Collaborative Research: Communication, Perturbation, and Early Development

University Of Denver, Denver CO

Investigators

Abstract

Young infants typically form lasting, emotional attachments to their caregivers. The strength and type of these attachments are related to emotional well-being and cognitive development. This project will explore how face-to-face interactions between infants and adults contribute to this important aspect of child development. During early interactions, infants and parents form expectations about one another. Will a smile be answered with a bigger smile, for example, or with no smile at all? If the parent is asked to stop interacting and just look at her infant, will the infant smile or vocalize in an attempt to repair the interaction? Do these early patterns of interaction predict the infant's later security of attachment--their ability to be comforted after a brief separation from the parent? To answer these questions, seventy-five infants and their mothers will participate in a standard "Face-To-Face/Still-Face" procedure at four months. Their security of attachment will then be assessed at 12 months. It is difficult to measure early interactive behavior-and human behavior more generally-objectively and efficiently. To address this challenge, the project's interdisciplinary team of psychological and computer scientists will implement automated, quantitative measurements of behavior in the Face-To-Face/Still-Face procedure. Automated facial image analysis and pattern recognition approaches will be used to produce objective, continuous measurements of infant and mother facial expression, head motion, gaze direction, and vocalizations. Precise measurement of this multimodal suite of infant and mother behaviors will be used to tackle a fundamental scientific problem: Modeling the structure of early interaction and its relation to later development. This is a promising approach to understanding threats to typical development and learning associated with risk factors such as maternal depression and disorders such as autism. To maximize the project's impact, the team will make a database of audiovisual recordings, automated measurements, and pattern recognition and modeling software available to other scientists.