Amygdala/hippocampal activation during the menstrual cycle: Evidence for lateralization of effects across different tasks

Stress and rumination in Premenstrual Syndrome (PMS): Identifying stable and menstrual cycle-related differences in PMS symptom severity

Since the inclusion of Premenstrual Dysphoric Disorder (PMDD) as a mood disorder in the DSM-5, Premenstrual Syndrome (PMS) symptoms have received more attention from researchers and clinicians. In this large-scale study, we investigated core psychological concepts relevant to mood disorder vulnerability between people with 1) no to mild, 2) moderate to severe, and 3) PMDD levels of PMS symptoms. Several trait measures related to mood disorders including depressive symptoms, feelings of stress and anxiety, and ruminative thinking were measured (single measurement, N = 380) along with state (momentary) reports of stress and stress-related perseverative thinking (measured twice, once in the follicular and once in the premenstrual/luteal phase, N = 237). We consistently observed that participants with higher severity of PMS symptoms also scored higher on depression, anxiety, stress, and rumination (trait measures). We also found consistent increases in momentary stress and stress-related perseverative ruminative thinking with increased PMS symptoms at each of our two test moments (in the middle of the follicular and premenstrual/luteal phase respectively). Interestingly, we did not find significant differences between our two test moments for any group, despite PMS being characterized by specific systems in the premenstrual/luteal phase. However, this could be due to noise surrounding the testing moments due to the temporal resolution of the questionnaires and the menstrual cycle estimation method. Nevertheless, these results suggest that stress and rumination are important psychological mechanisms to consider in PMS. Future PMS research studying stress and rumination on a day-to-day basis in combination with hormonal measures is warranted.

Attentional networks during the menstrual cycle

The menstrual cycle is characterized partially by fluctuations of the ovarian hormones estradiol (E2) and progesterone (P4), which are implicated in the regulation of cognition. Research on attention in the different stages of the menstrual cycle is eclectic with discrepancies in attention definitions, and the three attentional networks (alerting, orienting and executive) and their interaction were not explored during the menstrual cycle. In the current study, we used the ANT-I (attentional network test - interactions) to examine naturally cycling women (NC) and women using oral contraceptives (OC). We tested their performance at two time points that fit, in natural cycles, the follicular phase and the luteal phase. We found no differences in performance between the two time points (day 4 / day 18) for the OC group: the response pattern replicated known ANT-I findings. However, the NC group showed differences between the two time points. In the follicular phase, responses replicated known ANT-I results, but in the luteal phase, alertness did not interact with executive and orienting networks, resulting in a larger congruency effect (executive network) when attention was not oriented to the target in alerting and no alerting conditions. Results-driven exploratory regression analysis of E2 and P4 suggested that change in P4 from the follicular phase/day 4 to the luteal phase/day 18 was a mediator for the alerting effect found between groups. In conclusion, the alerting state, found with or without alertness manipulation, suggests that there is a progesterone-mediated activation of the alerting system during the luteal phase.

The Menstrual Cycle Modulates Whole-Brain Turbulent Dynamics

Brain dynamics have recently been shown to be modulated by rhythmic changes in female sex hormone concentrations across an entire menstrual cycle. However, many questions remain regarding the specific differences in information processing across spacetime between the two main follicular and luteal phases in the menstrual cycle. Using a novel turbulent dynamic framework, we studied whole-brain information processing across spacetime scales (i.e., across long and short distances in the brain) in two open-source, dense-sampled resting-state datasets. A healthy naturally cycling woman in her early twenties was scanned over 30 consecutive days during a naturally occurring menstrual cycle and under a hormonal contraceptive regime. Our results indicated that the luteal phase is characterized by significantly higher information transmission across spatial scales than the follicular phase. Furthermore, we found significant differences in turbulence levels between the two phases in brain regions belonging to the default mode, salience/ventral attention, somatomotor, control, and dorsal attention networks. Finally, we found that changes in estradiol and progesterone concentrations modulate whole-brain turbulent dynamics in long distances. In contrast, we reported no significant differences in information processing measures between the active and placebo phases in the hormonal contraceptive study. Overall, the results demonstrate that the turbulence framework is able to capture differences in whole-brain turbulent dynamics related to ovarian hormones and menstrual cycle stages.

The Menstrual Cycle Alters Resting-State Cortical Activity: A Magnetoencephalography Study

Resting-state neural oscillations are used as biomarkers for functional diseases such as dementia, epilepsy, and stroke. However, accurate interpretation of clinical outcomes requires the identification and minimisation of potential confounding factors. While several studies have indicated that the menstrual cycle also alters brain activity, most of these studies were based on visual inspection rather than objective quantitative measures. In the present study, we aimed to clarify the effect of the menstrual cycle on spontaneous neural oscillations based on quantitative magnetoencephalography (MEG) parameters. Resting-state MEG activity was recorded from 25 healthy women with normal menstrual cycles. For each woman, resting-state brain activity was acquired twice using MEG: once during their menstrual period (MP) and once outside of this period (OP). Our results indicated that the median frequency and peak alpha frequency of the power spectrum were low, whereas Shannon spectral entropy was high, during the MP. Theta intensity within the right temporal cortex and right limbic system was significantly lower during the MP than during the OP. High gamma intensity in the left parietal cortex was also significantly lower during the MP than during the OP. Similar differences were also observed in the parietal and occipital regions between the proliferative (the late part of the follicular phase) and secretory phases (luteal phase). Our findings suggest that the menstrual cycle should be considered to ensure accurate interpretation of functional neuroimaging in clinical practice.

