  Recently we developed a novel method for assessing the hierarchical
modularity of functional brain networks - the probability associated community
estimation(PACE). The PACE algorithm is unique in that it permits a dual
formulation, thus yielding equivalent connectome modular structure regardless
of whether considering positive or negative edges. This method was rigorously
validated using F1000 and HCP data. We detected novel sex differences in
resting-state connectivity that were not previously reported. This current
study more thoroughly examined sex differences as a function of age and their
clinical correlates, with findings supporting a basal configuration framework.
To this end, we found that men and women do not significantly differ in the
22-25 age range. However, these same non-significant differences attained
statistical significance in the 26-30 age group, while becoming highly
statistically significant in the 31-35 age group. At the most global level,
areas of diverging sex difference include parts of the prefrontal cortex and
the temporal lobe, amygdala, hippocampus, inferior parietal lobule, posterior
cingulate, and precuneus. Further, we identified statistically different
self-reported summary scores of inattention, hyperactivity, and anxiety
problems between men and women. These self-reports additionally divergently
interact with age and the basal configuration between sexes. In sum, our study
supports a paradigm change in how we conceptualize the functional connectome,
shifting away from simple concepts, and towards thinking globally and
probabilistically how the brain exhibits dynamic sex-specific connectivity
configuration as a function of age, and the role this sex-by-age configuration
at rest might play in mental health frequency and presentation, including
symptom patterns in depression.
