Menstrual cycle phase influences cognitive performance in women and modulates sex differences: A combined longitudinal and cross-sectional study of cognitive function in young adults

Menstrual cycle phase influences cognitive performance in women and modulates sex differences: A combined longitudinal and cross-sectional study of cognitive function in young adults | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Menstrual cycle phase influences cognitive performance in women and modulates sex differences: A combined longitudinal and cross-sectional study of cognitive function in young adults Angelika K. Sawicka, Katarzyna M. Michalak, Barbara Naparło, Adrià Bermudo-Gallaguet, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6264630/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Sex differences in cognitive performance have been widely studied, yet the role of sex hormones and their fluctuations across the menstrual cycle remains unclear. This study investigated cognitive performance differences between men and women, accounting for menstrual cycle phases, and examined associations between sex hormone levels and cognitive function. Seventy-one healthy young adults (42 women, 29 men) participated in the study. Women were tested twice, once during their menstrual (low oestradiol) phase and once during their pre-ovulatory (high oestradiol) phase. Men underwent a single assessment. Cognitive performance was evaluated using standardised tests that measured attention, processing speed, working memory, and visuospatial abilities. Blood samples were collected to measure oestradiol, progesterone, and testosterone levels. Women showed enhanced performance during the pre-ovulatory phase compared to the menstrual phase in working memory capacity (digit span forward: p = 0.04; backward max: p = 0.02) and attention switching (Trail making test B ( TMT B): p = 0.01). Sex differences in processing speed were observed only when men were compared to women in their menstrual phase (TMT A: p = 0.03; Stroop B: p = 0.04). These differences disappeared during the women's pre-ovulatory phase. While testosterone showed no significant correlations with cognitive measures, oestradiol and progesterone demonstrated distinct relationships. Positive correlations were shown with cognitive performance in men, and there were complex bidirectional relationships in women, but only during the menstrual phase. These findings suggest that cognitive differences between the sexes are modulated by hormonal status, with higher oestradiol levels potentially enhancing women's cognitive performance. Further research is needed to elucidate the complex mechanisms underlying these hormone-dependent cognitive changes. This study highlights the importance of considering the phase of the menstrual cycle when investigating sex differences in cognitive function. menstrual cycle phase sex hormones working memory attention sex differences oestrogen progesterone Figures Figure 1 Figure 2 Figure 3 Plain Language Summary This study examined how changes in sex hormone levels during women's menstrual cycles affect cognitive abilities and how these hormonal fluctuations influence cognitive differences between women and men. The research involved 71 young adults (42 women and 29 men) who completed various cognitive tasks measuring attention, processing speed, working memory, and visuospatial abilities. Women were tested twice - once during their menstrual phase (when estradiol levels are low) and again during their pre-ovulatory phase (when estradiol levels are high), while men were tested once. The results showed that women performed better on working memory and attention tasks during their pre-ovulatory phase compared to their menstrual phase. Men performed better in processing speed than women in their menstrual phase. Interestingly, these differences were not apparent when women were tested in the ovulatory phase of their menstrual cycle. The analysis also revealed that in men, higher estradiol and progesterone levels were associated with better cognitive performance, while in women, the relationships between hormones and cognition were more complex and only present during the menstrual phase. The findings of this study indicate that fluctuations in hormonal levels during a woman's menstrual cycle may contribute to variations in cognitive abilities observed between men and women. This research emphasises the importance of taking hormonal fluctuations into account when studying cognitive differences between the sexes. Highlights Sex hormone fluctuations during the menstrual cycle modulate cognitive differences between men and women. Women show improved working memory and attention during the pre-ovulatory phase compared to the early follicular phase. Sex differences in processing speed vanish when women are in the pre-ovulatory phase. Oestradiol correlates positively with cognition in men but shows mixed effects in women. Testosterone does not correlate with any cognitive functions in young adults. Introduction Hormones of the hypothalamic-pituitary-gonadal axis, which regulate reproductive functions, have multiple effects on brain development and function [ 1 ]. These effects are mediated through complex mechanisms involving neurotransmitter systems, synaptic plasticity, and neuronal excitability [ 2 , 3 ]. The irrefutable evidence for hormonal influences on brain function comes from the widespread distribution of hormone receptors throughout the central nervous system. Oestrogen receptors (ERs) are found throughout the brain—in the hypothalamus, pituitary, hippocampus, cortex, midbrain and brainstem [ 4 ]. ERs and progesterone receptors (PRs) are strategically located in brain regions involved in emotional and cognitive regulation [ 5 , 6 ]. Through these receptors, sex hormones influence cognitive function via multiple mechanisms, including the modulation of neurotransmitter systems, particularly the cholinergic and monoaminergic pathways, the regulation of synaptic plasticity, and effects on neural connectivity [ 2 , 7 ]. Progesterone specifically acts through the membrane component of the progesterone receptor 1 (PGRMC1) in the cerebellum, cortical regions, hippocampus and hypothalamic nuclei [ 8 ]. The menstrual cycle, characterised by dramatic fluctuations in sex hormone levels, provides a natural model for studying hormonal influence on cognition. The menstrual cycle begins with the early follicular phase, characterised by low progesterone and oestrogen levels. Oestrogen levels rise rapidly in the late follicular phase, showing a nearly eight-fold increase, and peaks one day before ovulation. The luteal phase sees a steady rise in progesterone levels that peak in the mid-luteal phase with an 80-fold increase, accompanied by a second oestrogen peak. Both hormone levels decline during the late luteal phase, reaching baseline shortly before the onset of menstruation [ 9 , 10 ]. Research shows that steroid hormones, their fluctuation and their receptors play a significant role in many brain functions, such as regulating socio-sexual behaviour, aggression, neurogenesis, learning and memory, stress, cognitive function, and mood and emotion [ 11 ]. It has been proven that oestrogen improves performance in prefrontal cortical-dependent learning in female rats [ 12 ] and rhesus monkeys [ 13 ], as well as in young adults and post-menopausal women [ 14 ]. According to research, higher oestrogen levels have a protective effect on cognitive functioning [ 4 ]. More specifically, oestrogen is involved in memory processes and can also affect different types of memory, such as episodic memory, working memory and long-term memory [ 15 ]. Furthermore, it may affect visuospatial functions, such as visuospatial orientation [ 16 ]. Regarding progesterone, an fMRI study proved that it modulates limbic and somatomotor networks, which can improve cognitive function in naturally cycling young women [ 17 ]. Both oestrogen and progesterone treatments have shown potential cognitive benefits in women, with progesterone showing better effects on verbal working memory [ 18 ]. Testosterone, on the other hand, activates a distributed cortical network, the ventral processing stream, during spatial cognition tasks, and the addition of testosterone improves spatial cognition in men [ 19 ]. According to research, testosterone also protects the brain against oxidative stress, serum deprivation-induced apoptosis and soluble amyloid-β (Aβ) toxicity [ 20 ]. Further evidence for the influence of sex hormones on cognitive functioning comes from studies of cognitive ageing in women and men, which is associated with significant changes in the physiological levels of sex hormones [ 21 ]. During menopause, women experience dramatic fluctuations and eventual decline in the neuroprotective hormones, such as oestrogen and progesterone, which is often accompanied by changes in cognitive performance [ 22 ]. A recent large-scale study of 731 post-menopausal women demonstrated that higher oestradiol levels were associated with better processing speed, sustained attention, and working memory [ 23 ]. These age-related hormonal changes provide a natural model that complements menstrual cycle studies in understanding hormone–cognition relationships. While testosterone levels are typically higher in men than women, both sexes experience age-related decline in this hormone [ 24 ]. This decline has been associated with cognitive deterioration in both sexes, particularly affecting the processing speed and memory functions [ 25 ]. Recent research has suggested that testosterone's effects on cognition may be particularly important in women, especially in those carrying genetic risk factors for cognitive decline [ 25 ]. This hormone can be converted to oestradiol in the brain through aromatisation, thereby potentially affecting cognition through both androgen and oestrogen-dependent mechanisms [ 26 ]. Studies have suggested the involvement of testosterone in spatial abilities and working memory, though its effects may differ between men and women [ 26 , 27 ]. Previous research has demonstrated that attention, processing speed, and memory are particularly sensitive to hormonal fluctuations. Higher oestrogen levels have been associated with enhanced working memory performance in animal and human studies [ 12 , 14 ]. Processing speed and sustained attention show a significant correlation with oestradiol levels in post-menopausal women [ 23 ], while progesterone has been shown to modulate networks involved in attention and memory processes [ 17 ]. These cognitive domains are also crucial for daily functioning and academic performance, making them particularly relevant for studying hormone-dependent cognitive changes in young adults. However, the exact nature of these relationships during the menstrual cycle remains unclear, particularly regarding potential differences between men and naturally cycling women. Building on the existing literature, we aimed to investigate three key research questions, each with a specific hypothesis. First, we examined whether women's cognitive functioning changes across the menstrual cycle phases, focusing on attention, processing speed, short-term and working memory, and visuospatial abilities. We hypothesised that performance would be enhanced during the pre-ovulatory phase (high oestradiol) compared to the menstrual phase (low oestradiol and progesterone), particularly in tasks measuring working memory [ 12 , 14 ], processing speed [ 23 ], and attention [ 17 ]. Second, we investigated sex differences in cognitive functioning between young, healthy women and men, accounting for women's menstrual cycle phase. Here, we expected to find sex differences in information processing speed and visuospatial abilities, with these differences being dependent on women's menstrual cycle phase [ 16 , 19 ]. Third, we explored associations between sex hormone levels (oestradiol, progesterone, and testosterone) and cognitive performance in both men and women, comparing the menstrual phase (lowest oestradiol) with the pre-ovulatory phase (highest oestradiol). For this aim, we hypothesised that higher oestradiol levels would be associated with better working memory and attention performance [ 12 , 14 ], progesterone levels would show an association with cognitive performance, in line with previous research, through underlying neural mechanisms (the limbic and somatomotor networks) [ 17 ], testosterone levels would demonstrate positive relationships with spatial abilities and working memory [ 26 , 27 ]. To address these research questions, the study employed two analytical approaches: (1) a longitudinal analysis including only women, comparing their cognitive performance across the menstrual and pre-ovulatory phases, and (2) a cross-sectional analysis comparing men and women at each phase. For methodological consistency in the latter approach, only data from women's first evaluation session was used when compared with men. Methods Participants and study design Recruitment for the study was conducted continuously between December 2022 and November 2023. The participants were recruited through the universities' methods of communication, such as mailing lists and advertisements on social media. The study enrolled women and men aged 18–35 with Polish as a native language. The qualifications for the study were assessed using an online questionnaire and consultation. A diverse group of 115 people applied for the study, of whom 104 were accepted for the study procedure. The exclusion criteria were any neurological or psychiatric illness, taking psychiatric medications, chronic disease (such as diabetes), irregular menstruation in women, endometriosis or polycystic ovary syndrome, current use or use of hormonal contraceptives within the past six months, current or past hormone therapy and current pregnancy, and postpartum or breastfeeding within one year of the study. In addition, women whose oestradiol levels did not change expectantly according to the menstrual cycle were removed from the statistical analysis. In the end, 71 subjects (42 women and 29 men) were included in the statistical analyses (Fig. 1 ). Ethics statement All participants were informed about the procedures, risks, and expected outcomes before starting the assessment procedure and gave their written informed consent for participation. The study was conducted under the Declaration of Helsinki. The study protocol was approved by the Independent Bioethics Commission for Research at the Medical University of Gdansk (NKBBN/398/2021 and NKBBN/398 − 14/2023). Assessment timing To estimate the examination dates, the women completed a questionnaire specifying their menstruation cycle, including regularity, average length based on their last three menstrual cycles, and date of last menstruation. All female participants included in the study had regular menstrual periods (between 25 and 32 days). Based on their calendar, two cycle phases were determined during which the study occurred: the menstrual phase and the pre-ovulatory phase. The menstrual phase was determined between the second and fifth day after the start of menstruation, and the pre-ovulatory phase was determined up to 2 days before ovulation was expected. The expected ovulation date was calculated by subtracting 14 days from the planned next menstruation and then confirmed by the occurrence of this period. The first assessment phase was randomised. Therefore, 26 women had their first measurement taken during the menstrual phase and 20 before ovulation. This avoided the effect of practice and increased the study's reliability. Hormone measurements Before every cognitive examination, blood samples were collected from the participants to establish the hormone levels of progesterone, oestradiol and testosterone. Blood tests were performed in the fasting state and collected in the morning. The samples were analysed by a commercial laboratory using the electrochemiluminescence immunoassay (ECLIA) method and Cobas Pro device. Cognitive tests During the neuropsychological assessment, the participants completed six tests in a fixed order, as described below. The total duration of the cognitive assessment was 45–60 minutes, depending on each individual's performance speed. Short breaks (2–3 minutes) were provided between the tests when requested by the participants to minimise fatigue effects. The Stroop test from the The Delis-Kaplan Executive Function System (D-KEFS) battery[ 28 ]measures rapid processing, attentional selectivity, inhibitory processing and cognitive flexibility. It is a neuropsychological test widely used to assess the ability to inhibit cognitive interference, which occurs when the processing of one stimulus feature prevents the simultaneous processing of a second stimulus feature. This test contained four conditions, each preceded by a short trial, and the time taken to complete each was measured. The first task was to say the colour of the squares (blue, red and green), the second was to read words written in black ink as quickly as possible, the next was to say the colour of the ink in which the words were written (written colour names were incongruent with the ink colour), and the final task was to read a word written in an ink colour inconsistent with the name of the colour if written without a frame, or to say the name of the colour according to the word that was written if the word was in a frame. All the tasks were presented on white sheets of A4 paper lying horizontally. Word reading and colour naming are measures of processing speed, while colour-word inhibition measures executive