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Dynamic Allostatic Modulation During Appraisal, Cognitive Challenge, and Across the Menstrual Cycle
- Babenko, Viktoriya
- Advisor(s): Grafton, Scott T.
Abstract
Unlike males, naturally menstruating females undergo a distinct hormonal monthly cycle, in which hypothalamic-pituitary-gonadal (HPG) sex hormones undergo drastic concentration changes across a single menstrual cycle. Furthermore, major regions of the brain are packed with receptors for both HPG and stress hormones. For these reasons, both HPG and stress hormones have numerous direct as well as indirect effects on the brain and body. The present research seeks to enhance the measurement of stress by developing definitive sympathetic drive measurement techniques to then record dynamic fluctuations of allostatic processes in relation to performance feedback and quantitative concentrations of HPG hormones within menstruating females. Current methods of measuring allostatic dynamics include the electrocardiogram (ECG) and impedance cardiography (ICG), which are typically combined to estimate actions of cardiac sympathetic nervous system (SNS); an indicator of stress responses mediated by the autonomic nervous system (ANS). Current methods of ICG are time intensive in subject preparation and analysis, and the measurements are vulnerable to non-reproducible subject-specific electrode configuration. With the present research, we present alternative state-of-the-art methods for tracking actions of the SNS. In Experiments 1 – 3, we present evidence of an electro-resonator, an accelerometer, and a trans-radial electrical bioimpedance velocimetry device (TREV) appropriately tracking SNS responses to physical stress tasks known to induce disruptions of allostatic processes. We further determine that the TREV device (Experiment 3) has the capacity to replace the need for ICG and ECG in estimating ANS activity, proving to be a reliable and capable method that is robust, time efficient, and readily accessible to researchers. In Experiment 4, we demonstrate the ability of false and predetermined performance appraisals to modulate dynamic allostatic responses, regardless of the individuals’ actual performance. Specifically, we find that the SNS acts as a perturbation-tracking system, in which compounding negative performance appraisal following a trend of positive feedback actuates a sympathetic drive. Conversely, we find that states of challenge and threat function at a grander, state-tracking level, in which any negative performance appraisal elicits a physiological response categorized as a “threat”, while only excessively outstanding performance feedback elicits a “challenge” response. Previous research has observed individual differences in challenge and threat states. However, the present findings demonstrate dynamic trial-by-trial changes within an individual, altering between states of challenge and threat. In Experiment 5, we examine the relationships between the concentrations of fluctuating cyclic HPG hormones at unique phases of the menstrual cycle and the modulation of behavior, allostasis, brain function, and brain morphology within individuals. We find that progesterone and follicle-stimulating-hormone (FSH) are related to a slower response time on hard arithmetic problems, while progesterone alone is related to a decrease in allostatic efficiency (i.e. SNS recovery) following feedback from hard trials. Furthermore, we find that estradiol is associated with an increased SNS response to both the onset of arithmetic problems and to the accompanying feedback that follows. In the brain, estradiol is found to be positively associated with the volume of the CA2/3 hippocampal subregion, yet negatively associated with resting-state functional coherence across the whole brain. Furthermore, both estradiol and luteinizing hormone (LH) are positively linked to white matter integrity across the brain. Ultimately, we believe that allostatic processes and the role of HPG hormones are at the core for understanding stress and well-being. We hope that the present combination of studies will provide better methods for tracking health within individuals, from moment-to-moment dynamics, to monthly cycles, and throughout the lifespan.
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