33 research outputs found

    Follicle Stimulating Hormone and Anti-MĂĽllerian Hormone per Oocyte in Predicting in vitro Fertilization Pregnancy in High Responders: A Cohort Study

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    Background: Follicle stimulating hormone (FSH) and Anti-MĂĽllerian hormone (AMH) are utilized to differentiate between good and poor response to controlled ovarian hyperstimulation. Their respective roles in defining functional ovarian reserve remain, however, to be elucidated. To better understand those we investigated AMH and FSH per oocyte retrieved (AMHo and FSHo). Methodology/Principal Findings: Three-hundred and ninety-six women, undergoing first in vitro fertilization cycles, were retrospectively evaluated. Women with oocyte yields.75 th percentile for their age group were identified as high responders. In a series of logistic regression analyses, AMHo and FSHo levels were then evaluated as predictive factors for pregnancy potential in high responders. Patients presented with a mean age of 38.065.0 years, mean baseline FSH of 11.868.7 mIU/mL and mean AMH of 1.662.1 ng/mL. Those 88 women, who qualified as high responders, showed mean FSH of 9.766.5 mIU/mL, AMH of 3.163.1 ng/mL and oocyte yields of 15.867.1. Baseline FSH and AMH did not predict pregnancy in high responders. However, a statistically significant association between FSHo and pregnancy was observed in high responders, both after univariate regression (p = 0.02) and when adjusted for age, percentage of usable embryos, and number of embryos transferred (p = 0.03). Rate of useable embryos also significantly affected pregnancy outcome independently of FSHo (p = 0.01). AMHo was also associated with clinical pregnancy chances in high responders (p = 0.03

    Optimal computation regarding risk attitudes in motor decision-making under risk

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    Dissociation of the sources of the risk-seeking bias in motor decision-making based on the subjective-objective relationship in risk-attitudes

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    The process of motor planning involves considering the movement variability and value of the motor outcome. Previous studies have shown that individuals tend to exhibit a consistent risk-seeking bias when performing a temporal aiming task, which involves aiming to respond as closely as possible to a reference time without any delay. However, it is unclear whether this bias is caused by a subjective attempt to take risks or by overestimating motor accuracy. Here, we examined changes in participants’ aiming points after they were instructed regarding subjective risk-attitudes. The results from four different task settings in Experiments 1, 2a, 2b, and 2c, consistently showed a good correspondence between participants’ objective and subjective risk-attitudes. However, in a free-choice situation where participants were instructed to maximize their scores, a robust risk-seeking bias was identified. Computational models suggested that the risk-seeking bias in the free-choice situation was linked to the Maximax strategy. Furthermore, Experiment 3 showed that the participants’ strategy selection in the free-choice situation was similar to the behavior when they were instructed to perform the Maximax strategy. Overall, our findings suggest that in motor planning under risk, humans process near-optimal computation regarding risk attitudes, but their strategic preferences can lead to risk-seeking biases

    The number of chances affects motor decision-making under risk

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    We execute scoring movements by taking the uncertainty of motor outcomes into account for maximization of reward rates. In many sports, the winning point could be determined by proximity to high gain or failure, and in such situations, the preference for high gain is evident. However, findings were constrained when individuals planned a movement to increase the average reward over a large number of trials under the same conditions. Here, we examined the effects of the number of chances, one of the essential contexts for decision-making, on the planning of aiming points. The results showed that when there was only one chance in a set, aiming points were more conservative than when there were more chances (5, 10, or 15). We proposed a risk-sensitive decision model that accounts for the modulation in aiming points, depending on the number of chances. Fitting the model to participants' observed data showed that participants tended to be risk-averse and to underestimate their motor variability in general. The current study provides behavioral and computational evidence that number of chances is one of the variables to account for in motor variability
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