Structure Guides Function: Beyond Pairwise Neural Interactions

ABSTRACT A central theme in Jon Kaas’ research, celebrated in this issue, is the relationship between brain structure and function. As a tribute, we examine how certain neuroanatomical structures enable higher order (higher arity) functions whose joint effects cannot be recovered from pairwise measurements. Specifically, we argue that neurons exploit coincident input detection to realize higher order operations that cannot be derived by studying any of the pairwise combinations in isolation. Pairwise statistics can miss these irreducible higher order (more‐than‐pairwise) effects. We advocate for an extension of graph‐based models to hypergraphs to formally capture and analyze these irreducible higher order neural interactions. Based on several recent studies, we discuss both the applicability and benefits of higher order neural data analyses.