Abstract
To study the dynamic changes in cognition across the human menstrual cycle, twenty, healthy, naturally-cycling women undertook a lateralized spatial figural comparison task on twelve occasions at approximately 3–4 day intervals. Each session was conducted in laboratory conditions with response times, accuracy rates, eye movements, salivary estrogen and progesterone concentrations and Profile of Mood states questionnaire data collected on each occasion. The first two sessions of twelve for the response variables were discarded to avoid early effects of learning thereby providing 10 sessions spread across each participant's complete menstrual cycle. Salivary progesterone data for each participant was utilized to normalize each participant's data to a standard 28 day cycle. Data was analysed categorically by comparing peak progesterone (luteal phase) to low progesterone (follicular phase) to emulate two-session repeated measures typical studies. Neither a significant difference in reaction times or accuracy rates was found. Moreover no significant effect of lateral presentation was observed upon reaction times or accuracy rates although inter and intra individual variance was sizeable. We demonstrate that hormone concentrations alone cannot be used to predict the response times or accuracy rates. In contrast, we constructed a standard linear model using salivary estrogen, salivary progesterone and their respective derivative values and found these inputs to be very accurate for predicting variance observed in the reaction times for all stimuli and accuracy rates for right visual field stimuli but not left visual field stimuli. The identification of sex-hormone derivatives as predictors of cognitive behaviours is of importance. The finding suggests that there is a fundamental difference between the up-surge and decline of hormonal concentrations where previous studies typically assume all points near the peak of a hormonal surge are the same. How contradictory findings in sex-hormone research may have come about are discussed.
Highlights
Changes in female human behaviour as a consequence of hormonal fluctuation over the menstrual cycle are a richly investigated area of science [1, 2] providing fascinating findings about sex hormone mediated behaviour
Accuracy rates stabilized by session 3 yet response times fell more or less across the entire experimental period
We found that the behavioural variables could not be reliably predicted using only the two hormone concentrations, but that a simple linear model including progesterone, estrogen and their derivatives provided an excellent fit for behavioural data at individual and group level for all behavioural measures except the accuracy rates of the left visual field stimuli (LVF-ACC)
Summary
Changes in female human behaviour as a consequence of hormonal fluctuation over the menstrual cycle are a richly investigated area of science [1, 2] providing fascinating findings about sex hormone mediated behaviour. Other findings include hormone related changes in memory [13, 14], verbal abilities [15] and facial recognition [5, 16] to name but a few. Many of these findings show large inconsistencies between studies. This may be due in part, to the incomplete representation that typical two-time-point repeated measures studies give of the female hormone profile which fluctuates rapidly. The following article presents a longitudinal study which exploits an established spatial recognition paradigm [5, 17] to assess how a rich data-set (12 time points) compares to data from the typical two-time-point repeated measures design
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