An investigation into the social learning of cooperation in children: individual, social, and cultural comparisons

Humans' unique cooperative and social learning skills have contributed to the evolution of human cumulative culture, fostering the creation and transmission of knowledge and the formation of social institutions. This thesis aimed to understand how children learn from others to collaborate in coordinated interactions with different roles and outcomes, and the influence of cultural, social, and individual factors on children's cooperative behaviour. It is organised in four experimental studies. The first study investigated how different collaborative actions are copied and transmitted between three- and four-year-old children. The second study investigated the adoption of different types of social information by six- and seven-year-old children in a collective social dilemma. The third study investigated the effects of age (four- and five-year-olds versus eight- and nine-year-olds), gender, social class and culture (Brazil versus England) on the cooperation and sharing of resources between children, in a task with unequal outcomes. The fourth study investigated whether the mothers’ social preferences and the children’s individual characteristics affect the cooperation and sharing of resources among children in the same task from the previous study. These studies yielded important findings regarding the diverse effects of contextual factors on the development of children’s collaborative skills. It has been shown that young children can copy peers by observing them in collaborative tasks, and are willing to collaborate with each other across different situations. However, when the tasks present potential conflicts of interest, children will rely on contextual cues to decide whether cooperate or not between themselves. Finally, older children showed better skills towards negotiation and coordination involving sharing of resources, across different sociocultural groups. This thesis contribute to the discussion of the role of contextual variables on the development and learning of cooperative behaviours from an evolutionary perspective

Dependência psicológica de Benzodiazepínicos: Psychological dependence on Benzodiazepines

O crescente aumento do seu uso no começo do século XXI, os ansiolíticos vêm se tornando a “porta de fuga” para nova e também velha geração. Geração essa, que cada vez mais vem sendo consumida por distúrbios de ansiedade, insônia e quadros depressivos de forma exponencial. (Faculdade de Ciências Farmacêuticas de Ribeirão Preto – 2019). Este trabalho, avalia o uso e possível dependência psicológica dos benzodiazepínicos, a partir de um levantamento bibliográfico de forma sistemática de pesquisas dentro da literatura científica acerca do assunto.&nbsp

A epidemiologia da cardiomiopatia de Takotsubo no Brasil e os principais fatores de risco da cardiomiopatia de Takotsubo: The epidemiology of Takotsubo cardiomyopathy in Brazil and the main risk factors for takotsubo cardiomyopathy

A Cardiomiopatia de Takotsubo (CTT) é uma disfunção cardíaca reversível, a qual está relacionada, diretamente, ao estresse físico ou emocional. Objetiva-se através dessa pesquisa evidenciar os principais fatores de risco da CT. Trata-se de uma revisão sistemática realizada no motor de busca Biblioteca Virtual em Saúde (BVS) na base de dados das “Ciências em Saúde em Geral” (Scielo, Medline, Lilacs). Percebeu-se que que a CT apresenta uma ocorrência maior em mulheres na fase de pós-menopausa, onde são atingidas pelo estresse emocional, bem como a inserção de marcapasso também pode desencadear a doença. Entretanto, a etiologia da CT ainda é marcada por controvérsias, mas há concordância acerca do surgimento da CT estar relacionado com a abundância de catecolaminas circulantes

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

The Open Science Revolution

Slides for my talk at the VI Conference in Psychobiology from UFRN (Natal, Brazil, 2019)

My view on children's learning across cultures

Slightly modified version of a submitted position piece for the “Interdisciplinary methods and theory for studying childhood learning across cultures” workshop organised by Sheina Lew-Levy, Helen Davis, Tanya Broesch, and Joe Henrich, and funded by the Wenner-Gren Foundation, held online from October 5-7 2022. I briefly explain my current view of children's learning across cultures