The neuroimaging field has made remarkable progress in mapping the brain’s functional architecture. The 2025 Organization for Human Brain Mapping (OHBM) meeting showcased exciting developments: functional gradient approaches, field theories, and continuum models that move beyond discrete network thinking to embrace the brain’s spatial continuity. Yet as our methods evolve, an interpretational gap persists. We are increasingly using eigenmode decompositions — from functional gradients to geometric modes — but treating eigenmodes as spatial templates with varying weights without a clear understanding of the fundamental principles governing harmonic phenomena. If these patterns truly represent eigenmodes, then to understand their origin and meaning, we must move beyond observational studies or mathematical predictions and look to the physical system itself and the principles that govern eigenmode phenomena in bounded systems in nature — principles well established in acoustics, structural dynamics, vibrational mechanics and fluid dynamics.
Cabral et al. (Mon,) studied this question.