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Much of our work in clinical neurosciences relies on knowledge obtained in non-human animals. However, in most cases, comparisons between the organization of the model species’ brain and the human brain are informal and post hoc. This is partly because comparing the organization of two species’ brains is traditionally labour-intensive and expensive work that relies on the sacrifice of many animals. Neuroimaging and other high-throughput methods for data acquisition have the potential to change this. I will present a framework for comparing brain organization across species using these new types of data. Originally developed for comparisons across primate species’ brains, we are now extending the work to the mouse, the most commonly used mammalian model species. The framework allows us to explicitly compare brain organization across species, at high resolution and at multiple levels of the neural hierarchy—from gene expression to functional networks. Furthermore, it enables us to quantify the limits of translation between the model and the human and to turn translational neuroscience into a quantitative endeavour.