Neuroimaging the menstrual cycle: A multimodal systematic review

Increasing evidence indicates that ovarian hormones affect brain structure, chemistry and function of women in their reproductive age, potentially shaping their behavior and mental health. Throughout the reproductive years, estrogens and progesterone levels fluctuate across the menstrual cycle and can modulate neural circuits involved in affective and cognitive processes. Here, we review seventy-seven neuroimaging studies and provide a comprehensive and data-driven evaluation of the accumulating evidence on brain plasticity associated with endogenous ovarian hormone fluctuations in naturally cycling women (n = 1304). The results particularly suggest modulatory effects of ovarian hormones fluctuations on the reactivity and structure of cortico-limbic brain regions. These findings highlight the importance of performing multimodal neuroimaging studies on neural correlates of systematic ovarian hormone fluctuations in naturally cycling women based on careful menstrual cycle staging.

Human menstrual cycle variation in subcortical functional brain connectivity: a multimodal analysis approach

Increasing evidence suggests that endogenous sex steroid changes affect human brain functional connectivity, which could be obtained by resting-state fMRI (RS-fMRI). Nevertheless, RS studies on the menstrual cycle (MC) are underrepresented and yield inconsistent results. We attribute these inconsistencies to the use of various methods in exploratory approaches and small sample sizes. Hormonal fluctuations along the MC likely elicit subtle changes that, however, may still have profound impact on network dynamics when affecting key brain nodes. To address these issues, we propose a ROI-based multimodal analysis approach focusing on areas of high functional relevance to adequately capture these changes. To that end, sixty naturally cycling women underwent RS-fMRI in three different cycle phases and we performed the following analyses: (1) group-independent component analyses to identify intrinsic connectivity networks, (2) eigenvector centrality (EC) as a measure of centrality in the global connectivity hierarchy, (3) amplitude of low-frequency fluctuations (ALFF) as a measure of oscillatory activity and (4) seed-based analyses to investigate functional connectivity from the ROIs. For (2)–(4), we applied a hypothesis-driven ROI approach in the hippocampus, caudate and putamen. In the luteal phase, we found (1) decreased intrinsic connectivity of the right angular gyrus with the default mode network, (2) heightened EC for the hippocampus, and (3) increased ALFF for the caudate. Furthermore, we observed (4) stronger putamen–thalamic connectivity during the luteal phase and stronger fronto-striatal connectivity during the pre-ovulatory phase. This hormonal modulation of connectivity dynamics may underlie behavioural, emotional and sensorimotor changes along the MC.

Neurobiological mechanisms underlying sex-related differences in stress-related disorders: Effects of neuroactive steroids on the hippocampus

Men and women differ in their vulnerability to a variety of stress-related illnesses, but the underlying neurobiological mechanisms are not well understood. This is likely due to a comparative dearth of neurobiological studies that assess male and female rodents at the same time, while human neuroimaging studies often don't model sex as a variable of interest. These sex differences are often attributed to the actions of sex hormones, i.e. estrogens, progestogens and androgens. In this review, we summarize the results on sex hormone actions in the hippocampus and seek to bridge the gap between animal models and findings in humans. However, while effects of sex hormones on the hippocampus are largely consistent in animals and humans, methodological differences challenge the comparability of animal and human studies on stress effects. We summarise our current understanding of the neurobiological mechanisms that underlie sex-related differences in behavior and discuss implications for stress-related illnesses.

Phase of the menstrual cycle affects engagement of attention with emotional images

Changes that occur during the menstrual cycle affect various aspects of behavior, cognition, and emotion. Here, we focused on potential differences between early follicular and midluteal phases in the way women process images of behaviorally relevant content categories: children, threat, disgust, erotic scenes, low- and high-calorie food. Using eye-tracking, we examined women's engagement of attention in the key region of each image in a free-viewing condition. Specifically, we tested how quickly attention was attracted to these regions and for how long it was held there. Participants took part in two experimental sessions, one in the early follicular and one in the midluteal phase. The results showed that in the midluteal phase attention was attracted to the key region earlier than in the early follicular phase: the first fixation more often fell within the key region and there were fewer fixations preceding it. While the effect of the phase in terms of the capture of attention did not depend on the image category, the effect regarding the hold of attention was category-specific, concerning the disgust category only. Specifically, in the midluteal phase the duration of the exploration of the key region between reaching it for the first time and first exiting it was shorter, which might be due to heightened sensitivity to disgusting stimuli in this period. Overall, our results indicate the occurrence of changes in attentional processing of emotional scenes related to the menstrual cycle, which seem to differ depending on the aspect of attention deployment: in the midluteal phase the effect of enhancing orienting was general and concerned any important visual information, whereas the effect of the shortened hold of attention appeared to be limited to specific content.

