A common view among researchers in learning and conditioning is that the associative strength or value of a stimulus varies inversely with respect to the context of reinforcement in which it occurs. This view provides an intuitively appealing account of a wide range of phenomena known collectively as contrast effects (Flaherty, 1996;Williams, 2002). For example, a stimulus that is correlated with a given rate of reinforcement will maintain a higher response rate when the reinforcement rate correlated with an alternative stimulus is relatively low than when it is relatively high (Reynolds, 1961;Williams, 1983). The elevation in response rate presumably reflects the increased value of the stimulus due to its occurrence in an overall lean context of reinforcement. Yet results of studies in which preference tests have been used to assess value independently of response rate have sometimes obtained paradoxical results (e.g., that positive contrast can be accompanied by decreased stimulus value in preference tests; Williams, 1991Williams, , 1992, and unraveling the complexities of these findings has proven to be a complex undertaking (Williams & McDevitt, 2001; see Williams, 2002, for review).The focus of the present research is a particular type of contrast effect, defined as within-trial contrast by Zentall (2005). The initial demonstration of this effect was a report by Clement, Feltus, Kaiser, and Zentall (2000). In their experiment, pigeons were trained on two simultaneous discriminations that differed in terms of the effort required. One discrimination required relatively little effort-a single response (FR1) to a center key-before the S and S stimuli appeared (red and yellow illumination of the side keys), whereas the other discrimination required relatively high effort (20 center-key responses; FR20) before the S and S stimuli appeared (green and blue illumination of the side keys). After pigeons were performing both discriminations to a high degree of accuracy, Clement et al. arranged a transfer test in which both S or both S stimuli appeared (i.e., S FR1 vs. S FR20 or S FR1 vs. S FR20 ). They found that the pigeons preferred both the S and the S stimuli from the FR20 discrimination, and moreover, that this preference did not depend on the event that initiated the test trial (FR1 or FR20 response requirements on the center key, or no response requirement).To explain these results, Clement et al. (2000) suggested that the value of a stimulus depended on the relative change in the animal's hedonic state. Because the FR20 was a more effortful requirement, the appearance of the S FR20 signaled University of Canterbury, Christchurch, New ZealandThe present research tested the generality of the "work ethic" effect described by Clement, Feltus, Kaiser, and Zentall (2000). In Experiment 1, we trained 10 pigeons on a pair of either simultaneous or successive discriminations. One discrimination followed a high-effort requirement (20 pecks to the center key) and the other followed a low-effort requirement (1 peck). Con...

BackgroundThe aim of this review was to identify studies exploring neuroanatomy teaching tools and their impact in learning, as a basis towards the implementation of a neuroanatomy program in the context of a curricular reform in medical education.MethodsComputer-assisted searches were conducted through March 2017 in the PubMed, Web of Science, Medline, Current Contents Connect, KCI and Scielo Citation Index databases. Four sets of keywords were used, combining “neuroanatomy” with “education”, “teaching”, “learning” and “student*”. Studies were reviewed independently by two readers, and data collected were confirmed by a third reader.ResultsOf the 214 studies identified, 29 studies reported data on the impact of using specific neuroanatomy teaching tools. Most of them (83%) were published in the last 8 years and were conducted in the United States of America (65.52%). Regarding the participants, medical students were the most studied sample (37.93%) and the majority of the studies (65.52%) had less than 100 participants. Approximately half of the studies included in this review used digital teaching tools (e.g., 3D computer neuroanatomy models), whereas the remaining used non-digital learning tools (e.g., 3D physical models).ConclusionsOur work highlight the progressive interest in the study of neuroanatomy teaching tools over the last years, as evidenced from the number of publications and highlight the need to consider new tools, coping with technological development in medical education.

Do people want to be vaccinated against COVID-19? Herd immunity is dependent on individuals’ willingness to be vaccinated since vaccination is not mandatory. Our main goal was to investigate people’s intention to be vaccinated and their intentions to vaccinate their children. Moreover, we were interested in understanding the role of the personal characteristics, psychological factors, and the lockdown context on that decision. Therefore, we conducted an online survey during the lockdown in Portugal (15 January 2021 until 14 March 2021). Participants completed a socio-demographic questionnaire, questions about their intentions of being vaccinated, concerns about the vaccine, a COVID-19 attitudes and beliefs scale, a COVID-19 vaccine attitudes and beliefs scale, and the Domain-Specific Risk-Taking (DOSPERT) Scale. Our results showed that from the 649 participants, 63% of the participants reported being very likely to have the vaccine, while 60% reported being very likely to vaccinate their children. We conducted two linear regression models, explaining 65% of the variance for personal vaccination and 56% of the variance for children vaccination. We found that the COVID-19 vaccine general beliefs and attitudes were the main determinants of vaccination intention. Additionally, our proposed artificial neural network model was able to predict with 85% accuracy vaccination intention. Thus, our results suggest that psychological factors are an essential determinant of vaccination intention. Thus, public policy decision makers may use these insights for predicting vaccine hesitancy and designing effective vaccination communication strategies.

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