Progesterone modulates theta oscillations in the frontal-parietal network

Ovarian hormone effects on cognitive flexibility in social contexts: Evidence from resting-state and task-based fMRI

Accumulating evidence suggests that the menstrual cycle and its endogenous ovarian hormones, including progesterone (PROG) and estradiol (E2), affect cognitive performance in women, particularly by modulating the prefrontal regions. In this study, we investigated whether differences in PROG and E2 levels modulate attentional control by affecting the prefrontal cognitive control areas. An fMRI scan was conducted on 53 naturally cycling healthy women in their late follicular phase (FP, n = 28) or mid-luteal phase (LP, n = 25) to examine the resting and task states during the completion of a face‒gender Stroop task. PROG was found to be positively correlated with the nodal efficiency of the inferior frontal gyrus (IFG) in the resting-state executive control network. At the behavioral level, while accuracy in categorizing male faces remained similar, participants in the mid-LP were significantly more accurate in categorizing female faces than those in the late FP. At the neural level, both the univariate and multivariate results indicated that higher levels of PROG enhance the detection and resolution of female incongruent faces through the activation of the bilateral IFG. These findings expand evidence of the effects of ovarian hormones on prefrontal-based attentional control in the social context.

Prediction of brain sex from EEG: using large-scale heterogeneous dataset for developing a highly accurate and interpretable ML model

This study presents a comprehensive examination of sex-related differences in resting-state electroencephalogram (EEG) data, leveraging two different types of machine learning models to predict an individual's sex. We utilized data from the Two Decades-Brainclinics Research Archive for Insights in Neurophysiology (TDBRAIN) EEG study, affirming that gender prediction can be attained with noteworthy accuracy. The best performing model achieved an accuracy of 85% and an ROC AUC of 89%, surpassing all prior benchmarks set using EEG data and rivaling the top-tier results derived from fMRI studies. A comparative analysis of LightGBM and Deep Convolutional Neural Network (DCNN) models revealed DCNN's superior performance, attributed to its ability to learn complex spatial-temporal patterns in the EEG data and handle large volumes of data effectively. Despite this, interpretability remained a challenge for the DCNN model. The LightGBM interpretability analysis revealed that the most important EEG features for accurate sex prediction were related to left fronto-central and parietal EEG connectivity. We also showed the role of both low (delta and theta) and high (beta and gamma) activity in the accurate sex prediction. These results, however, have to be approached with caution, because it was obtained from a dataset comprised largely of participants with various mental health conditions, which limits the generalizability of the results and necessitates further validation in future studies. . Overall, the study illuminates the potential of interpretable machine learning for sex prediction, alongside highlighting the importance of considering individual differences in prediction sex from brain activity.

The estrous cycle modulates early-life adversity effects on mouse avoidance behavior through progesterone signaling

Early-life adversity (ELA) increases the likelihood of neuropsychiatric diagnoses, which are more prevalent in women than men. Since changes in reproductive hormone levels can also increase the probability of anxiety disorders in women, we examined the effects of ELA on adult female mice across the estrous cycle. We found that during diestrus, when progesterone levels are relatively high, ELA mice exhibit increased avoidance behavior and increased theta oscillation power in the ventral hippocampus (vHIP). We also found that diestrus ELA mice had higher levels of progesterone and lower levels of allopregnanolone, a neurosteroid metabolite of progesterone, in the vHIP compared with control-reared mice. Progesterone receptor antagonism normalized avoidance behavior in ELA mice, while treatment with a negative allosteric modulator of allopregnanolone promoted avoidance behavior in control mice. These results suggest that altered vHIP progesterone and allopregnanolone signaling during diestrus increases avoidance behavior in ELA mice.