functions [ 29 ]. In this test, we measured the time taken to complete each task and the interference between each subtest. Digit span forward and backward repetition from the Wechsler Adult Intelligence Scale [ 30 ] is a measure of auditory short-term and working memory. The participants repeated an increasing number of random digits forward and then backwards in the order given by the researcher. Each correctly repeated series was followed by another series plus an additional digit. If the participant failed the first attempt, the subject was given a second chance with a different set of numbers of the same length. If the subject failed the second attempt, the test was terminated. In this test, we measured the number of points the subject scored and the number of items correctly recalled in the longest sequence. The trail making test (TMT) parts A and B [ 31 ] were administered to measure visual processing speed, visual perceptual ability, working memory, task-switching ability and executive control. In part A, the participants had to match the following numbers on an A4 sheet of paper; in part B, the numbers and letters alternated in alphabetical order. Before the actual test, the participants completed a trial task. The time taken to complete the task was measured. An additional indicator of working memory performance was the ratio of the time taken to complete part A to part B. The Corsi block-tapping test [ 32 ] has been used as a measure of spatial short-term and working memory. The test requires the maintenance of a visuospatial pattern and sequence of movements [ 33 ]. Corsi's original apparatus consisted of a series of nine blocks arranged irregularly on a board. The blocks were tapped by the experimenter in random sequences of increasing length. There were two subtests: the forward subtest and the backward subtest. Immediately after each tapped sequence, the participant attempted to reproduce it, progressing until he or she failed to correctly reproduce two sequences of the same length [ 34 ]. As the test progressed, the number of blocks increased. The score was assessed by the maximum number the participant could reproduce correctly in the forward and backward directions. The total score forward (TSF) and total score backward (TSB) indices gave the number of examples performed correctly multiplied by the length of the sequence reproduced correctly. The visual pattern test (VPT) [ 35 ] has been used to measure short-term non-verbal memory and memory for item sequences. There were two parallel sets of patterns, set A and set B, which formed two parallel forms of the test, version A and version B, respectively. The grids ranged in size from the smallest, a 2×2 matrix (with two filled cells), to the largest, a 5×6 matrix (with 15 filled cells), with the complexity increasing progressively by adding two additional cells to the previous grid. Therefore (assuming the simplest pattern can be reproduced), the subject received a score ranging from 2 to 15 [ 36 ]. During the test, the participants were shown patterns of black squares for three seconds and asked to reproduce them from memory. The test was stopped when the participant incorrectly reproduced three boards with the same number of cells. The result of the test was the maximum number of elements that the participant was able to recall and the average number of the last three examples that the participant got right. The visual perceptual skills subtests memory and sequence [ 37 ] were used to measure short-term visual recognition. Due to the young, healthy group of participants, the first six items in each subtest were omitted—the items were too easy to recognise and did not differentiate. The next 10 items were shown for three seconds, and the last six for 5 seconds. After viewing each figure or sequence of elements, the participant was expected to identify and select the correct one from other similar options. A maximum of 18 points could be scored. During the test, the participant did not receive any feedback as to whether or not he or she was speaking correctly. Statistical analysis Statistical analyses were performed using the Statistical Package for Social Sciences (SPSS) version 29 and GraphPad Prism 8. First, Shapiro-Wilk's test was used to check for the normal distribution of the variables. As the cognitive results and hormonal concentrations were not normally distributed, non-parametric tests were performed. For the longitudinal part of the study, women's cognitive performance in the two phases of the menstrual cycle was compared using the Wilcoxon signed-rank test with a calculated effect size. For the cross-sectional part of the study, women's cognitive performance in the two phases of the menstrual cycle was compared to men's using the Kruskal-Wallis test with a post hoc Mann-Whitney U test. Correlations between the changes in hormone levels and cognitive performance were calculated using partial correlation tests adjusted by age. Partial correlations were conducted for all samples together and separately for each group (men, women in the low oestradiol phase and women in the high oestradiol phase). A p -value < 0.05 was considered to be significant. Results Demographic and hormonal data The statistical analysis included 71 young, healthy adults aged 20–36 years, comprising 42 women (mean age 23.64 ± 3.53) and 29 men (mean age 24.1 ± 3.46). Participants had comparable education levels (mean years of education 16.02 ± 2.48) and body mass index (BMI; mean 23.09 ± 3.72), which allowed us to determine the degree of homogeneity of the group. Women participating in the study were characterised by a regular menstrual cycle between 21 and 35 days (Table 1 ). Oestradiol levels were significantly higher in the pre-ovulatory phase than in the menstrual phase of the cycle (T = 5.65; p < 0.001; r = 0.6), and progesterone levels were likewise higher (T = 2.48; p = 0.01; r = 0.3) (Fig. 2 ). Hormonal status was as expected for the healthy women in both phases of the menstrual cycle (Table 2 ). We also investigated hormone levels in men during the study (Table 2 ). Table 1 Presentation of the information on women's menstrual cycles. Women (n = 42) Variable M (SD) Length of the menstrual cycle (days) 30.09 (2.30) Duration of the menstrual phase (days) 5.52 (0.86) Abbreviations : n, number of participants in a given group; M, Mean; SD, Standard Deviation Table 2 Concentrations of hormones in groups of women and men. Group/ phase Testosterone (nmol/ml) M (SD) Progesterone (ng/ml) M (SD) Estradiol (pg/ml) M (SD) Women (n = 42) Menstrual phase 1.32 (0.45) 0.37 (0.2) 30.86 (16.74) Pre-ovulatory phase 1.77 (0.58) 2.06 (3.92) 163.98 (115.85) Men (n = 29) 18.95 (6.07) 0.35 (0.19) 24.79 (8.09) Abbreviations : n, number of participants in a given group; M, Mean; SD, Standard Deviation Changes in cognitive performance between women in the menstrual and pre-ovulatory phases To compare women's cognitive functioning in two phases of the cycle, at low oestradiol and high oestradiol levels, the Wilcoxon signed-rank test was conducted for the dependent groups. The results were statistically and significantly better in the pre-ovulatory phase in the digit span - in the subtests digit span forward (T = 2.06; p = 0.04, r = 0.2), digit span forward max (T = 2.61; p = 0.01, r = 0.3) and digit span backward max (T = 2.32; p = 0.002, r = 0.3) and in the TMT B test time (T = 2.61; p = 0.01, r = 0,3). For all statistically significant results, the effect size ranged from 0.2 to 0.3, which indicates a small and medium effect size (Table 3 ). Table 3 Changes in the cognitive performance between women in the menstrual and pre-ovulatory phases of the cycle. Variables Group N Mean SD Median Mean Rank Sum of Ranks T p r Digit span forward W_M 42 7.33 2.54 7 Negative 133.5 2.06 0.04* 0.22 W_PO 42 8.0 2.06 8 Positive 331.5 Digit span forward max W_M 42 6.24 1.38 6 Negative 93.0 2.61 0.01* 0.28 W_PO 42 6.74 1.27 7 Positive 313.0 Digit span backward W_M 42 7.0 2.35 7 Negative 167.5 1.84 0.07 0.20 W_PO 42 7.48 2.08 7 Positive 360.5 Digit span backward max W_M 42 4.98 1.3 5 Negative 96.0 2.32 0.02* 0.25 W_PO 42 5.43 1.21 5 Positive 282.0 TMT A time(s) W_M 42 22.83 7.41 21.45 Negative 525.5 1.55 0.12 0.17 W_PO 40 21.68 7.29 20.13 Positive 294.50 TMT B time (s) W_M 42 47.47 14.38 47.23 Negative 604.00 2.61 0.01* 0.28 W_PO 40 41.57 9.74 41.63 Positive 216.00 TMT B/A time (s) W_M 42 2.15 0.56 2.11 Negative 489.00 1.06 0.29 0.12 W_PO 40 2.02 0.57 1.89 Positive 331.00 Corsi block span forward W_M 42 6.33 1.07 6 Negative 228.5 0.98 0.33 0.11 W_PO 42 6.17 1.17 6 Positive 149.5 Corsi TSF W_M 42 61.9 21.01 60 Negative 409.0 0.87 0.39 0.09 W_PO 42 58.88 21.76 54 Positive 294.0 Corsi block span backward W_M 42 6.60 1.29 6.00 Negative 153.00 0.27 0.79 0.03 W_PO 42 6.57 0.80 6.00 Positive 172.00 Corsi TSB W_M 42 62.10 17.23 60.00 Negative 204.50 1.81 0.07 0.20 W_PO 42 67.05 17.71 60.00 Positive 425.50 VPT max W_M 41 10.32 1.86 10 Negative 172.0 1.52 0.13 0.17 W_PO 42 10.76 1.86 11 Positive 324.0 VPT mean W_M 41 9.76 1.68 10.30 Negative 202.50 1.85 0.07 0.20 W_PO 42 10.18 1.76 10.00 Positive 427.50 VMT Vis Mem W_M 41 16.22 1.26 16.00 Negative 221.50 0.53 0.60 0.06 W_PO 40 16.38 1.41 17.00 Positive 274.50 VMT Seq Mem W_M 41 14.61 1.52 15.00 Negative 163.50 1.91 0.06 0.21 W_PO 40 15.28 1.63 15.00 Positive 364.50 Stroop A time (s) W_M 42 28.28 4.67 27.92 Negative 517.5 0.83 0.41 0.09 W_PO 42 27.85 4.1 26.45 Positive 385.5 Stroop B time (s) W_M 42 22.89 3.50 22.16 Negative 477.50 0.33 0.75 0.04 W_PO 42 22.48 2.42 22.13 Positive 425.50 Stroop C time (s) W_M 42 44.45 9.89 44.75 Negative 606.00 1.93 0.05 0.21 W_PO 42 42.21 8.03 41.53 Positive 297.00 Stroop D time (s) W_M 42 49.10 9.61 48.65 Negative 540.00 1.11 0.27 0.12 W_PO 42 47.69 9.61 47.74 Positive 363.00 Stroop interference W_M 42 21.56 7.8 21.44 Negative 598.0 1.83 0.07 0.20 W_PO 42 19.72 7.69 19.79 Positive 305.00 Stroop interference a W_M 42 16.17 7.50 13.62 Negative 596.00 1.81 0.07 0.20 W_PO 42 14.35 6.08 13.70 Positive 307.00 Stroop interference b W_M 42 -2.06 8.37 -2.65 Negative 552.50 1.26 0.21 0.14 W_PO 42 -2.65 7.84 -3.04 Positive 350.50 Stroop interference c W_M 42 4.65 7.94 4.65 Negative 429.00 0.28 0.78 0.03 W_PO 42 5.48 8.44 5.21 Positive 474.00 Note : Values marked with an asterisk (*) indicate the level of statistical significance (p < 0.05). Abbreviations : W _ M, women in the menstruation phase; W_PO, women in the pre-ovulatory phase; N – The number of participants in a given group.; SD, Standard Deviation; T, the test statistic for the Wilcoxon signed-rank test; p, the p-value, representing the probability of obtaining the observed results under the null hypothesis; p < 0.05, ndicates statistical significance, meaning there is less than a 5% probability that the observed effect occurred by chance; r – the effect size; DSF, Digit Span Forward; DSB, Digit Span Backward; TMT A, Trail Making Test A; TMT B, Trail Making Test B; TMT B/A, Trail Making Test B/A Ratio; CORSI TSF, Corsi Total Score Forward; CORSI TSB, Corsi Total Score Backward; VPT Max, Visuospatial Test Maximum - the highest level of performance achieved in a visuospatial test; VPT Mean, Visuospatial Test Mean – the average score in a visuospatial test, reflects overall performance; VMT Vis Mem – Visual Memory Task - Visual Memory; VMT Seq Mem – Visual Memory Task - Sequential Memory. Differences in cognitive performance between men and women in two phases of the menstrual cycle To compare the results of the men and women, the data obtained were divided into three independent groups: men (M; n = 29), women in the low oestradiol phase (W1; n = 26), and women in the high oestradiol phase (W2; n = 16). The groups were formed based on the order in which the cognitive tests were performed to ensure the results were as homogeneous as possible. The men were tested only once, but the women were assigned to groups W1 and W2 according to when they underwent the first neuropsychological test (W1: when the first assessment was performed at menstruation; W2: when the first assessment was performed in the pre-ovulatory phase). We used the Kruskal-Wallis test to evaluate the differences in cognitive performance between men and women in two menstrual cycle phases. The test revealed significant differences between the groups in the TMT test, subtest A (p = 0.03), and the Stroop B test—reading words (p = 0.04). No significant changes were observed in the rest of the cognitive tests (Table 4 ). The post hoc analysis indicated differences in both tests only between the groups M and W1 (p = 0.04 for TMT A time and p = 0.04 for Stroop B time) (Fig. 3 ). Table 4 Differences in cognitive performance between men and women in two phases of menstrual cycle. Cognitive test Group Statistics Digit span forward N Mean rank Median IQR KW statistic p W1 26 30.58 7 2 2.96 0.23 W2 16 40.22 8 4 Men 29 38.53 8 4 Digit span forward max W1 26. 30.88 6 2 2.67 0.26 W2 16 39.47 6.5 2 Men 29 38.67 7 2 Digit span backward W1 26 31.27 7 3 2.21 0.33 W2 16 38.25 8 3 Men 29 39.00 8 4 Digit span backward max W1 26 30.96 5 2 2.99 0.22 W2 16 36.38 5.5 2 Men 29 40.31 6 3 TMT A time (s) W1 26 43.08 22.5 11.26 6.77 0.03 * W2 14 30.50 19.31 9.32 Men 29 29.93 19.02 6.71 TMT B time (s) W1 26 37.27 47.75 16.76 0.54 0.76 W2 14 34.07 47.91 15.19 Men 29 33.41 44.55 17.78 TMT B/A time (s) W1 26 30.88 1.89 0.56 1.97 0.37 W2 14 35.43 2.16 1.12 Men 29 38.48 2.06 1.21 Corsi block span forward W1 26 37.12 6 2 0.15 0.93 W2 16 35.97 6 3 Men 29 35.02 6 2 Corsi TSF W1 26 36.58 54 32 0.22 0.90 W2 16 37.44 57 50 Men 29 34.69 54 30 Corsi block span backward W1 26 32.79 6 1 2.27 0.32 W2 16 42.00 7 2 Men 29 35.57 6 1 Corsi TSB W1 26 29.87 57 12 4.37 0.11 W2 16 42.88 66.5 31 Men 29 37.71 60 23 VPT max W1 26 34.62 11 3 1.03 0.60 W2 16 40.53 11 2 Men 29 34.74 10 3 VPT mean W1 26 34.60 10.3 3.07 0.56 0.76 W2 16 39.31 10.15 2.6 Men 29 35.43 9.67 2.16 VMT Vis Mem W1 26 33.87 16 2 0.80 0.67 W2 14 32.25 16 2 Men 29 37.34 16 1 VMT Seq Mem W1 26 33.81 14.5 3 0.40 0.82 W2 14 33.57 14.5 3 Men 29 36.76 15.00 2 Stroop A time (s) W1 26 39.69 28.88 6.8 1.35 0.51 W2 16 33.06 28.18 7.51 Men 29 34.31 28.44 4.86 Stroop B time (s) W1 26 43.37 23.58 3.47 6.60 0.04 * W2 14 36.59 22.4 2.86 Men 29 29.07 21.25 3.75 Stroop C time (s) W1 26 37.96 45.35 13.23 0.38 0.83 W2 16 34.38 46.27 15.17 Men 29 35.14 44.00 9.85 Stroop D time (s) W1 26 36.38 52.70 13.76 0.35 0.84 W2 16 33.38 49.28 13.6 Men 29 37.10 52.09 9.84 Stroop interference W1 26 35.92 22.37 13.95 0.45 0.80 W2 16 33.28 23.09 14.45 Men 29 37.57 23.68 9.99 Stroop interference a W1 26 36.50 14.11 12.8 0.17 0.92 W2 16 34.13 15.54 10.59 Men 29 36.59 15.61 8.71 Stroop interference b W1 26 32.38 -2.82 15.18 2.44 0.30 W2 16 33.59 0.13 12.51 Men 29 40.57 1.34 9.19 Stroop interference c W1 26 32.08 4.30 12.68 1.49 0.47 W2 16 37.81 6.96 9.55 Men 29 38.52 7.28 9.59 Note : Values marked with an asterisk (*) indicate the level of statistical significance (p < 0.05). Abbreviations : W_1, women in the menstruation phase; W_2, women in the pre-ovulatory phase; N – The number of participants in a given group.; IQR, Interquartile Range- a measure of statistical dispersion, representing the range between the first and third quartiles (Q1–Q3); KW Statistic, Kruskal-Wallis Test Statistic; ; p – the p-value, representing the probability of obtaining the observed results under the null hypothesis; p < 0.05, indicates statistical significance, meaning there is less than a 5% probability that the observed effect occurred by chance; DSF, Digit Span Forward; DSB, Digit Span Backward; TMT A, Trail Making Test A; TMT B, Trail Making Test B; TMT B/A, Trail Making Test B/A Ratio; CORSI TSF, Corsi Total Score Forward; CORSI TSB, Corsi Total Score Backward; VPT Max, Visuospatial Test Maximum - the highest level of performance achieved in a visuospatial test; VPT Mean, Visuospatial Test Mean – the average score in a visuospatial test, reflecting overall performance; VMT Vis Mem – Visual Memory Task - Visual Memory; VMT Seq Mem – Visual Memory Task - Sequential Memory. Correlation between hormone concentration and cognitive function In group W1, the higher level of oestradiol was related to better performance in the digit span forward max test (cor. 0.347; p = 0.09) and Stroop interference c (cor. 0.509; p = 0.009). At the same time, an elevated oestradiol level was negatively correlated with the time score in the TMT A test (cor. -0.513; p = 0.005) in the M group. In group W1, the higher level of progesterone was negatively related to the results in the digit span backward test (cor. -0.407; p = 0.043) and Stroop interference c (cor. -0.442; p = 0.027). Meanwhile, in the M group, progesterone levels were positively correlated with the results in the Corsi block span forward (cor. 0.366; p = 0.055) and Corsi TSF (cor. 0,396; p = 0.037) tests. Testosterone levels did not correlate with any cognitive test scores. No correlations were observed in the W2 group or when correlating all groups together. Discussion There are three main findings of the study. The first conclusion was that women's cognitive functioning differs according to their cycle phase. We found better short-term memory capacity, working memory for auditory material, and attention during the high-oestradiol phase compared to the low-oestradiol phase in a group of the same women. Neuroimaging studies have demonstrated that oestradiol enhances hippocampal activation during the pre-ovulatory phase of the menstrual cycle in both verbal and spatial navigation tasks [ 38 , 39 ]. Oestradiol enhances glutamatergic neurotransmission and reduces GABAergic neurotransmission, creating an overall excitatory effect in the brain [ 2 ]. This increased neuronal excitability may explain oestradiol's role in boosting neural activity during cognitive tasks in high-hormone phases of the cycle, such as the pre-ovulatory phase [ 7 ]. The enhancement of glutamatergic transmission and the reduction of GABAergic inhibition under the influence of oestradiol increases neuronal excitability, facilitating rapid and effective data processing necessary for maintaining concentration and manipulating information in working memory [ 2 ], which is what we observed in our study. Furthermore, oestradiol increases the dendritic spine density in the hippocampus [ 40 , 41 ], which may improve memory functions, including working memory. Our research results are also reflected in recent studies using magnetoencephalography (MEG) [ 42 ]. The cited study noted an increase in brain elasticity, particularly in the beta band, during the pre-ovulatory phase. This may explain the better performance in tasks requiring rapid information processing, which is crucial for working and short-term memory. Brain flexibility refers to the ability to adapt quickly to new information and to manage cognitive resources more efficiently [ 43 ], which promotes both working memory and the metastability of attention. During the pre-ovulatory phase, greater activity was also observed in areas such as the left posterior cingulate gyrus and right insula [ 42 ], which are associated with decision-making and social-emotional processing. These areas also relate to cognitive control and attention [ 44 ]. The higher activity of these areas during this cycle phase may explain the better metastability of attention and higher working memory capacity. However, it is crucial to recognise that not all neuroactive effects of sex hormones immediately translate to observable changes in cognitive functioning. This discrepancy is evident in neuroimaging studies where alterations in brain activity do not always correspond to performance improvements in cognitive tasks [ 39 , 45 – 47 ]. This suggests that the relationship between hormonal fluctuations and cognitive function is complex and likely influenced by multiple factors beyond immediate hormonal levels. On the other hand, some studies also indicate that the changes that occur during the cycle may be more subtle and not strictly related to performance per se but to the strategies that are adopted during the execution of the task; for example, during spatial navigation tasks [ 48 ]. Our second key finding showed that sex differences in information processing speed and executive functioning between men and women were observed only when women were in their low-oestradiol (menstrual) phase. This phase-dependent effect was particularly evident in information processing speed (TMT A time and Stroop B time). These differences notably disappeared when women were tested during their pre-ovulatory phase, suggesting that hormonal status plays a crucial role in modulating cognitive sex differences. The literature presents inconsistent results regarding sex differences in attention [ 49 – 52 ]. The reason for this lack of clarity is that many studies investigating the cognitive differences between the sexes do not consider the hormonal changes that occur during the menstrual cycle and their impact on the results obtained. Recent neuroimaging evidence has provided insight into these hormone-dependent effects. Pletzer et al. [ 39 ] have shown that oestradiol increases hippocampal activation during the pre-ovulatory phase, which may facilitate information processing and cognitive performance. This is in line with our observation of reduced sex differences in the pre-ovulatory phase, suggesting that elevated oestradiol levels may have a compensatory function in female cognitive performance. These hormonal influences on cognitive performance are further supported by studies showing oestradiol-dependent increases in hippocampal spine density and enhanced synaptic plasticity [ 40 , 53 ], as well as increased grey matter volume in regions critical for attention and executive function [ 38 , 54 ]. The absence of sex differences during the pre-ovulatory phase may thus reflect enhanced neural efficiency mediated by elevated oestradiol levels. Furthermore, our findings complement previous research on sustained attention, where Pletzer et al. [ 55 ] observed cycle-dependent variations in attention. While their study focused on the luteal phase, showing slower response times in women compared to men during high progesterone levels, our results extend these observations by demonstrating that sex differences are particularly pronounced during the low-oestradiol phase. These findings collectively suggest that both oestradiol and progesterone play distinct roles in modulating cognitive performance, with oestradiol potentially serving a protective or enhancing function that may help eliminate baseline sex differences in cognitive processing speed. What is concerning is the lack of differences in the visuospatial tests in our study between men and women. The literature suggests male predominance in visuospatial tasks. This advantage appears to be domain-specific, primarily documented in mental rotation [ 56 , 57 ] and visual motion processing tasks [ 51 ]. Our study's absence of sex-related differences in visuospatial functions may be attributed to our test selection. Our battery included measures of visuospatial capacity and pattern retrieval (visual pattern test; VPT) and visuospatial sequential working memory (Corsi block-tapping test) rather than tasks involving mental rotation or motion processing. This methodological distinction may explain why our findings diverge from the commonly reported male advantage in specific visuospatial domains. Our third finding has revealed complex, gender-specific associations between sex hormone levels and cognitive functions, but only during the low oestradiol phase in women. In men, oestradiol levels positively correlated with processing speed, while progesterone showed associations with enhanced spatial memory capacity. However, during the low oestradiol phase, the relationship between hormones and cognition appeared more nuanced in women. Oestradiol demonstrated a positive association with short-term memory span but a negative relationship with attention, while progesterone showed an inverse pattern, correlating positively with selective attention but negatively with auditory working memory. These seemingly contradictory findings can be understood through the underlying neurobiological mechanisms. Pletzer et al. [ 39 ] demonstrated that oestradiol and progesterone exert opposing effects on neurotransmitter systems: oestradiol enhances glutamatergic transmission while reducing GABAergic neurotransmission, whereas progesterone produces the opposite effect. This antagonistic relationship between these hormones at the neurotransmitter level may explain our observed differential effects on cognitive function. During the early follicular phase, when both hormones are at their lowest levels, the absence of oestradiol's stimulating effect on glutamatergic transmission may contribute to decreased performance in certain cognitive domains. Conversely, progesterone's enhancement of GABAergic inhibition could potentially impair performance through increased neural inhibition [ 2 ]. Interestingly, our study found no significant correlations between testosterone levels and cognitive performance in men or women. This finding may be explained by interpreting the results obtained in the context of the age and hormonal characteristics of our sample. The absence of testosterone effects in our study contrasts with some previous research showing testosterone's influence on cognitive function, particularly in spatial abilities and working memory [ 26 ]. However, studies showing testosterone's cognitive effects often focus on ageing populations [ 25 , 58 – 60 ]. As shown by Thilers et al. [ 27 ] in their population-based study of 35–90-year-olds, associations between endogenous testosterone levels and cognitive performance become more pronounced with age, particularly in tasks involving processing speed and spatial abilities. This moderation according to age is particularly important because testosterone levels begin to gradually decline, by about 1–2% per year, from the age of 30 [ 61 , 62 ], with the greatest decline observed in the sixth decade of life [ 26 ]. Our results from a young adult sample suggest that these associations may not be evident during the peak reproductive years when hormone levels are relatively stable. This is consistent with other studies investigating the relationship between testosterone levels in young adults and cognitive performance [ 63 ], including spatial abilities [ 64 ] and navigation and verbal fluency tasks [ 48 ]. The relationship between testosterone and cognition is complex and potentially non-linear, as demonstrated by several foundational studies [ 65 , 66 ], showing that both low and high testosterone levels are associated with poorer cognitive ability. In our study, the male participants showed testosterone levels within the normal age-appropriate range (laboratory norm: 8.64–29.0 nmol/l; results of participants: M = 18.95 ± 6.07 nmol/ml); the women's testosterone variations were minimal (fluctuating within 0.45 nmol/ml between cycle phases). In people with normal testosterone levels, as in our study, the effect of this hormone on cognitive function can be challenging to observe. These findings collectively suggest that the absence of testosterone–cognition correlation in our study may be attributed to our sample's age range and the expected physiological hormone levels observed. Future studies might benefit from including participants with a broader range of testosterone levels and age groups to better understand the threshold at which testosterone variations begin to impact cognitive function. What should also be kept in mind, and as recent studies suggest, is that the effect of testosterone on cognitive function may be moderated by many factors, not only age and hormone concentration but also genetic predisposition [ 25 ], and this relationship may also differ between men and women [ 59 ]. The above-mentioned study using MEG showed changes in brain dynamics during the menstrual cycle, especially between the menstrual and pre-ovulatory phases, but these were not related to changes in hormone levels [ 42 ]. According to the authors, which also seems interesting in the case of our study's correlation results, the changes that occur during the cycle are not related solely to hormone levels. It is worth noting that hormone secretion by the hypothalamic-pituitary-gonadal axis is regulated by the hypothalamus, whose work depends on many physiological processes and concentrations of proteins and cytokines in the system [ 67 ]. In order to understand the changes in brain function and further the cognitive changes that occur during the menstrual cycle, it is worth investigating the broader molecular pathways that can help explain the changes that occur. A limitation of our study is that our longitudinal assessment was restricted to two-time points (menstrual and pre-ovulatory phases), which limited our ability to comprehensively assess hormonal influences throughout the menstrual cycle. Perspectives and Significance The present study highlights the complex interactions between sex hormones and cognitive functions, and it demonstrates the significant role of hormonal fluctuations in modulating cognitive differences between sexes. The discovery that differences in information processing speed between men and women disappear during the pre-ovulatory phase suggests a potential compensatory role of estradiol in women's cognitive functioning. These findings carry significant implications for the design of neuropsychological research, underscoring the need to consider the menstrual cycle phase as an important variable, particularly in studies comparing cognitive functions between women and men. Future research should seek to enhance our understanding of the molecular mechanisms underlying these relationships, moving beyond direct measurements of hormone levels to consider broader molecular and physiological pathways influencing brain dynamics and cognitive functions. Conclusion Our findings demonstrate three key aspects of hormone–cognition interactions: (1) enhanced cognitive performance during the pre-ovulatory phase compared to the menstrual phase in women, particularly in working memory and attention; (2) phase-dependent sex differences between men and women in processing speed are present only during women's menstrual phase; and (3) distinct hormone–cognition relationships in men and women vary according to the menstrual cycle phase. These results highlight the necessity of considering the phases of the menstrual cycle in scientific and clinical research where cognitive functions are assessed, especially in studies on sex differences. Declarations Ethics approval and consent to participate The study was conducted under the Declaration of Helsinki. The study protocol was approved by the Independent Bioethics Commission for Research at the Medical University of Gdansk (NKBBN/398/2021 and NKBBN/398-14/2023). Informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding The research was funded by the Medical University of Gdansk. Additional support was provided to MM through the ICREA under the ICREA Academia program. AB-G received a pre-doctoral fellowship [grant number FPU18/04344]. Authors' contributions A.K.S. and P.J.W., conceptualization; A.K.S., K.M.M. and B.N. performed the experiments; A.K.S. and A.B-G. statistical analysis; A.K.S., M.M., P.J.W. and A.B.M. interpreted the results of the experiments; A.K.S., K.M.M., B.N. and A.B.-G. prepared the tabels and graphs; A.K.S. and K.M.M. drafted the manuscript; M.M., P.J.W. and A.B.M edited and revised the manuscript. All authors have read and approved the final manuscript. Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on request. Acknowledgements The authors thank all the participants involved in this study. References Galea LAM, Frick KM, Hampson E, Sohrabji F, Choleris E. Why estrogens matter for behavior and brain health. Neurosci Biobehav Rev. 2017;76:363–79. Barth C, Villringer A, Sacher J. Sex hormones affect neurotransmitters and shape the adult female brain during hormonal transition periods. Front Neurosci. 2015;9. McEwen BS, Milner TA. Understanding the broad influence of sex hormones and sex differences in the brain. J Neurosci Res. 2017;95:24–39. Farage MA, Osborn TW, MacLean AB. Cognitive, sensory, and emotional changes associated with the menstrual cycle: a review. Arch Gynecol Obstet. 2008;278:299–307. Brinton RD, Thompson RF, Foy MR, Baudry M, Wang J, Finch CE, et al. Progesterone receptors: Form and function in brain. Front Neuroendocrinol. 2008;29:313–39. Wharton W, Gleason E, Sandra C, Carlsson OM, Asthana C. Neurobiological Underpinnings of the Estrogen - Mood Relationship. Curr Psychiatry Rev. 2012;8:247–56. Sundström Poromaa I, Gingnell M. Menstrual cycle influence on cognitive function and emotion processingâ€from a reproductive perspective. Front Neurosci. 2014;8. Intlekofer KA, Petersen SL. Distribution of mRNAs encoding classical progestin receptor, progesterone membrane components 1 and 2, serpine mRNA binding protein 1, and progestin and ADIPOQ receptor family members 7 and 8 in rat forebrain. Neuroscience. 2011;172:55–65. Hall G, Phillips TJ. Estrogen and skin: The effects of estrogen, menopause, and hormone replacement therapy on the skin. J Am Acad Dermatol. 2005;53:555–68. Stricker R, Eberhart R, Chevailler M-C, Quinn FA, Bischof P, Stricker R. Establishment of detailed reference values for luteinizing hormone, follicle stimulating hormone, estradiol, and progesterone during different phases of the menstrual cycle on the Abbott ARCHITECT® analyzer. Clinical Chemistry and Laboratory Medicine (CCLM). 2006;44. Ubuka T, Trudeau VL, Parhar I, Editorial. Steroids and the Brain. Front Endocrinol (Lausanne). 2020;11. Luine VN. Sex Steroids and Cognitive Function. J Neuroendocrinol. 2008;20:866–72. Hao J, Rapp PR, Janssen WGM, Lou W, Lasley BL, Hof PR et al. Interactive effects of age and estrogen on cognition and pyramidal neurons in monkey prefrontal cortex. Proceedings of the National Academy of Sciences. 2007;104:11465–70. Keenan PA, Ezzat WH, Ginsburg K, Moore GJ. Prefrontal cortex as the site of estrogen’s effect on cognition. Psychoneuroendocrinology. 2001;26:577–90. Sherwin BB. Estrogen and memory in women: how can we reconcile the findings? Horm Behav. 2005;47:371–5. Šimić N, Santini M. Verbal and spatial functions during different phases of the menstrual cycle. Psychiatr Danub. 2012;24:73–9. Avila-Varela DS, Hidalgo-Lopez E, Dagnino PC, Acero-Pousa I, del Agua E, Deco G et al. Whole-brain dynamics across the menstrual cycle: the role of hormonal fluctuations and age in healthy women. npj Women’s Health. 2024;2. Berent-Spillson A, Briceno E, Pinsky A, Simmen A, Persad CC, Zubieta J-K, et al. Distinct cognitive effects of estrogen and progesterone in menopausal women. Psychoneuroendocrinology. 2015;59:25–36. Zitzmann M. Testosterone and the brain. Aging Male. 2006;9:195–9. Davis SR, Wahlin-Jacobsen S. Testosterone in women—the clinical significance. Lancet Diabetes Endocrinol. 2015;3:980–92. Gurvich C, Le J, Thomas N, Thomas EHX, Kulkarni J. Sex hormones and cognition in aging. 2021. pp. 511–33. Conde DM, Verdade RC, Valadares ALR, Mella LFB, Pedro AO, Costa-Paiva L. Menopause and cognitive impairment: A narrative review of current knowledge. World J Psychiatry. 