  A critical mystery in neuroscience lies in determining how anatomical
structure impacts the complex functional dynamics of human thought. How does
large-scale brain circuitry constrain states of neuronal activity and
transitions between those states? We address these questions using a maximum
entropy model of brain dynamics informed by white matter tractography. We
demonstrate that the most probable brain states -- characterized by minimal
energy -- display common activation profiles across brain areas: local
spatially-contiguous sets of brain regions reminiscent of cognitive systems are
co-activated frequently. The predicted activation rate of these systems is
highly correlated with the observed activation rate measured in a separate
resting state fMRI data set, validating the utility of the maximum entropy
model in describing neurophysiologial dynamics. This approach also offers a
formal notion of the energy of activity within a system, and the energy of
activity shared between systems. We observe that within- and between-system
energies cleanly separate cognitive systems into distinct categories, optimized
for differential contributions to integrated v.s. segregated function. These
results support the notion that energetic and structural constraints
circumscribe brain dynamics, offering novel insights into the roles that
cognitive systems play in driving whole-brain activation patterns.
