Mapping Population Variability in the Human Brain

Brain imaging provides some of the most versatile and powerful tools in neuroscience. With the advent of population-level imaging, we can now study how the human brain relates to cognition, lifestyle, genetics, and disease. However, an outstanding challenge is how to create a valid basis for comparison across thousands of unique brains. Currently, analysis centres on either reducing population data to an over-simplistic population-average atlas, or analysing individuals in isolation, untethered from a biological reference to other subjects. Instead, we need to place individuals within the context of a far more complete description of the population. This requires a true "like-with-like" comparison that accounts for the unique structural folds, connections, and functional regions of each individual’s brain. To meet this challenge, we propose the Large Adaptive Neuroimage Atlas (LANA), a foundation model of population-level imaging data, along with a new platform to build and utilise this atlas. This transformative approach will allow small, focused studies to leverage big data, drive personalised therapeutic predictions, and enable the first high-resolution whole-genome-to-brain translation. We will create an accessible software platform to maximise LANA's impact, allowing researchers globally to discover complex links between the brain, genes, lifestyle, and disease.