2021;11:412–28. Xu Q, Ji M, Huang S, Guo W. Association between serum estradiol levels and cognitive function in older women: a cross-sectional analysis. Front Aging Neurosci. 2024;16. Fabbri E, An Y, Gonzalez-Freire M, Zoli M, Maggio M, Studenski SA, et al. Bioavailable Testosterone Linearly Declines Over A Wide Age Spectrum in Men and Women From The Baltimore Longitudinal Study of Aging. J Gerontol Biol Sci Med Sci. 2016;71:1202–9. Dratva MA, Banks SJ, Panizzon MS, Galasko D, Sundermann EE. Low testosterone levels relate to poorer cognitive function in women in an APOE-ε4-dependant manner. Biol Sex Differ. 2024;15. Celec P, Ostatníková D, Hodosy J. On the effects of testosterone on brain behavioral functions. Front Neurosci. Frontiers Research Foundation; 2015. Thilers PP, MacDonald SWS, Herlitz A. The association between endogenous free testosterone and cognitive performance: A population-based study in 35 to 90 year-oldmen and women. Psychoneuroendocrinology. 2006;31:565–76. Erdodi LA, Sagar S, Seke K, Zuccato BG, Schwartz ES, Roth RM. The Stroop test as a measure of performance validity in adults clinically referred for neuropsychological assessment. Psychol Assess. 2018;30:755–66. Scarpina F, Tagini S. The Stroop Color and Word Test. Front Psychol. 2017;8. Young JC, Sawyer RJ, Roper BL, Baughman BC. Expansion and Re-examination of Digit Span Effort Indices on the WAIS-IV. Clin Neuropsychol. 2012;26:147–59. Sánchez-Cubillo I, Periáñez JA, Adrover-Roig D, Rodríguez-Sánchez JM, Ríos-Lago M, Tirapu J, et al. Construct validity of the Trail Making Test: Role of task-switching, working memory, inhibition/interference control, and visuomotor abilities. J Int Neuropsychol Soc. 2009;15:438–50. Arce T, McMullen K. The Corsi Block-Tapping Test: Evaluating methodological practices with an eye towards modern digital frameworks. Computers Hum Behav Rep. 2021;4:100099. Guariglia CC. Spatial working memory in Alzheimer’s disease: A study using the Corsi block-tapping test. Dement Neuropsychol. 2007;1:392–5. Berch DB, Krikorian R, Huha EM. The Corsi Block-Tapping Task: Methodological and Theoretical Considerations. Brain Cogn. 1998;38:317–38. McInerney V. Review of visual patterns test [Internet]. Buros Institute of Mental Measurements; 2007 [cited 2025 Mar 9]. pp. 842–5. Available from: https://researchers.westernsydney.edu.au/en/publications/review-of-visual-patterns-test Della Sala S, Gray C, Baddeley A, Allamano N, Wilson L. Pattern span: a tool for unwelding visuo–spatial memory. Neuropsychologia. 1999;37:1189–99. Colosimo S, Brown T. Examining the Convergent Validity of the Test of Visual Perceptual Skills – Fourth Edition (TVPS-4) in the Australian Context. J Occup Ther Sch Early Interv. 2022;15:90–110. Protopopescu X, Butler T, Pan H, Root J, Altemus M, Polanecsky M, et al. Hippocampal structural changes across the menstrual cycle. Hippocampus. 2008;18:985–8. Pletzer B, Harris TA, Scheuringer A, Hidalgo-Lopez E. The cycling brain: menstrual cycle related fluctuations in hippocampal and fronto-striatal activation and connectivity during cognitive tasks. Neuropsychopharmacology. 2019;44:1867–75. Yankova M, Hart SA, Woolley CS. March. Estrogen increases synaptic connectivity between single presynaptic inputs and multiple postsynaptic CA1 pyramidal cells: A serial electron-microscopic study [Internet]. PNAS 2001. Available from: Khan MM, Dhandapani KM, Zhang Q, Brann DW. Estrogen regulation of spine density and excitatory synapses in rat prefrontal and somatosensory cerebral cortex. Steroids. 2013;78:614–23. Liparoti M, Cipriano L, Troisi Lopez E, Polverino A, Minino R, Sarno L et al. Brain flexibility increases during the peri-ovulatory phase as compared to early follicular phase of the menstrual cycle. Sci Rep. 2024;14. Diamond A. Executive Functions. Annu Rev Psychol. 2013;64:135–68. Kurth F, Zilles K, Fox PT, Laird AR, Eickhoff SB. A link between the systems: functional differentiation and integration within the human insula revealed by meta-analysis. Brain Struct Funct. 2010;214:519–34. Dietrich T, Krings T, Neulen J, Willmes K, Erberich S, Thron A, et al. Effects of Blood Estrogen Level on Cortical Activation Patterns during Cognitive Activation as Measured by Functional MRI. NeuroImage. 2001;13:425–32. Joseph JE, Swearingen JE, Corbly CR, Curry TE, Kelly TH. Influence of estradiol on functional brain organization for working memory. NeuroImage. 2012;59:2923–31. Thimm M, Weis S, Hausmann M, Sturm W. Menstrual cycle effects on selective attention and its underlying cortical networks. Neuroscience. 2014;258:307–17. Scheuringer A, Pletzer B. Sex differences and menstrual cycle dependent changes in cognitive strategies during spatial navigation and verbal fluency. Front Psychol. 2017;8. Feng Q, Zheng Y, Zhang X, Song Y, Luo Y, Li Y, et al. Gender differences in visual reflexive attention shifting: Evidence from an ERP study. Brain Res. 2011;1401:59–65. Evans KL, Hampson E. Sex-dependent effects on tasks assessing reinforcement learning and interference inhibition. Front Psychol. 2015;6. Murray SO, Schallmo MP, Kolodny T, Millin R, Kale A, Thomas P, et al. Sex Differences in Visual Motion Processing. Curr Biol. 2018;28:2794–e27993. Li Y, Wang Y, Jin X, Niu D, Zhang L, Jiang SY, et al. Sex differences in hemispheric lateralization of attentional networks. Psychol Res. 2021;85:2697–709. Woolley CS, McEwen BS. Roles of estradiol and progesterone in regulation of hippocampal dendritic spine density during the estrous cycle in the rat. J Comp Neurol. 1993;336:293–306. Pletzer B, Harris T, Hidalgo-Lopez E. Subcortical structural changes along the menstrual cycle: beyond the hippocampus. Sci Rep. 2018;8:16042. Pletzer B, Harris TA, Ortner T. Sex and menstrual cycle influences on three aspects of attention. Physiol Behav. 2017;179:384–90. Voyer D. Time limits and gender differences on paper-and-pencil tests of mental rotation: a meta-analysis. Psychon Bull Rev. 2011;18:267–77. Voyer D, Voyer SD, Saint-Aubin J. Sex differences in visual-spatial working memory: A meta-analysis. Psychon Bull Rev. 2017;24:307–34. Holland J, Bandelow S, Hogervorst E. Testosterone levels and cognition in elderly men: A review. Maturitas. Elsevier Ireland Ltd; 2011. pp. 322–37. Dong X, Jiang H, Li S, Zhang D. Low Serum Testosterone Concentrations Are Associated With Poor Cognitive Performance in Older Men but Not Women. Front Aging Neurosci. 2021;13. Giannos P, Prokopidis K, Church DD, Kirk B, Morgan PT, Lochlainn MN et al. Associations of Bioavailable Serum Testosterone With Cognitive Function in Older Men: Results From the National Health and Nutrition Examination Survey. Journals of Gerontology - Series A Biological Sciences and Medical Sciences. 2023;78:151–7. Kaufman JM, Vermeulen A. The decline of androgen levels in elderly men and its clinical and therapeutic implications. Endocr Rev. 2005. pp. 833–76. Harman SM, Metter EJ, Tobin JD, Pearson J, Blackman MR. Longitudinal Effects of Aging on Serum Total and Free Testosterone Levels in Healthy Men. J Clin Endocrinol Metab. 2001;86:724–31. Halari R, Hines M, Kumari V, Mehrotra R, Wheeler M, Ng V, et al. Sex Differences and Individual Differences in Cognitive Performance and Their Relationship to Endogenous Gonadal Hormones and Gonadotropins. Behav Neurosci. 2005;119:104–17. Puts DA, Cárdenas RA, Bailey DH, Burriss RP, Jordan CL, Breedlove SM. Salivary testosterone does not predict mental rotation performance in men or women. Horm Behav. 2010;58:282–9. Gouchie C, Kimura D. The relationship between testosterone levels and cognitive ability patterns. Psychoneuroendocrinology. 1991;16:323–34. Moffat S, Hampson E. A curvilinear relationship between testosterone and spatial cognition in humans: Possible influence of hand preference. Psychoneuroendocrinology. 1996;21:323–37. Das N, Kumar TR. Molecular regulation of follicle-stimulating hormone synthesis, secretion and action. J Mol Endocrinol. 2018;60:R131–55. Additional Declarations No competing interests reported. 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Sawicka","email":"data:image/png;base64,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","orcid":"","institution":"Medical University of Gdansk","correspondingAuthor":true,"prefix":"","firstName":"Angelika","middleName":"K.","lastName":"Sawicka","suffix":""},{"id":438097549,"identity":"8e607f42-baaa-4070-9edb-e3c89695b8d3","order_by":1,"name":"Katarzyna M. Michalak","email":"","orcid":"","institution":"Medical University of Gdansk","correspondingAuthor":false,"prefix":"","firstName":"Katarzyna","middleName":"M.","lastName":"Michalak","suffix":""},{"id":438097551,"identity":"87ced124-9e59-49ac-8906-afb8ed4a69b2","order_by":2,"name":"Barbara Naparło","email":"","orcid":"","institution":"Medical University of Gdansk","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Naparło","suffix":""},{"id":438097554,"identity":"e13c5688-631d-42d8-a499-3f95f279527e","order_by":3,"name":"Adrià Bermudo-Gallaguet","email":"","orcid":"","institution":"Universitat de Barcelona (UB)","correspondingAuthor":false,"prefix":"","firstName":"Adrià","middleName":"","lastName":"Bermudo-Gallaguet","suffix":""},{"id":438097556,"identity":"5caad15e-de05-4176-bd5c-dcb95fd89954","order_by":4,"name":"Maria Mataró","email":"","orcid":"","institution":"Universitat de Barcelona (UB)","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Mataró","suffix":""},{"id":438097557,"identity":"9d253503-75fc-4652-8e95-d55638d30d73","order_by":5,"name":"Pawel J. Winklewski","email":"","orcid":"","institution":"Medical University of Gdansk","correspondingAuthor":false,"prefix":"","firstName":"Pawel","middleName":"J.","lastName":"Winklewski","suffix":""},{"id":438097558,"identity":"ea0e404a-548b-43ee-8a0c-7d919bb2feb1","order_by":6,"name":"Anna B. Marcinkowska","email":"","orcid":"","institution":"Medical University of Gdansk","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"B.","lastName":"Marcinkowska","suffix":""}],"badges":[],"createdAt":"2025-03-19 21:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6264630/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6264630/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80863111,"identity":"840b1048-006d-45c9-9a05-b306a4ad5abf","added_by":"auto","created_at":"2025-04-18 02:33:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":217873,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrial flow diagram.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6264630/v1/9e95dfc2cc8e219386eeb4c2.png"},{"id":80863565,"identity":"b5c5726e-5b26-4aae-94d1-07b611995a9b","added_by":"auto","created_at":"2025-04-18 02:41:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":226455,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in progesterone and estradiol levels in women (n=42) during two menstrual cycle phases.\u003c/strong\u003e \u003cem\u003eNote: \u003c/em\u003eData are presented as the mean ± SE and were analysed using the Wilcoxon signed-rank test. Significant differences are denoted by ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 and *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. Progesterone is marked in coral, estradiol in violet.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6264630/v1/2fe43b47257632bfefa72dfa.png"},{"id":80863112,"identity":"990b20ae-fa62-4266-a1f8-5570947ba703","added_by":"auto","created_at":"2025-04-18 02:33:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":234618,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eChanges in performance time in the TMT A and the Stroop test in task B between men and women in two cycle phases. \u003c/strong\u003e\u003cem\u003eNote: \u003c/em\u003eSignificant differences are denoted by *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; \u003cem\u003eAbbreviations: \u003c/em\u003eM, men;\u003cem\u003e \u003c/em\u003eW1, women in the menstruation phase; W2, women in the pre-ovulatory phase.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6264630/v1/eaae80b7ba9d0cb3d673c580.png"},{"id":81041270,"identity":"af3c7684-09d2-4e53-bb40-47270bcc1b1e","added_by":"auto","created_at":"2025-04-21 13:38:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2240918,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6264630/v1/6e45a7dc-4471-423a-8ac1-eb50931148d1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Menstrual cycle phase influences cognitive performance in women and modulates sex differences: A combined longitudinal and cross-sectional study of cognitive function in young adults","fulltext":[{"header":"Plain Language Summary","content":"\u003cp\u003eThis study examined how changes in sex hormone levels during women\u0026apos;s menstrual cycles affect cognitive abilities and how these hormonal fluctuations influence cognitive differences between women and men.\u003c/p\u003e\n\u003cp\u003eThe research involved 71 young adults (42 women and 29 men) who completed various cognitive tasks measuring attention, processing speed, working memory, and visuospatial abilities. Women were tested twice - once during their menstrual phase (when estradiol levels are low) and again during their pre-ovulatory phase (when estradiol levels are high), while men were tested once.\u003c/p\u003e\n\u003cp\u003eThe results showed that women performed better on working memory and attention tasks during their pre-ovulatory phase compared to their menstrual phase. Men performed better in processing speed than women in their menstrual phase. Interestingly, these differences were not apparent when women were tested in the ovulatory phase of their menstrual cycle. The analysis also revealed that in men, higher estradiol and progesterone levels were associated with better cognitive performance, while in women, the relationships between hormones and cognition were more complex and only present during the menstrual phase.\u003c/p\u003e\n\u003cp\u003eThe findings of this study indicate that fluctuations in hormonal levels during a woman\u0026apos;s menstrual cycle may contribute to variations in cognitive abilities observed between men and women. This research emphasises the importance of taking hormonal fluctuations into account when studying cognitive differences between the sexes.\u003c/p\u003e"},{"header":"Highlights","content":"\u003col\u003e\n \u003cli\u003eSex hormone fluctuations during the menstrual cycle modulate cognitive differences between men and women.\u003c/li\u003e\n \u003cli\u003eWomen show improved working memory and attention during the pre-ovulatory phase compared to the early follicular phase.\u003c/li\u003e\n \u003cli\u003eSex differences in processing speed vanish when women are in the pre-ovulatory phase.\u003c/li\u003e\n \u003cli\u003eOestradiol correlates positively with cognition in men but shows mixed effects in women.\u003c/li\u003e\n \u003cli\u003eTestosterone does not correlate with any cognitive functions in young adults.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Introduction","content":"\u003cp\u003eHormones of the hypothalamic-pituitary-gonadal axis, which regulate reproductive functions, have multiple effects on brain development and function [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These effects are mediated through complex mechanisms involving neurotransmitter systems, synaptic plasticity, and neuronal excitability [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe irrefutable evidence for hormonal influences on brain function comes from the widespread distribution of hormone receptors throughout the central nervous system. Oestrogen receptors (ERs) are found throughout the brain\u0026mdash;in the hypothalamus, pituitary, hippocampus, cortex, midbrain and brainstem [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. ERs and progesterone receptors (PRs) are strategically located in brain regions involved in emotional and cognitive regulation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Through these receptors, sex hormones influence cognitive function via multiple mechanisms, including the modulation of neurotransmitter systems, particularly the cholinergic and monoaminergic pathways, the regulation of synaptic plasticity, and effects on neural connectivity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Progesterone specifically acts through the membrane component of the progesterone receptor 1 (PGRMC1) in the cerebellum, cortical regions, hippocampus and hypothalamic nuclei [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe menstrual cycle, characterised by dramatic fluctuations in sex hormone levels, provides a natural model for studying hormonal influence on cognition. The menstrual cycle begins with the early follicular phase, characterised by low progesterone and oestrogen levels. Oestrogen levels rise rapidly in the late follicular phase, showing a nearly eight-fold increase, and peaks one day before ovulation. The luteal phase sees a steady rise in progesterone levels that peak in the mid-luteal phase with an 80-fold increase, accompanied by a second oestrogen peak. Both hormone levels decline during the late luteal phase, reaching baseline shortly before the onset of menstruation [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eResearch shows that steroid hormones, their fluctuation and their receptors play a significant role in many brain functions, such as regulating socio-sexual behaviour, aggression, neurogenesis, learning and memory, stress, cognitive function, and mood and emotion [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It has been proven that oestrogen improves performance in prefrontal cortical-dependent learning in female rats [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and rhesus