Attentional bias towards appealing and disgusting food cues varies with the menstrual cycle

Ovarian hormonal changes along the female menstrual cycle are believed to adapt women to the external environment through various adaptive strategies, including modulating appetite and eating behavior. We aimed to compare food-associated behavioral responses between two distinct menstrual phases (late follicular vs. mid-luteal) and investigate the underlying neural mechanism. Attentional bias towards visual food cues was repeatedly measured in 29 healthy young women during these two menstrual phases in a counterbalanced manner. Combining an emotional dot-probe task with frequency-tagged electroencephalography (EEG), we confirmed that the menstrual cycle modulated healthy women's attentional bias towards appealing and disgusting food cues. Women in the mid-luteal phase showed more avoidance of disgusting food cues, as reflected by a significantly longer response time. Steady-state visual evoked potential (SSVEP) results indicated that they exhibited a trend of transiently enhanced attentional bias towards appealing food cues and another trend of speeded attentional withdrawal from disgusting food cues during the mid-luteal phase relative to the late follicular phase, albeit non-significant after correction for multiple testing. Moreover, a significantly larger P3 amplitude was evoked by probes following the presentation of disgusting food cues in the mid-luteal phase than the late follicular phase. These findings indicate divergent attentional deployments on emotional food cues across menstrual phases and suggest the mid-luteal phase as a relatively sensitive stage in the menstrual cycle for women to regulate their appetite and eating behavior.

In search of sex-related mediators of affective illness

Sex differences in the rates of affective disorders have been recognized for decades. Studies of physiologic sex-related differences in animals and humans, however, have generally yielded little in terms of explaining these differences. Furthermore, the significance of these findings is difficult to interpret given the dynamic, integrative, and highly context-dependent nature of human physiology. In this article, we provide an overview of the current literature on sex differences as they relate to mood disorders, organizing existing findings into five levels at which sex differences conceivably influence physiology relevant to affective states. These levels include the following: brain structure, network connectivity, signal transduction, transcription/translation, and epigenesis. We then evaluate the importance and limitations of this body of work, as well as offer perspectives on the future of research into sex differences. In creating this overview, we attempt to bring perspective to a body of research that is complex, poorly synthesized, and far from complete, as well as provide a theoretical framework for thinking about the role that sex differences ultimately play in affective regulation. Despite the overall gaps regarding both the underlying pathogenesis of affective illness and the role of sex-related factors in the development of affective disorders, it is evident that sex should be considered as an important contributor to alterations in neural function giving rise to susceptibility to and expression of depression.

Causal role of frontal-midline theta in cognitive effort: a pilot study

Frontal-midline theta (FMT) oscillations are increased in amplitude during cognitive control tasks. Since these tasks often conflate cognitive control and cognitive effort, it remains unknown if FMT amplitude maps onto cognitive control or effort. To address this gap, we utilized the glucose facilitation effect to manipulate cognitive effort without changing cognitive control demands. We performed a single-blind, crossover human study in which we provided participants with a glucose drink (control session: volume-matched water) to reduce cognitive effort and improve performance on a visuospatial working memory task. Following glucose consumption, participants performed the working memory task at multiple time points of a 3-h window to sample across the rise and fall of blood glucose. Using high-density electroencephalography (EEG), we calculated FMT amplitude during the delay period of the working memory task. Source localization analysis revealed that FMT oscillations originated from bilateral prefrontal cortex. We found that glucose increased working memory accuracy during the high working memory load condition but decreased FMT amplitude. The decrease in FMT amplitude coincided with both peak blood glucose elevation and peak performance enhancement for glucose relative to water. Therefore, the positive association between glucose consumption and task performance provided causal evidence that the amplitude of FMT oscillations may correspond to cognitive effort, rather than cognitive control. Due to the COVID-19 pandemic, data collection was terminated prematurely; the preliminary nature of these findings due to small sample size should be contextualized by rigorous experimental design and use of a novel causal perturbation to dissociate cognitive effort and cognitive control.NEW & NOTEWORTHY We investigated whether frontal-midline theta (FMT) oscillations tracked with cognitive control or cognitive effort by simultaneous manipulation of cognitive control demands in a working memory task and causal perturbation of cognitive effort using glucose consumption. Facilitation of performance from glucose consumption corresponded with decreased FMT amplitude, which provided preliminary causal evidence for a relationship between FMT amplitude with cognitive effort.