Abstract
Accuracy in facial emotion recognition has shown to vary with ovarian hormones, both in naturally cycling women, as well as in women taking oral contraceptives. It remains uncertain however, if specific – endogenous and exogenous – hormonal levels selectively impact recognition of certain basic emotions (or neutral faces) and if this relationship coincides with certain affective states. Therefore, we investigated 86 women under different hormonal conditions and compared their performance in an emotion recognition task as well as self-reported measures of affective states. Based on self-reported cycle days and ovulation testing, the participants have been split into groups of naturally cycling women during their early follicular phase (fNC, n = 30), naturally cycling women during their peri-ovulatory phase (oNC, n = 26), and women taking oral contraceptives (OC, n = 30). Participants were matched for age and did not differ in education or neuropsychological abilities. Self-reported anxiety and depressive affective state scores were similar across groups, but current affective state turned out to be significantly more negative in fNC women. Independent of negative affective state, fNC women showed a significantly higher negativity bias in recognizing neutral faces, resulting in a lower recognition accuracy of neutral faces compared to oNC and OC women. In the OC group only, negative affective state was associated with lower recognition accuracy and longer response times for neutral faces. Furthermore, there was a significant, positive association between disgust recognition accuracy and negative affective state in the fNC group. Low progesterone levels during the early follicular phase were linked to higher negative affective state, whereas in the peri-ovulatory phase they were linked to elevated positive affective state. Overall, previous findings regarding impaired emotion recognition during OC-use were not confirmed. Synthetic hormones did not show a correlation with emotion recognition performance and affective state. Considering the important role of emotion recognition in social communication, the elevated negativity bias in neutral face recognition found for fNC women may adversely impact social interactions in this hormonal phase.
Highlights
Women experience significant fluctuations of ovarian hormones over the menstrual cycle
Baseline levels of state anxiety and positive affective state at the beginning of the experimental session were comparable amongst women in different hormonal phases, whereas fNC women reported significantly higher negative affective state compared to oral contraceptives (OCs)-users [main effect: H(2) = 7.28, p = 0.026; fNC > OC: p = 0.044; fNC > oNC: p = 0.088; OC > oNC: p = 1.00]
Hormonal analyses using median tests confirmed that the women assigned to the respective groups differed in hormonal profiles accounting for endogenous as well as for exogenous sex hormones [EndoE2 vs. ExoE2: H(2) = 56.73, p < 0.001; EndoP vs. ExoP: X2(2) = 49.58, p < 0.001; Testosterone: H(2) = 7.92, p = 0.019]
Summary
Women experience significant fluctuations of ovarian hormones over the menstrual cycle. During the follicular phase at the beginning of the menstrual cycle estradiol and progesterone levels are low. Estradiol is rising until reaching its peak right before ovulation and abruptly decreasing with ovulation. Progesterone is rising coinciding with a second yet smaller increase of estradiol, with both hormones declining during the late luteal phase reaching the initial low levels during menstruation. To prevent pregnancy and facilitate safe family planning, millions of women rely on hormonal contraceptives such as oral contraceptives (OCs) during their reproductive years (United Nations [UN], 2020). OCs typically contain ethinyl estradiol (synthetic estrogen) and progestin (synthetic progesterone) that effectively suppress endogenous estradiol and progesterone levels and prevent ovulation (Petitti, 2003). Evidence is accumulating that endogenous as well as synthetic ovarian hormones impact women’s socio-affective processing, including facial emotion recognition (Derntl et al, 2008a; Hamstra et al, 2014, 2015, 2017; for reviews see: Montoya and Bos, 2017; Lewis et al, 2019; Pahnke et al, 2019; Gamsakhurdashvili et al, 2021a)
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