monkeys [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], as well as in young adults and post-menopausal women [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. According to research, higher oestrogen levels have a protective effect on cognitive functioning [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. More specifically, oestrogen is involved in memory processes and can also affect different types of memory, such as episodic memory, working memory and long-term memory [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, it may affect visuospatial functions, such as visuospatial orientation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Regarding progesterone, an fMRI study proved that it modulates limbic and somatomotor networks, which can improve cognitive function in naturally cycling young women [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Both oestrogen and progesterone treatments have shown potential cognitive benefits in women, with progesterone showing better effects on verbal working memory [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Testosterone, on the other hand, activates a distributed cortical network, the ventral processing stream, during spatial cognition tasks, and the addition of testosterone improves spatial cognition in men [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. According to research, testosterone also protects the brain against oxidative stress, serum deprivation-induced apoptosis and soluble amyloid-β (Aβ) toxicity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurther evidence for the influence of sex hormones on cognitive functioning comes from studies of cognitive ageing in women and men, which is associated with significant changes in the physiological levels of sex hormones [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. During menopause, women experience dramatic fluctuations and eventual decline in the neuroprotective hormones, such as oestrogen and progesterone, which is often accompanied by changes in cognitive performance [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A recent large-scale study of 731 post-menopausal women demonstrated that higher oestradiol levels were associated with better processing speed, sustained attention, and working memory [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These age-related hormonal changes provide a natural model that complements menstrual cycle studies in understanding hormone\u0026ndash;cognition relationships. While testosterone levels are typically higher in men than women, both sexes experience age-related decline in this hormone [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This decline has been associated with cognitive deterioration in both sexes, particularly affecting the processing speed and memory functions [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Recent research has suggested that testosterone's effects on cognition may be particularly important in women, especially in those carrying genetic risk factors for cognitive decline [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This hormone can be converted to oestradiol in the brain through aromatisation, thereby potentially affecting cognition through both androgen and oestrogen-dependent mechanisms [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Studies have suggested the involvement of testosterone in spatial abilities and working memory, though its effects may differ between men and women [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious research has demonstrated that attention, processing speed, and memory are particularly sensitive to hormonal fluctuations. Higher oestrogen levels have been associated with enhanced working memory performance in animal and human studies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Processing speed and sustained attention show a significant correlation with oestradiol levels in post-menopausal women [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], while progesterone has been shown to modulate networks involved in attention and memory processes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These cognitive domains are also crucial for daily functioning and academic performance, making them particularly relevant for studying hormone-dependent cognitive changes in young adults. However, the exact nature of these relationships during the menstrual cycle remains unclear, particularly regarding potential differences between men and naturally cycling women.\u003c/p\u003e \u003cp\u003eBuilding on the existing literature, we aimed to investigate three key research questions, each with a specific hypothesis. First, we examined whether women's cognitive functioning changes across the menstrual cycle phases, focusing on attention, processing speed, short-term and working memory, and visuospatial abilities. We hypothesised that performance would be enhanced during the pre-ovulatory phase (high oestradiol) compared to the menstrual phase (low oestradiol and progesterone), particularly in tasks measuring working memory [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], processing speed [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and attention [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Second, we investigated sex differences in cognitive functioning between young, healthy women and men, accounting for women's menstrual cycle phase. Here, we expected to find sex differences in information processing speed and visuospatial abilities, with these differences being dependent on women's menstrual cycle phase [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Third, we explored associations between sex hormone levels (oestradiol, progesterone, and testosterone) and cognitive performance in both men and women, comparing the menstrual phase (lowest oestradiol) with the pre-ovulatory phase (highest oestradiol). For this aim, we hypothesised that higher oestradiol levels would be associated with better working memory and attention performance [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], progesterone levels would show an association with cognitive performance, in line with previous research, through underlying neural mechanisms (the limbic and somatomotor networks) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], testosterone levels would demonstrate positive relationships with spatial abilities and working memory [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo address these research questions, the study employed two analytical approaches: (1) a longitudinal analysis including only women, comparing their cognitive performance across the menstrual and pre-ovulatory phases, and (2) a cross-sectional analysis comparing men and women at each phase. For methodological consistency in the latter approach, only data from women's first evaluation session was used when compared with men.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and study design\u003c/h2\u003e \u003cp\u003eRecruitment for the study was conducted continuously between December 2022 and November 2023. The participants were recruited through the universities' methods of communication, such as mailing lists and advertisements on social media. The study enrolled women and men aged 18\u0026ndash;35 with Polish as a native language. The qualifications for the study were assessed using an online questionnaire and consultation. A diverse group of 115 people applied for the study, of whom 104 were accepted for the study procedure. The exclusion criteria were any neurological or psychiatric illness, taking psychiatric medications, chronic disease (such as diabetes), irregular menstruation in women, endometriosis or polycystic ovary syndrome, current use or use of hormonal contraceptives within the past six months, current or past hormone therapy and current pregnancy, and postpartum or breastfeeding within one year of the study. In addition, women whose oestradiol levels did not change expectantly according to the menstrual cycle were removed from the statistical analysis. In the end, 71 subjects (42 women and 29 men) were included in the statistical analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthics statement\u003c/h3\u003e\n\u003cp\u003e All participants were informed about the procedures, risks, and expected outcomes before starting the assessment procedure and gave their written informed consent for participation. The study was conducted under the Declaration of Helsinki. The study protocol was approved by the Independent Bioethics Commission for Research at the Medical University of Gdansk (NKBBN/398/2021 and NKBBN/398\u0026thinsp;\u0026minus;\u0026thinsp;14/2023).\u003c/p\u003e\n\u003ch3\u003eAssessment timing\u003c/h3\u003e\n\u003cp\u003eTo estimate the examination dates, the women completed a questionnaire specifying their menstruation cycle, including regularity, average length based on their last three menstrual cycles, and date of last menstruation. All female participants included in the study had regular menstrual periods (between 25 and 32 days). Based on their calendar, two cycle phases were determined during which the study occurred: the menstrual phase and the pre-ovulatory phase. The menstrual phase was determined between the second and fifth day after the start of menstruation, and the pre-ovulatory phase was determined up to 2 days before ovulation was expected. The expected ovulation date was calculated by subtracting 14 days from the planned next menstruation and then confirmed by the occurrence of this period. The first assessment phase was randomised. Therefore, 26 women had their first measurement taken during the menstrual phase and 20 before ovulation. This avoided the effect of practice and increased the study's reliability.\u003c/p\u003e\n\u003ch3\u003eHormone measurements\u003c/h3\u003e\n\u003cp\u003eBefore every cognitive examination, blood samples were collected from the participants to establish the hormone levels of progesterone, oestradiol and testosterone. Blood tests were performed in the fasting state and collected in the morning. The samples were analysed by a commercial laboratory using the electrochemiluminescence immunoassay (ECLIA) method and Cobas Pro device.\u003c/p\u003e\n\u003ch3\u003eCognitive tests\u003c/h3\u003e\n\u003cp\u003eDuring the neuropsychological assessment, the participants completed six tests in a fixed order, as described below. The total duration of the cognitive assessment was 45\u0026ndash;60 minutes, depending on each individual's performance speed. Short breaks (2\u0026ndash;3 minutes) were provided between the tests when requested by the participants to minimise fatigue effects.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Stroop test\u003c/b\u003e from the The Delis-Kaplan Executive Function System (D-KEFS) battery[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]measures rapid processing, attentional selectivity, inhibitory processing and cognitive flexibility. It is a neuropsychological test widely used to assess the ability to inhibit cognitive interference, which occurs when the processing of one stimulus feature prevents the simultaneous processing of a second stimulus feature. This test contained four conditions, each preceded by a short trial, and the time taken to complete each was measured. The first task was to say the colour of the squares (blue, red and green), the second was to read words written in black ink as quickly as possible, the next was to say the colour of the ink in which the words were written (written colour names were incongruent with the ink colour), and the final task was to read a word written in an ink colour inconsistent with the name of the colour if written without a frame, or to say the name of the colour according to the word that was written if the word was in a frame. All the tasks were presented on white sheets of A4 paper lying horizontally. Word reading and colour naming are measures of processing speed, while colour-word inhibition measures executive functions [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In this test, we measured the time taken to complete each task and the interference between each subtest.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDigit span forward and backward repetition\u003c/b\u003e from the Wechsler Adult Intelligence Scale [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] is a measure of auditory short-term and working memory. The participants repeated an increasing number of random digits forward and then backwards in the order given by the researcher. Each correctly repeated series was followed by another series plus an additional digit. If the participant failed the first attempt, the subject was given a second chance with a different set of numbers of the same length. If the subject failed the second attempt, the test was terminated. In this test, we measured the number of points the subject scored and the number of items correctly recalled in the longest sequence.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe trail making test (TMT) parts A and B\u003c/b\u003e [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] were administered to measure visual processing speed, visual perceptual ability, working memory, task-switching ability and executive control. In part A, the participants had to match the following numbers on an A4 sheet of paper; in part B, the numbers and letters alternated in alphabetical order. Before the actual test, the participants completed a trial task. The time taken to complete the task was measured. An additional indicator of working memory performance was the ratio of the time taken to complete part A to part B.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe Corsi block-tapping test\u003c/b\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] has been used as a measure of spatial short-term and working memory. The test requires the maintenance of a visuospatial pattern and sequence of movements [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Corsi's original apparatus consisted of a series of nine blocks arranged irregularly on a board. The blocks were tapped by the experimenter in random sequences of increasing length. There were two subtests: the forward subtest and the backward subtest. Immediately after each tapped sequence, the participant attempted to reproduce it, progressing until he or she failed to correctly reproduce two sequences of the same length [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. As the test progressed, the number of blocks increased. The score was assessed by the maximum number the participant could reproduce correctly in the forward and backward directions. The total score forward (TSF) and total score backward (TSB) indices gave the number of examples performed correctly multiplied by the length of the sequence reproduced correctly.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe visual pattern test (VPT)\u003c/b\u003e [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] has been used to measure short-term non-verbal memory and memory for item sequences. There were two parallel sets of patterns, set A and set B, which formed two parallel forms of the test, version A and version B, respectively. The grids ranged in size from the smallest, a 2\u0026times;2 matrix (with two filled cells), to the largest, a 5\u0026times;6 matrix (with 15 filled cells), with the complexity increasing progressively by adding two additional cells to the previous grid. Therefore (assuming the simplest pattern can be reproduced), the subject received a score ranging from 2 to 15 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. During the test, the participants were shown patterns of black squares for three seconds and asked to reproduce them from memory. The test was stopped when the participant incorrectly reproduced three boards with the same number of cells. The result of the test was the maximum number of elements that the participant was able to recall and the average number of the last three examples that the participant got right.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe visual perceptual skills subtests memory and sequence\u003c/b\u003e [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] were used to measure short-term visual recognition. Due to the young, healthy group of participants, the first six items in each subtest were omitted\u0026mdash;the items were too easy to recognise and did not differentiate. The next 10 items were shown for three seconds, and the last six for 5 seconds. After viewing each figure or sequence of elements, the participant was expected to identify and select the correct one from other similar options. A maximum of 18 points could be scored. During the test, the participant did not receive any feedback as to whether or not he or she was speaking correctly.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using the Statistical Package for Social Sciences (SPSS) version 29 and GraphPad Prism 8. First, Shapiro-Wilk's test was used to check for the normal distribution of the variables. As the cognitive results and hormonal concentrations were not normally distributed, non-parametric tests were performed.