Understanding socio-affective development in prematurely born preschool children by assessing multimodal biobehavioural socio-communicative attunement among child-mother dyads

Despite improved survival rates, preterm infants remain at increased risk for adverse health outcomes and neurodevelopmental disabilities, in particular socio-emotional difficulties and autism spectrum disorders. Research has described both clinical and subclinical impairments in these domains. The Neonatal Intensive Care Unit (NICU) at UZ Leuven launched an ambitious project (C24/15/036) aimed at investigating the long-term impact of pre-and perinatal stress in preterm infants and their parents. The Resilience project has collected a unique longitudinal database of medical, physiological, psychological, and endocrinological parameters of stress and attachment in 170 dyads, from (before) birth up to three years. Soon, this well-documented cohort will enter primary school, which is a crucial transition period. Using innovative methods, we aim to study the socio-affective and cognitive development of this cohort, with emphasis on the mother-child attachment relationship which lays the foundation of future social functioning. Building on the pioneering biobehavioural synchrony framework, we aim to study development within its social context. Technological advances allow us to study the child-mother dyadic biobehavioural attunement in terms of neural processing, eye-gaze, facial and motor mimicry, stress physiology, and behaviour. We will study the social and emotional functioning of mother and child separately, to uncover correlates of dyadic synchrony. Additionally, we will use innovative Virtual Reality methodology to identify learning processes in these children’s attachment development. Pertaining to cognitive functioning, we will assess general aspects such as executive functioning, but also specific precursors of reading and arithmetic (dis)ability, such as phonological and quantity sensitivity. In addition to established behavioural tasks, frequency-tagging EEG paradigms will allow automatic neural assessment of the quality of phonological and quantity representations. Integration of these new longitudinal data with the early-life data will allow us to model developmental trajectories and to identify risk and protective factors for this vulnerable population.