Idiosyncrasy and generalizability of contraceptive- and hormone-related functional connectomes across the menstrual cycle

Abstract

Neuroendocrinology has received little attention in human neuroscience research, resulting in a dearth of knowledge surrounding potent and dynamic modulators of cognition and behavior, as well as brain structure and function. This work addresses one such phenomenon by studying functional connectomics related to ovarian hormone fluctuations throughout the adult menstrual cycle. To do so, we used functional magnetic resonance imaging (fMRI) and hormone assessments from two dense, longitudinal datasets to assess variations in functional connectivity with respect to endogenous and exogenous endocrine factors throughout the menstrual cycle. First, we replicated prior findings that common, group-level and individual specific factors have similar relative contributions to functional brain network organization. Second, we found widespread connectivity related to hormonal contraceptive (HC) use, in addition to sparser estradiol- and progesterone-related connectivity, and differential generalizability of these subnetworks that suggests progestin-specific impacts on functional connectivity in HC users. These results provide novel insight into within-individual changes in brain organization across the menstrual cycle and the extent to which these changes are shared between individuals, illuminating understudied phenomena in reproductive health and important information for all neuroimaging studies that include participants who menstruate. Author SummaryEndocrine modulation of brain function across the menstrual cycle is poorly understood. Human neuroimaging research on the menstrual cycle has long relied on group- and or coarse, within-individual cycle stage-differences, overlooking considerable individual differences in brain organization, the menstrual cycle, and hormone concentrations. Here, we take a multi-dataset approach to identify idiosyncratic contraceptive- and hormone-related functional connectivity from within-individual neuroendocrine dynamics and then test the generalizability of this connectivity to other individuals. In doing so, we identified idiosyncratic hormone-responsive subnetworks that are somewhat generalizable to other individuals, though this generalizability is complicated by hormonal contraceptive use, potentially reflecting differential connectivity between contraceptive formulations. Thus, this work illuminates individual similarities and differences in neuroendocrine dynamics across the menstrual cycle.