\u003c/p\u003e \u003cp\u003eFor the longitudinal part of the study, women's cognitive performance in the two phases of the menstrual cycle was compared using the Wilcoxon signed-rank test with a calculated effect size. For the cross-sectional part of the study, women's cognitive performance in the two phases of the menstrual cycle was compared to men's using the Kruskal-Wallis test with a post hoc Mann-Whitney \u003cem\u003eU\u003c/em\u003e test. Correlations between the changes in hormone levels and cognitive performance were calculated using partial correlation tests adjusted by age. Partial correlations were conducted for all samples together and separately for each group (men, women in the low oestradiol phase and women in the high oestradiol phase). A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to be significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and hormonal data\u003c/h2\u003e \u003cp\u003eThe statistical analysis included 71 young, healthy adults aged 20\u0026ndash;36 years, comprising 42 women (mean age 23.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.53) and 29 men (mean age 24.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.46). Participants had comparable education levels (mean years of education 16.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48) and body mass index (BMI; mean 23.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72), which allowed us to determine the degree of homogeneity of the group.\u003c/p\u003e \u003cp\u003eWomen participating in the study were characterised by a regular menstrual cycle between 21 and 35 days (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Oestradiol levels were significantly higher in the pre-ovulatory phase than in the menstrual phase of the cycle (T\u0026thinsp;=\u0026thinsp;5.65; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; r\u0026thinsp;=\u0026thinsp;0.6), and progesterone levels were likewise higher (T\u0026thinsp;=\u0026thinsp;2.48; p\u0026thinsp;=\u0026thinsp;0.01; r\u0026thinsp;=\u0026thinsp;0.3) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Hormonal status was as expected for the healthy women in both phases of the menstrual cycle (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). We also investigated hormone levels in men during the study (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePresentation of the information on women's menstrual cycles.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWomen (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM (SD)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of the menstrual cycle (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.09 (2.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of the menstrual phase (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.52 (0.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cem\u003eAbbreviations\u003c/em\u003e\u003cstrong\u003e:\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003en, number of participants in a given group; M, Mean; SD, Standard Deviation\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConcentrations of hormones in groups of women and men.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup/ phase\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTestosterone (nmol/ml)\u003c/p\u003e \u003cp\u003eM (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProgesterone (ng/ml)\u003c/p\u003e \u003cp\u003eM (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEstradiol (pg/ml)\u003c/p\u003e \u003cp\u003eM (SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWomen (n\u0026thinsp;=\u0026thinsp;42)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenstrual phase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.32 (0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.37 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.86 (16.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-ovulatory phase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.77 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.06 (3.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e163.98 (115.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMen (n\u0026thinsp;=\u0026thinsp;29)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.95 (6.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.35 (0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.79 (8.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cp\u003e\u003cem\u003eAbbreviations\u003c/em\u003e\u003cstrong\u003e:\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003en, number of participants in a given group; M, Mean; SD, Standard Deviation\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eChanges in cognitive performance between women in the menstrual and pre-ovulatory phases\u003c/h2\u003e \u003cp\u003eTo compare women's cognitive functioning in two phases of the cycle, at low oestradiol and high oestradiol levels, the Wilcoxon signed-rank test was conducted for the dependent groups. The results were statistically and significantly better in the pre-ovulatory phase in the digit span - in the subtests digit span forward (T\u0026thinsp;=\u0026thinsp;2.06; p\u0026thinsp;=\u0026thinsp;0.04, r\u0026thinsp;=\u0026thinsp;0.2), digit span forward max (T\u0026thinsp;=\u0026thinsp;2.61; p\u0026thinsp;=\u0026thinsp;0.01, r\u0026thinsp;=\u0026thinsp;0.3) and digit span backward max (T\u0026thinsp;=\u0026thinsp;2.32; p\u0026thinsp;=\u0026thinsp;0.002, r\u0026thinsp;=\u0026thinsp;0.3) and in the TMT B test time (T\u0026thinsp;=\u0026thinsp;2.61; p\u0026thinsp;=\u0026thinsp;0.01, r\u0026thinsp;=\u0026thinsp;0,3). For all statistically significant results, the effect size ranged from 0.2 to 0.3, which indicates a small and medium effect size (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in the cognitive performance between women in the menstrual and pre-ovulatory phases of the cycle.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean Rank\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSum of Ranks\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigit span forward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e133.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.04*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e331.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigit span forward max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e93.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e313.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigit span backward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e167.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e360.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigit span backward max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e96.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e282.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTMT A time(s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e525.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e294.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTMT B time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e604.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e216.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTMT B/A time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e489.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e331.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCorsi block span forward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e228.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e149.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCorsi TSF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e409.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e294.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCorsi block span backward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e153.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e172.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCorsi TSB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e62.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e204.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e425.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVPT max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e172.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e324.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVPT mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e202.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e427.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVMT Vis Mem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e221.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e274.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVMT Seq Mem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e163.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e364.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop A time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e517.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e385.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop B time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e477.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e425.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop C time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e606.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e297.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop D time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e540.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e47.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e363.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop interference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e598.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e305.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop interference a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e596.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e307.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop interference b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e552.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e350.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroop interference c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e429.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW_PO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e474.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eNote\u003c/em\u003e: Values marked with an asterisk (*) indicate the level of statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eAbbreviations\u003c/em\u003e: W\u003cb\u003e_\u003c/b\u003eM, women in the menstruation phase; W_PO, women in the pre-ovulatory phase; N \u0026ndash; The number of participants in a given group.; SD, Standard Deviation; T, the test statistic for the Wilcoxon signed-rank test; p, the p-value, representing the probability of obtaining the observed results under the null hypothesis; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ndicates statistical significance, meaning there is less than a 5% probability that the observed effect occurred by chance; r \u0026ndash; the effect size; DSF, Digit Span Forward; DSB, Digit Span Backward; TMT A, Trail Making Test A; TMT B, Trail Making Test B; TMT B/A, Trail Making Test B/A Ratio; CORSI TSF, Corsi Total Score Forward; CORSI TSB, Corsi Total Score Backward; VPT Max, Visuospatial Test Maximum - the highest level of performance achieved in a visuospatial test; VPT Mean, Visuospatial Test Mean \u0026ndash; the average score in a visuospatial test, reflects overall performance; VMT Vis Mem \u0026ndash; Visual Memory Task - Visual Memory; VMT Seq Mem \u0026ndash; Visual Memory Task - Sequential Memory.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDifferences in cognitive performance between men and women in two phases of the menstrual cycle\u003c/h2\u003e \u003cp\u003eTo compare the results of the men and women, the data obtained were divided into three independent groups: men (M; n\u0026thinsp;=\u0026thinsp;29), women in the low oestradiol phase (W1; n\u0026thinsp;=\u0026thinsp;26), and women in the high oestradiol phase (W2; n\u0026thinsp;=\u0026thinsp;16). The groups were formed based on the order in which the cognitive tests were performed to ensure the results were as homogeneous as possible. The men were tested only once, but the women were assigned to groups W1 and W2 according to when they underwent the first neuropsychological test (W1: when the first assessment was performed at menstruation; W2: when the first assessment was performed in the pre-ovulatory phase). We used the Kruskal-Wallis test to evaluate the differences in cognitive performance between men and women in two menstrual cycle phases. The test revealed significant differences between the groups in the TMT test, subtest A (p\u0026thinsp;=\u0026thinsp;0.03), and the Stroop B test\u0026mdash;reading words (p\u0026thinsp;=\u0026thinsp;0.04). No significant changes were observed in the rest of the cognitive tests (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The post hoc analysis indicated differences in both tests only between the groups M and W1 (p\u0026thinsp;=\u0026thinsp;0.04 for TMT A time and p\u0026thinsp;=\u0026thinsp;0.04 for Stroop B time) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in cognitive performance between men and women in two phases of menstrual cycle.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span forward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMean rank\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMedian\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eKW statistic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span forward max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span backward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigit span backward max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMT A time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e6.77\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMT B time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMT B/A time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorsi block span forward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorsi TSF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorsi block span backward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorsi TSB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVPT max\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVPT mean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVMT Vis Mem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVMT Seq Mem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop A time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop B time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e6.60\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop C time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop D time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop interference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop interference a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e 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colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroop interference c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eW2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote\u003c/em\u003e: Values marked with an asterisk (*) indicate the level of statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eAbbreviations\u003c/em\u003e: W_1, women in the menstruation phase; W_2, women in the pre-ovulatory phase; N \u0026ndash; The number of participants in a given group.; IQR, Interquartile Range- a measure of statistical dispersion, representing the range between the first and third quartiles (Q1\u0026ndash;Q3); KW Statistic, Kruskal-Wallis Test Statistic; ; p \u0026ndash; the p-value, representing the probability of obtaining the observed results under the null hypothesis; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, indicates statistical significance, meaning there is less than a 5% probability that the observed effect occurred by chance; DSF, Digit Span Forward; DSB, Digit Span Backward; TMT A, Trail Making Test A; TMT B, Trail Making Test B; TMT B/A, Trail Making Test B/A Ratio; CORSI TSF, Corsi Total Score Forward; CORSI TSB, Corsi Total Score Backward; VPT Max, Visuospatial Test Maximum - the highest level of performance achieved in a visuospatial test; VPT Mean, Visuospatial Test Mean \u0026ndash; the average score in a visuospatial test, reflecting overall performance; VMT Vis Mem \u0026ndash; Visual Memory Task - Visual Memory; VMT Seq Mem \u0026ndash; Visual Memory Task - Sequential Memory.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation between hormone concentration and cognitive function\u003c/h2\u003e \u003cp\u003eIn group W1, the higher level of oestradiol was related to better performance in the digit span forward max test (cor. 0.347; p\u0026thinsp;=\u0026thinsp;0.09) and Stroop interference c (cor. 0.509; p\u0026thinsp;=\u0026thinsp;0.009). At the same time, an elevated oestradiol level was negatively correlated with the time score in the TMT A test (cor. -0.513; p\u0026thinsp;=\u0026thinsp;0.005) in the M group.\u003c/p\u003e \u003cp\u003eIn group W1, the higher level of progesterone was negatively related to the results in the digit span backward test (cor. -0.407; p\u0026thinsp;=\u0026thinsp;0.043) and Stroop interference c (cor. -0.442; p\u0026thinsp;=\u0026thinsp;0.027). Meanwhile, in the M group, progesterone levels were positively correlated with the results in the Corsi block span forward (cor. 0.366; p\u0026thinsp;=\u0026thinsp;0.055) and Corsi TSF (cor. 0,396; p\u0026thinsp;=\u0026thinsp;0.037) tests.\u003c/p\u003e \u003cp\u003eTestosterone levels did not correlate with any cognitive test scores. No correlations were observed in the W2 group or when correlating all groups together.