Identifying predictors of within-person variance in MRI-based brain volume estimates

Adequate reliability of measurement is a precondition for investigating individual differences and age-related changes in brain structure. One approach to improve reliability is to identify and control for variables that are predictive of within-person variance. To this end, we applied both classical statistical methods and machine-learning-inspired approaches to structural magnetic resonance imaging (sMRI) data of six participants aged 24-31 years gathered at 40-50 occasions distributed over 6-8 months from the Day2day study. We explored the within-person associations between 21 variables covering physiological, affective, social, and environmental factors and global measures of brain volume estimated by VBM8 and FreeSurfer. Time since the first scan was reliably associated with Freesurfer estimates of grey matter volume and total cortex volume, in line with a rate of annual brain volume shrinkage of about 1 percent. For the same two structural measures, time of day also emerged as a reliable predictor with an estimated diurnal volume decrease of, again, about 1 percent. Furthermore, we found weak predictive evidence for the number of steps taken on the previous day and testosterone levels. The results suggest a need to control for time-of-day effects in sMRI research. In particular, we recommend that researchers interested in assessing longitudinal change in the context of intervention studies or longitudinal panels make sure that, at each measurement occasion, (a) a given participant is measured at the same time of day; (b) all participants are measured at about the same time of day. Furthermore, the potential effects of physical activity, including moderate amounts of aerobic exercise, and testosterone levels on MRI-based measures of brain structure deserve further investigation.

Cortical and subcortical changes in patients with premenstrual syndrome

BACKGROUND

Premenstrual syndrome (PMS) is characterized by a series of emotional, physical and behavioral symptoms. Although PMS is related to dysfunctions of the central nervous system, the neuropathological mechanism of PMS still has not been clearly established. The aim of this study is to evaluate potential differences in both cortical thickness and subcortical volumes in PMS patients compared to healthy controls (HCs).

METHODS

Twenty PMS patients and twenty HCs underwent a structural magnetic resonance imaging scan and clinical assessment. Cortical thickness and subcortical volumes were computed using the FreeSurfer image analysis suite. Relationships between cortical thickness/subcortical volumes and the daily rating of severity of problems (DRSP) score were then measured in patients.

RESULTS

Compared to HCs, PMS patients exhibited reduced cortical thickness in the medial prefrontal cortex (MPFC), orbitofrontal cortex (OFC) and insula, and increased subcortical volumes of the amygdala, thalamus and pallidum. Furthermore, negative correlations were detected between the DRSP and cortical thickness in the anterior cingulate cortex and precuneus.

LIMITATIONS

The study is limited by a small sample size and narrow age range of participants.

CONCLUSIONS

Our findings indicate that the abnormal morphological changes are mainly implicated in emotional regulation and visceral perception in PMS patients. We hope that our study may contribute to a better understanding of PMS.

Larger volume and different functional connectivity of the amygdala in women with premenstrual syndrome

OBJECTIVES

To assess structural and functional changes of the amygdala due to premenstrual syndrome (PMS) using magnetic resonance imaging (MRI).

METHODS

Twenty PMS patients and 21 healthy control (HC) subjects underwent a 6-min resting-state fMRI scan during the luteal phase as well as scanning high-resolution T1-weighted images. Subcortical amygdala-related volume and functional connectivity (FC) were estimated between the two groups. Each subject completed a daily record of severity of problems (DRSP) to measure the severity of clinical symptoms.

RESULTS

Greater bilateral amygdalae volumes were found in PMS patients compared with HC subjects, and PMS patients had increased FC between the amygdala and certain regions of the frontal cortex (e.g. medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), right precentral gyrus), the right temporal pole and the insula, as well as decreased FC between the bilateral amygdalae and the right orbitofrontal cortex and right hippocampus. The strength of FC between the right amygdala and right precentral gyrus, left ACC and left mPFC were significantly and positively correlated with DRSP scores in PMS patients.

CONCLUSIONS

Our findings may improve our understanding of the neural mechanisms involved in PMS.

KEY POINTS

• Functional and structural MRI used to explore amygdala in PMS patients. • Aberrant amygdala structural and functional connectivity were found in PMS patients. • Amygdala strength FC was positively correlated with individual clinical symptom scores.

Estrogen- and progesterone-mediated structural neuroplasticity in women: evidence from neuroimaging

There is substantial evidence that the ovarian sex hormones, estrogen and progesterone, which vary considerably over the course of the human female lifetime, contribute to changes in brain structure and function. This structured, quantitative literature reviews aims to summarize neuroimaging literature addressing physiological variation in brain macro- and microstructure across an array of hormonal transitions including the menstrual cycle, use of hormonal contraceptives, pregnancy, and menopause. Twenty-five studies reporting structural neuroimaging of women, addressing variation across hormonal states, were identified from a structured search of PUBMED and were systematically reviewed. Although the studies are heterogenous with regard to methodology, overall the results point to overlapping areas of hormone related effects on brain structure particularly affecting the structures of the limbic system. These findings are in keeping with functional data that point to a role for estrogen and progesterone in mediating emotional processing.