  Whether it be in a man-made machine or a biological system, form and function
are often directly related. In the latter, however, this particular
relationship is often unclear due to the intricate nature of biology. Here we
developed a geometric deep learning model capable of exploiting the actual
structure of the cortex to learn the complex relationship between brain
function and anatomy from structural and functional MRI data. Our model was not
only able to predict the functional organization of human visual cortex from
anatomical properties alone, but it was also able to predict nuanced variations
across individuals.
