Our research group is situated within the field of developmental psychology and developmental neuroscience. It is dedicated to the study of a child's cognitive, communicative, linguistic, and affective development in the life span, as well as parent-child relationships. Our general goal is to gain a better understanding of how the mind and the brain develops and how this process is influenced by children’s experiences and their interactions with the environment.
Our research explores various aspects of cognitive and emotional development, such as socio-moral development, which involves how children develop a sense of justice, how they learn to behave in socially acceptable ways, and how their reasoning evolves over time. Our studies investigate both typical and atypical development in children, including the identification of developmental disorders and the underlying neurobiological mechanisms.
Another focus of the group is the study of interactions between child and parent and how these interactions influence brain development. Our research investigates how parental behaviors (e.g., sensitivity and responsiveness) influence neural systems underlying emotional regulation, social cognition, and executive functions. Our research also explores the impact of stressors such as poverty, neglect, and abuse that can influence early brain development and lead to the activation of various "at-risk" behaviors.
The methodologies we use to investigate these phenomena range from behavioral experiments to physiological studies, neuroimaging, and big data analysis. For example, we use neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS), functional Magnetic Resonance Imaging (fMRI), and Electroencephalography (EEG) to explore the neural substrates of cognitive and emotional processes in typically developing children and those with developmental disorders. We also employ hyperscanning techniques (fNIRS) to study child-parent interactions and social cognition, allowing us to investigate real-time brain activity in natural settings, providing a more ecologically valid understanding of neural processes underlying social behavior and cognition. We are exploring the potential of these techniques to enhance our understanding of developmental disorders such as autism spectrum disorder and identify potential biomarkers for early diagnosis and intervention. We also use big data analysis approaches to identify patterns and associations in large datasets, enabling us to develop new insights into the complex interplay between genetics, environment, and behavior.