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

The integration-segregation framework succinctly captures the tradeoff brains face between seamless function (more integration) in light of energetic constrains (more segregation). Despite its ubiquitous use in the field, there is no consensus on its definition with various graph theoretical properties being proposed. Here, we define the two states based on the underlying mechanism of neuronal coupling strength to provide a physical foundation for the framework. We find that younger adults’ brains are close to perfectly balancing between integration and segregation, while older adults’ brains veer off towards random signaling.

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Handling Editor: Emma Towlson

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