brain. These studies are identifying neurons previously known to exist, and very importantly, many new neurons of unknown function. Because these analyses are based on genome-wide transcriptomic profiles, and because the genes expressed by a neuron subtype determine its function, these datasets, combined with the existing scientific literature, are fertile ground for generating important new hypotheses about brain function. As a Scholars in Medicine Project, students will take these neuron subtype datasets, mine them for functionally important, uniquely expressed genes, research relevant literature on these uniquely expressed genes, and then synthesize new hypotheses about the role of novel neuron subtypes in controlling behavior. Compelling hypotheses that result from this process will be selected by the team of neuroscientists for further exploration using the latest advanced neuroscience approaches – for examples, see publications for “Lowell BB”, and also see: https://www.hms.harvard.edu/dms/neuroscience/fac/Lowell.php Students can immerse themselves in any steps of the process depending on their interests, skill sets, etc. At the most basic level, with guidance from members of the team, students will work with processed datasets and perform literature searches on functionally relevant, uniquely expressed genes – with the goal of generating new hypotheses regarding function. Depending on the students’ interests and capabilities, they may also become involved in the “afferent arm” of such research – i.e. in the generation of the transcriptomic datasets and/or bioinformatics analysis of such datasets, etc., or alternatively they may become involved in the “efferent arm” of such research – in the testing of generated hypotheses using the advanced neuroscience techniques mentioned above. This project should be a great opportunity to learn about neuroscience, how the brain controls motivated drives and metabolism, and how one approaches large single cell datasets – all with the goal of making new discoveries about how the brain works.