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThere are three main findings of the study. The \u003cb\u003efirst conclusion\u003c/b\u003e was that women's cognitive functioning differs according to their cycle phase. We found better short-term memory capacity, working memory for auditory material, and attention during the high-oestradiol phase compared to the low-oestradiol phase in a group of the same women. Neuroimaging studies have demonstrated that oestradiol enhances hippocampal activation during the pre-ovulatory phase of the menstrual cycle in both verbal and spatial navigation tasks [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOestradiol enhances glutamatergic neurotransmission and reduces GABAergic neurotransmission, creating an overall excitatory effect in the brain [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This increased neuronal excitability may explain oestradiol's role in boosting neural activity during cognitive tasks in high-hormone phases of the cycle, such as the pre-ovulatory phase [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The enhancement of glutamatergic transmission and the reduction of GABAergic inhibition under the influence of oestradiol increases neuronal excitability, facilitating rapid and effective data processing necessary for maintaining concentration and manipulating information in working memory [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], which is what we observed in our study. Furthermore, oestradiol increases the dendritic spine density in the hippocampus [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which may improve memory functions, including working memory.\u003c/p\u003e \u003cp\u003eOur research results are also reflected in recent studies using magnetoencephalography (MEG) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The cited study noted an increase in brain elasticity, particularly in the beta band, during the pre-ovulatory phase. This may explain the better performance in tasks requiring rapid information processing, which is crucial for working and short-term memory. Brain flexibility refers to the ability to adapt quickly to new information and to manage cognitive resources more efficiently [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], which promotes both working memory and the metastability of attention. During the pre-ovulatory phase, greater activity was also observed in areas such as the left posterior cingulate gyrus and right insula [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], which are associated with decision-making and social-emotional processing. These areas also relate to cognitive control and attention [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The higher activity of these areas during this cycle phase may explain the better metastability of attention and higher working memory capacity.\u003c/p\u003e \u003cp\u003eHowever, it is crucial to recognise that not all neuroactive effects of sex hormones immediately translate to observable changes in cognitive functioning. This discrepancy is evident in neuroimaging studies where alterations in brain activity do not always correspond to performance improvements in cognitive tasks [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This suggests that the relationship between hormonal fluctuations and cognitive function is complex and likely influenced by multiple factors beyond immediate hormonal levels. On the other hand, some studies also indicate that the changes that occur during the cycle may be more subtle and not strictly related to performance per se but to the strategies that are adopted during the execution of the task; for example, during spatial navigation tasks [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur \u003cb\u003esecond key\u003c/b\u003e finding showed that sex differences in information processing speed and executive functioning between men and women were observed only when women were in their low-oestradiol (menstrual) phase. This phase-dependent effect was particularly evident in information processing speed (TMT A time and Stroop B time). These differences notably disappeared when women were tested during their pre-ovulatory phase, suggesting that hormonal status plays a crucial role in modulating cognitive sex differences.\u003c/p\u003e \u003cp\u003eThe literature presents inconsistent results regarding sex differences in attention [\u003cspan additionalcitationids=\"CR50 CR51\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. The reason for this lack of clarity is that many studies investigating the cognitive differences between the sexes do not consider the hormonal changes that occur during the menstrual cycle and their impact on the results obtained. Recent neuroimaging evidence has provided insight into these hormone-dependent effects. Pletzer et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] have shown that oestradiol increases hippocampal activation during the pre-ovulatory phase, which may facilitate information processing and cognitive performance. This is in line with our observation of reduced sex differences in the pre-ovulatory phase, suggesting that elevated oestradiol levels may have a compensatory function in female cognitive performance.\u003c/p\u003e \u003cp\u003eThese hormonal influences on cognitive performance are further supported by studies showing oestradiol-dependent increases in hippocampal spine density and enhanced synaptic plasticity [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], as well as increased grey matter volume in regions critical for attention and executive function [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The absence of sex differences during the pre-ovulatory phase may thus reflect enhanced neural efficiency mediated by elevated oestradiol levels.\u003c/p\u003e \u003cp\u003eFurthermore, our findings complement previous research on sustained attention, where Pletzer et al. [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] observed cycle-dependent variations in attention. While their study focused on the luteal phase, showing slower response times in women compared to men during high progesterone levels, our results extend these observations by demonstrating that sex differences are particularly pronounced during the low-oestradiol phase. These findings collectively suggest that both oestradiol and progesterone play distinct roles in modulating cognitive performance, with oestradiol potentially serving a protective or enhancing function that may help eliminate baseline sex differences in cognitive processing speed.\u003c/p\u003e \u003cp\u003eWhat is concerning is the lack of differences in the visuospatial tests in our study between men and women. The literature suggests male predominance in visuospatial tasks. This advantage appears to be domain-specific, primarily documented in mental rotation [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and visual motion processing tasks [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Our study's absence of sex-related differences in visuospatial functions may be attributed to our test selection. Our battery included measures of visuospatial capacity and pattern retrieval (visual pattern test; VPT) and visuospatial sequential working memory (Corsi block-tapping test) rather than tasks involving mental rotation or motion processing. This methodological distinction may explain why our findings diverge from the commonly reported male advantage in specific visuospatial domains.\u003c/p\u003e \u003cp\u003eOur \u003cb\u003ethird finding\u003c/b\u003e has revealed complex, gender-specific associations between sex hormone levels and cognitive functions, but only during the low oestradiol phase in women. In men, oestradiol levels positively correlated with processing speed, while progesterone showed associations with enhanced spatial memory capacity. However, during the low oestradiol phase, the relationship between hormones and cognition appeared more nuanced in women. Oestradiol demonstrated a positive association with short-term memory span but a negative relationship with attention, while progesterone showed an inverse pattern, correlating positively with selective attention but negatively with auditory working memory.\u003c/p\u003e \u003cp\u003eThese seemingly contradictory findings can be understood through the underlying neurobiological mechanisms. Pletzer et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] demonstrated that oestradiol and progesterone exert opposing effects on neurotransmitter systems: oestradiol enhances glutamatergic transmission while reducing GABAergic neurotransmission, whereas progesterone produces the opposite effect. This antagonistic relationship between these hormones at the neurotransmitter level may explain our observed differential effects on cognitive function. During the early follicular phase, when both hormones are at their lowest levels, the absence of oestradiol's stimulating effect on glutamatergic transmission may contribute to decreased performance in certain cognitive domains. Conversely, progesterone's enhancement of GABAergic inhibition could potentially impair performance through increased neural inhibition [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, our study found no significant correlations between testosterone levels and cognitive performance in men or women. This finding may be explained by interpreting the results obtained in the context of the age and hormonal characteristics of our sample. The absence of testosterone effects in our study contrasts with some previous research showing testosterone's influence on cognitive function, particularly in spatial abilities and working memory [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, studies showing testosterone's cognitive effects often focus on ageing populations [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. As shown by Thilers et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] in their population-based study of 35\u0026ndash;90-year-olds, associations between endogenous testosterone levels and cognitive performance become more pronounced with age, particularly in tasks involving processing speed and spatial abilities. This moderation according to age is particularly important because testosterone levels begin to gradually decline, by about 1\u0026ndash;2% per year, from the age of 30 [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], with the greatest decline observed in the sixth decade of life [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our results from a young adult sample suggest that these associations may not be evident during the peak reproductive years when hormone levels are relatively stable. This is consistent with other studies investigating the relationship between testosterone levels in young adults and cognitive performance [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], including spatial abilities [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] and navigation and verbal fluency tasks [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The relationship between testosterone and cognition is complex and potentially non-linear, as demonstrated by several foundational studies [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], showing that both low and high testosterone levels are associated with poorer cognitive ability. In our study, the male participants showed testosterone levels within the normal age-appropriate range (laboratory norm: 8.64\u0026ndash;29.0 nmol/l; results of participants: M\u0026thinsp;=\u0026thinsp;18.95\u0026thinsp;\u0026plusmn;\u0026thinsp;6.07 nmol/ml); the women's testosterone variations were minimal (fluctuating within 0.45 nmol/ml between cycle phases). In people with normal testosterone levels, as in our study, the effect of this hormone on cognitive function can be challenging to observe. These findings collectively suggest that the absence of testosterone\u0026ndash;cognition correlation in our study may be attributed to our sample's age range and the expected physiological hormone levels observed. Future studies might benefit from including participants with a broader range of testosterone levels and age groups to better understand the threshold at which testosterone variations begin to impact cognitive function. What should also be kept in mind, and as recent studies suggest, is that the effect of testosterone on cognitive function may be moderated by many factors, not only age and hormone concentration but also genetic predisposition [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and this relationship may also differ between men and women [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe above-mentioned study using MEG showed changes in brain dynamics during the menstrual cycle, especially between the menstrual and pre-ovulatory phases, but these were not related to changes in hormone levels [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. According to the authors, which also seems interesting in the case of our study's correlation results, the changes that occur during the cycle are not related solely to hormone levels. It is worth noting that hormone secretion by the hypothalamic-pituitary-gonadal axis is regulated by the hypothalamus, whose work depends on many physiological processes and concentrations of proteins and cytokines in the system [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. In order to understand the changes in brain function and further the cognitive changes that occur during the menstrual cycle, it is worth investigating the broader molecular pathways that can help explain the changes that occur.\u003c/p\u003e \u003cp\u003eA limitation of our study is that our longitudinal assessment was restricted to two-time points (menstrual and pre-ovulatory phases), which limited our ability to comprehensively assess hormonal influences throughout the menstrual cycle.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePerspectives and Significance\u003c/h2\u003e \u003cp\u003eThe present study highlights the complex interactions between sex hormones and cognitive functions, and it demonstrates the significant role of hormonal fluctuations in modulating cognitive differences between sexes. The discovery that differences in information processing speed between men and women disappear during the pre-ovulatory phase suggests a potential compensatory role of estradiol in women's cognitive functioning. These findings carry significant implications for the design of neuropsychological research, underscoring the need to consider the menstrual cycle phase as an important variable, particularly in studies comparing cognitive functions between women and men. Future research should seek to enhance our understanding of the molecular mechanisms underlying these relationships, moving beyond direct measurements of hormone levels to consider broader molecular and physiological pathways influencing brain dynamics and cognitive functions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings demonstrate three key aspects of hormone\u0026ndash;cognition interactions: (1) enhanced cognitive performance during the pre-ovulatory phase compared to the menstrual phase in women, particularly in working memory and attention; (2) phase-dependent sex differences between men and women in processing speed are present only during women's menstrual phase; and (3) distinct hormone\u0026ndash;cognition relationships in men and women vary according to the menstrual cycle phase. These results highlight the necessity of considering the phases of the menstrual cycle in scientific and clinical research where cognitive functions are assessed, especially in studies on sex differences.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted under the Declaration of Helsinki. The study protocol was approved by the Independent Bioethics Commission for Research at the Medical University of Gdansk (NKBBN/398/2021 and NKBBN/398-14/2023). Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was funded by the Medical University of Gdansk. Additional support was provided to MM through the ICREA under the ICREA Academia program. AB-G received a pre-doctoral fellowship [grant number FPU18/04344].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.K.S. and P.J.W., conceptualization; A.K.S., K.M.M. and B.N. performed the experiments; A.K.S. and A.B-G. statistical analysis; A.K.S., M.M., P.J.W. and A.B.M. interpreted the results of the experiments; A.K.S., K.M.M., B.N. and A.B.-G. prepared the tabels and graphs; A.K.S. and K.M.M. drafted the manuscript; M.M., P.J.W. and A.B.M edited and revised the manuscript. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the participants involved in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGalea LAM, Frick KM, Hampson E, Sohrabji F, Choleris E. Why estrogens matter for behavior and brain health. Neurosci Biobehav Rev. 2017;76:363\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarth C, Villringer A, Sacher J. Sex hormones affect neurotransmitters and shape the adult female brain during hormonal transition periods. Front Neurosci. 2015;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcEwen BS, Milner TA. Understanding the broad influence of sex hormones and sex differences in the brain. J Neurosci Res. 2017;95:24\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarage MA, Osborn TW, MacLean AB. Cognitive, sensory, and emotional changes associated with the menstrual cycle: a review. Arch Gynecol Obstet. 2008;278:299\u0026ndash;307.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrinton RD, Thompson RF, Foy MR, Baudry M, Wang J, Finch CE, et al. Progesterone receptors: Form and function in brain. Front Neuroendocrinol. 