TY - UNPB
T1 - Whole-brain dynamics and hormonal shifts throughout women's lifespan
T2 - From reproductive stages to menopausal transition and beyond
AU - Escrichs, Anira
AU - Avila-Varela, Daniela
AU - Patow, Gustavo A.
AU - Sanz Perl, Yonatan
AU - Pletzer, Belinda
AU - Ritter, Petra
PY - 2024/9/23
Y1 - 2024/9/23
N2 - Neuroimaging studies have identified significant age-related disruptions in whole-brain dynamics, yet the influence of women's reproductive stages and associated hormonal shifts remains underexplored. This study leverages resting-state fMRI data from the Human Connectome Project in Aging to examine brain dynamics through five reproductive stages: reproductive, late reproductive, perimenopause, early postmenopause, and late postmenopause. Our results indicate that the late reproductive stage is characterized by the highest dynamical complexity across whole-brain and resting-state networks, while brain dynamics significantly decline at menopause onset. Additionally, we employ machine learning classifiers using two approaches: (1) brain dynamics alone and (2) brain dynamics combined with follicle-stimulating hormone (FSH) and estradiol (brain-hormone model). Both models accurately distinguished reproductive stages, but the brain-hormone model outperformed the brain dynamics model. Key predictors included decreased estradiol, increased FSH, and altered brain dynamics in later life stages. These results offer a framework for assessing brain health across women's reproductive lifespan.
AB - Neuroimaging studies have identified significant age-related disruptions in whole-brain dynamics, yet the influence of women's reproductive stages and associated hormonal shifts remains underexplored. This study leverages resting-state fMRI data from the Human Connectome Project in Aging to examine brain dynamics through five reproductive stages: reproductive, late reproductive, perimenopause, early postmenopause, and late postmenopause. Our results indicate that the late reproductive stage is characterized by the highest dynamical complexity across whole-brain and resting-state networks, while brain dynamics significantly decline at menopause onset. Additionally, we employ machine learning classifiers using two approaches: (1) brain dynamics alone and (2) brain dynamics combined with follicle-stimulating hormone (FSH) and estradiol (brain-hormone model). Both models accurately distinguished reproductive stages, but the brain-hormone model outperformed the brain dynamics model. Key predictors included decreased estradiol, increased FSH, and altered brain dynamics in later life stages. These results offer a framework for assessing brain health across women's reproductive lifespan.
U2 - 10.1101/2024.09.23.614341
DO - 10.1101/2024.09.23.614341
M3 - Preprint
BT - Whole-brain dynamics and hormonal shifts throughout women's lifespan
PB - bioRxiv
ER -