UCSF

The integration-segregation framework is a popular first step to understand brain dynamics because it simplifies brain dynamics into two states based on global versus local signaling patterns. However, there is no consensus for how to best define the two states. Here, we map integration and segregation to order and disorder states from the Ising model in physics to calculate state probabilities, P int and P seg, from functional MRI data. We find that integration decreases and segregation increases with age across three databases. Changes are consistent with weakened connection strength among regions rather than topological connectivity based on structural and diffusion MRI data.