Network segregation in aging females and evaluation of the impact of sex steroid hormones - Hicks, Tracey H.; Magalhães, Thamires N. C.; Ballard, Hannah K.; Jackson, T. Bryan; Cox, Sydney J.; Bernard, Jessica A. (Frontiers in Human Neuroscience, 2023)
Males and females show differential patterns in connectivity in resting-state networks (RSNs) during normal aging, from early adulthood to late middle age. Age-related differences in network integration (effectiveness of specialized communication at the global network level) and segregation (functional specialization at the local level of specific brain regions) may also differ by sex. These differences may be due at least in part to endogenous hormonal fluctuation, such as that which occurs in females during midlife with the transition to menopause when levels of estrogens and progesterone drop markedly. A limited number of studies that have investigated sex differences in the action of steroid hormones in brain networks. Here we investigated how sex steroid hormones relate to age-network relationships in both males and females, with a focus on network segregation. Females displayed a significant quadratic relationship between age and network segregation for the cerebellar-basal ganglia and salience networks. In both cases, segregation was still increasing through adulthood, highest in midlife, and with a downturn thereafter. However, there were no significant relationships between sex steroid hormone levels and network segregation levels in females, and they did not exhibit significant associations between progesterone or 17β-estradiol and network segregation. Patterns of connectivity between the cerebellum and basal ganglia have been associated with cognitive performance and self-reported balance confidence in older adults. Together, these findings suggest that network segregation patterns with age in females vary by network, and that sex steroid hormones are not associated with this measure of connectivity in this cross-sectional analysis. Though this is a null effect, it remains critical for understanding the extent to which hormones relate to brain network architecture.