2008;29:313\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWharton W, Gleason E, Sandra C, Carlsson OM, Asthana C. Neurobiological Underpinnings of the Estrogen - Mood Relationship. Curr Psychiatry Rev. 2012;8:247\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSundstr\u0026ouml;m Poromaa I, Gingnell M. Menstrual cycle influence on cognitive function and emotion processing\u0026acirc;\u0026euro;from a reproductive perspective. Front Neurosci. 2014;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIntlekofer KA, Petersen SL. Distribution of mRNAs encoding classical progestin receptor, progesterone membrane components 1 and 2, serpine mRNA binding protein 1, and progestin and ADIPOQ receptor family members 7 and 8 in rat forebrain. Neuroscience. 2011;172:55\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHall G, Phillips TJ. Estrogen and skin: The effects of estrogen, menopause, and hormone replacement therapy on the skin. J Am Acad Dermatol. 2005;53:555\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStricker R, Eberhart R, Chevailler M-C, Quinn FA, Bischof P, Stricker R. Establishment of detailed reference values for luteinizing hormone, follicle stimulating hormone, estradiol, and progesterone during different phases of the menstrual cycle on the Abbott ARCHITECT\u0026reg; analyzer. Clinical Chemistry and Laboratory Medicine (CCLM). 2006;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUbuka T, Trudeau VL, Parhar I, Editorial. Steroids and the Brain. Front Endocrinol (Lausanne). 2020;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuine VN. Sex Steroids and Cognitive Function. J Neuroendocrinol. 2008;20:866\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao J, Rapp PR, Janssen WGM, Lou W, Lasley BL, Hof PR et al. Interactive effects of age and estrogen on cognition and pyramidal neurons in monkey prefrontal cortex. Proceedings of the National Academy of Sciences. 2007;104:11465\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeenan PA, Ezzat WH, Ginsburg K, Moore GJ. Prefrontal cortex as the site of estrogen\u0026rsquo;s effect on cognition. Psychoneuroendocrinology. 2001;26:577\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSherwin BB. Estrogen and memory in women: how can we reconcile the findings? Horm Behav. 2005;47:371\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eŠimić N, Santini M. Verbal and spatial functions during different phases of the menstrual cycle. Psychiatr Danub. 2012;24:73\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAvila-Varela DS, Hidalgo-Lopez E, Dagnino PC, Acero-Pousa I, del Agua E, Deco G et al. Whole-brain dynamics across the menstrual cycle: the role of hormonal fluctuations and age in healthy women. npj Women\u0026rsquo;s Health. 2024;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerent-Spillson A, Briceno E, Pinsky A, Simmen A, Persad CC, Zubieta J-K, et al. Distinct cognitive effects of estrogen and progesterone in menopausal women. Psychoneuroendocrinology. 2015;59:25\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZitzmann M. Testosterone and the brain. Aging Male. 2006;9:195\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis SR, Wahlin-Jacobsen S. Testosterone in women\u0026mdash;the clinical significance. Lancet Diabetes Endocrinol. 2015;3:980\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGurvich C, Le J, Thomas N, Thomas EHX, Kulkarni J. Sex hormones and cognition in aging. 2021. pp. 511\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConde DM, Verdade RC, Valadares ALR, Mella LFB, Pedro AO, Costa-Paiva L. Menopause and cognitive impairment: A narrative review of current knowledge. World J Psychiatry. 2021;11:412\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Q, Ji M, Huang S, Guo W. Association between serum estradiol levels and cognitive function in older women: a cross-sectional analysis. Front Aging Neurosci. 2024;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFabbri E, An Y, Gonzalez-Freire M, Zoli M, Maggio M, Studenski SA, et al. Bioavailable Testosterone Linearly Declines Over A Wide Age Spectrum in Men and Women From The Baltimore Longitudinal Study of Aging. J Gerontol Biol Sci Med Sci. 2016;71:1202\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDratva MA, Banks SJ, Panizzon MS, Galasko D, Sundermann EE. Low testosterone levels relate to poorer cognitive function in women in an APOE-ε4-dependant manner. Biol Sex Differ. 2024;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCelec P, Ostatn\u0026iacute;kov\u0026aacute; D, Hodosy J. On the effects of testosterone on brain behavioral functions. Front Neurosci. Frontiers Research Foundation; 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThilers PP, MacDonald SWS, Herlitz A. The association between endogenous free testosterone and cognitive performance: A population-based study in 35 to 90 year-oldmen and women. Psychoneuroendocrinology. 2006;31:565\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErdodi LA, Sagar S, Seke K, Zuccato BG, Schwartz ES, Roth RM. The Stroop test as a measure of performance validity in adults clinically referred for neuropsychological assessment. Psychol Assess. 2018;30:755\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScarpina F, Tagini S. The Stroop Color and Word Test. Front Psychol. 2017;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoung JC, Sawyer RJ, Roper BL, Baughman BC. Expansion and Re-examination of Digit Span Effort Indices on the WAIS-IV. Clin Neuropsychol. 2012;26:147\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026aacute;nchez-Cubillo I, Peri\u0026aacute;\u0026ntilde;ez JA, Adrover-Roig D, Rodr\u0026iacute;guez-S\u0026aacute;nchez JM, R\u0026iacute;os-Lago M, Tirapu J, et al. Construct validity of the Trail Making Test: Role of task-switching, working memory, inhibition/interference control, and visuomotor abilities. J Int Neuropsychol Soc. 2009;15:438\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArce T, McMullen K. The Corsi Block-Tapping Test: Evaluating methodological practices with an eye towards modern digital frameworks. Computers Hum Behav Rep. 2021;4:100099.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuariglia CC. Spatial working memory in Alzheimer\u0026rsquo;s disease: A study using the Corsi block-tapping test. Dement Neuropsychol. 2007;1:392\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerch DB, Krikorian R, Huha EM. The Corsi Block-Tapping Task: Methodological and Theoretical Considerations. Brain Cogn. 1998;38:317\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcInerney V. Review of visual patterns test [Internet]. Buros Institute of Mental Measurements; 2007 [cited 2025 Mar 9]. pp. 842\u0026ndash;5. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://researchers.westernsydney.edu.au/en/publications/review-of-visual-patterns-test\u003c/span\u003e\u003cspan address=\"https://researchers.westernsydney.edu.au/en/publications/review-of-visual-patterns-test\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDella Sala S, Gray C, Baddeley A, Allamano N, Wilson L. Pattern span: a tool for unwelding visuo\u0026ndash;spatial memory. Neuropsychologia. 1999;37:1189\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColosimo S, Brown T. Examining the Convergent Validity of the Test of Visual Perceptual Skills \u0026ndash; Fourth Edition (TVPS-4) in the Australian Context. J Occup Ther Sch Early Interv. 2022;15:90\u0026ndash;110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProtopopescu X, Butler T, Pan H, Root J, Altemus M, Polanecsky M, et al. Hippocampal structural changes across the menstrual cycle. Hippocampus. 2008;18:985\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePletzer B, Harris TA, Scheuringer A, Hidalgo-Lopez E. The cycling brain: menstrual cycle related fluctuations in hippocampal and fronto-striatal activation and connectivity during cognitive tasks. Neuropsychopharmacology. 2019;44:1867\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYankova M, Hart SA, Woolley CS. March. Estrogen increases synaptic connectivity between single presynaptic inputs and multiple postsynaptic CA1 pyramidal cells: A serial electron-microscopic study [Internet]. PNAS 2001. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003c/span\u003e\u003cspan address=\"http://www.pnas.orgcgidoi10.1073pnas.051624598\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan MM, Dhandapani KM, Zhang Q, Brann DW. Estrogen regulation of spine density and excitatory synapses in rat prefrontal and somatosensory cerebral cortex. Steroids. 2013;78:614\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiparoti M, Cipriano L, Troisi Lopez E, Polverino A, Minino R, Sarno L et al. Brain flexibility increases during the peri-ovulatory phase as compared to early follicular phase of the menstrual cycle. Sci Rep. 2024;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiamond A. Executive Functions. Annu Rev Psychol. 2013;64:135\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurth F, Zilles K, Fox PT, Laird AR, Eickhoff SB. A link between the systems: functional differentiation and integration within the human insula revealed by meta-analysis. Brain Struct Funct. 2010;214:519\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDietrich T, Krings T, Neulen J, Willmes K, Erberich S, Thron A, et al. Effects of Blood Estrogen Level on Cortical Activation Patterns during Cognitive Activation as Measured by Functional MRI. NeuroImage. 2001;13:425\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoseph JE, Swearingen JE, Corbly CR, Curry TE, Kelly TH. Influence of estradiol on functional brain organization for working memory. NeuroImage. 2012;59:2923\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThimm M, Weis S, Hausmann M, Sturm W. Menstrual cycle effects on selective attention and its underlying cortical networks. Neuroscience. 2014;258:307\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScheuringer A, Pletzer B. Sex differences and menstrual cycle dependent changes in cognitive strategies during spatial navigation and verbal fluency. Front Psychol. 2017;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng Q, Zheng Y, Zhang X, Song Y, Luo Y, Li Y, et al. Gender differences in visual reflexive attention shifting: Evidence from an ERP study. Brain Res. 2011;1401:59\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEvans KL, Hampson E. Sex-dependent effects on tasks assessing reinforcement learning and interference inhibition. Front Psychol. 2015;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray SO, Schallmo MP, Kolodny T, Millin R, Kale A, Thomas P, et al. Sex Differences in Visual Motion Processing. Curr Biol. 2018;28:2794\u0026ndash;e27993.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y, Wang Y, Jin X, Niu D, Zhang L, Jiang SY, et al. Sex differences in hemispheric lateralization of attentional networks. Psychol Res. 2021;85:2697\u0026ndash;709.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoolley CS, McEwen BS. Roles of estradiol and progesterone in regulation of hippocampal dendritic spine density during the estrous cycle in the rat. J Comp Neurol. 1993;336:293\u0026ndash;306.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePletzer B, Harris T, Hidalgo-Lopez E. Subcortical structural changes along the menstrual cycle: beyond the hippocampus. Sci Rep. 2018;8:16042.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePletzer B, Harris TA, Ortner T. Sex and menstrual cycle influences on three aspects of attention. Physiol Behav. 2017;179:384\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVoyer D. Time limits and gender differences on paper-and-pencil tests of mental rotation: a meta-analysis. Psychon Bull Rev. 2011;18:267\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVoyer D, Voyer SD, Saint-Aubin J. Sex differences in visual-spatial working memory: A meta-analysis. Psychon Bull Rev. 2017;24:307\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolland J, Bandelow S, Hogervorst E. Testosterone levels and cognition in elderly men: A review. Maturitas. Elsevier Ireland Ltd; 2011. pp. 322\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong X, Jiang H, Li S, Zhang D. Low Serum Testosterone Concentrations Are Associated With Poor Cognitive Performance in Older Men but Not Women. Front Aging Neurosci. 2021;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiannos P, Prokopidis K, Church DD, Kirk B, Morgan PT, Lochlainn MN et al. Associations of Bioavailable Serum Testosterone With Cognitive Function in Older Men: Results From the National Health and Nutrition Examination Survey. Journals of Gerontology - Series A Biological Sciences and Medical Sciences. 2023;78:151\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaufman JM, Vermeulen A. The decline of androgen levels in elderly men and its clinical and therapeutic implications. Endocr Rev. 2005. pp. 833\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarman SM, Metter EJ, Tobin JD, Pearson J, Blackman MR. Longitudinal Effects of Aging on Serum Total and Free Testosterone Levels in Healthy Men. J Clin Endocrinol Metab. 2001;86:724\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHalari R, Hines M, Kumari V, Mehrotra R, Wheeler M, Ng V, et al. Sex Differences and Individual Differences in Cognitive Performance and Their Relationship to Endogenous Gonadal Hormones and Gonadotropins. Behav Neurosci. 2005;119:104\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePuts DA, C\u0026aacute;rdenas RA, Bailey DH, Burriss RP, Jordan CL, Breedlove SM. Salivary testosterone does not predict mental rotation performance in men or women. Horm Behav. 2010;58:282\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGouchie C, Kimura D. The relationship between testosterone levels and cognitive ability patterns. Psychoneuroendocrinology. 1991;16:323\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoffat S, Hampson E. A curvilinear relationship between testosterone and spatial cognition in humans: Possible influence of hand preference. Psychoneuroendocrinology. 1996;21:323\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDas N, Kumar TR. Molecular regulation of follicle-stimulating hormone synthesis, secretion and action. J Mol Endocrinol. 2018;60:R131\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"menstrual cycle phase, sex hormones, working memory, attention, sex differences, oestrogen, progesterone","lastPublishedDoi":"10.21203/rs.3.rs-6264630/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6264630/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSex differences in cognitive performance have been widely studied, yet the role of sex hormones and their fluctuations across the menstrual cycle remains unclear. This study investigated cognitive performance differences between men and women, accounting for menstrual cycle phases, and examined associations between sex hormone levels and cognitive function.\u003c/p\u003e \u003cp\u003eSeventy-one healthy young adults (42 women, 29 men) participated in the study. Women were tested twice, once during their menstrual (low oestradiol) phase and once during their pre-ovulatory (high oestradiol) phase. Men underwent a single assessment. Cognitive performance was evaluated using standardised tests that measured attention, processing speed, working memory, and visuospatial abilities. Blood samples were collected to measure oestradiol, progesterone, and testosterone levels.\u003c/p\u003e \u003cp\u003eWomen showed enhanced performance during the pre-ovulatory phase compared to the menstrual phase in working memory capacity (digit span forward: p\u0026thinsp;=\u0026thinsp;0.04; backward max: p\u0026thinsp;=\u0026thinsp;0.02) and attention switching (Trail making test B \u003cb\u003e(\u003c/b\u003eTMT B): p\u0026thinsp;=\u0026thinsp;0.01). Sex differences in processing speed were observed only when men were compared to women in their menstrual phase (TMT A: p\u0026thinsp;=\u0026thinsp;0.03; Stroop B: p\u0026thinsp;=\u0026thinsp;0.04). These differences disappeared during the women's pre-ovulatory phase. While testosterone showed no significant correlations with cognitive measures, oestradiol and progesterone demonstrated distinct relationships. Positive correlations were shown with cognitive performance in men, and there were complex bidirectional relationships in women, but only during the menstrual phase.\u003c/p\u003e \u003cp\u003eThese findings suggest that cognitive differences between the sexes are modulated by hormonal status, with higher oestradiol levels potentially enhancing women's cognitive performance. Further research is needed to elucidate the complex mechanisms underlying these hormone-dependent cognitive changes. This study highlights the importance of considering the phase of the menstrual cycle when investigating sex differences in cognitive function.\u003c/p\u003e","manuscriptTitle":"Menstrual cycle phase influences cognitive performance in women and modulates sex differences: A combined longitudinal and cross-sectional study of cognitive function in young adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-18 02:25:11","doi":"10.21203/rs.3.rs-6264630/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"81db2d7f-dfaf-4875-acbf-2eba9bfd4694","owner":[],"postedDate":"April 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-21T13:38:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-18 02:25:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6264630","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6264630","identity":"rs-6264630","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}