Toward a neuroscientific understanding of play: a dimensional coding framework for analyzing infant–adult play patterns

• Main Authors: Neale, Dave, Clackson, Kaili, Georgieva, Stanimira, Dedetas, Hatice, Scarpate, Melissa, Wass, Sam, Leong, Victoria
• Other Authors: School of Humanities and Social Sciences
• Format: Article
• Language: English
• Published: 2018
• Subjects: Mother–infant Interaction; Play
• Online Access: https://hdl.handle.net/10356/85182; http://hdl.handle.net/10220/45096
• Institution: Nanyang Technological University

Play during early life is a ubiquitous activity, and an individual’s propensity for play is positively related to cognitive development and emotional well-being. Play behavior (which may be solitary or shared with a social partner) is diverse and multi-faceted. A challenge for current research is to converge on a common definition and measurement system for play – whether examined at a behavioral, cognitive or neurological level. Combining these different approaches in a multimodal analysis could yield significant advances in understanding the neurocognitive mechanisms of play, and provide the basis for developing biologically grounded play models. However, there is currently no integrated framework for conducting a multimodal analysis of play that spans brain, cognition and behavior. The proposed coding framework uses grounded and observable behaviors along three dimensions (sensorimotor, cognitive and socio-emotional), to compute inferences about playful behavior in a social context, and related social interactional states. Here, we illustrate the sensitivity and utility of the proposed coding framework using two contrasting dyadic corpora (N = 5) of mother-infant object-oriented interactions during experimental conditions that were either non-conducive (Condition 1) or conducive (Condition 2) to the emergence of playful behavior. We find that the framework accurately identifies the modal form of social interaction as being either non-playful (Condition 1) or playful (Condition 2), and further provides useful insights about differences in the quality of social interaction and temporal synchronicity within the dyad. It is intended that this fine-grained coding of play behavior will be easily assimilated with, and inform, future analysis of neural data that is also collected during adult–infant play. In conclusion, here, we present a novel framework for analyzing the continuous time-evolution of adult–infant play patterns, underpinned by biologically informed state coding along sensorimotor, cognitive and socio-emotional dimensions. We expect that the proposed framework will have wide utility amongst researchers wishing to employ an integrated, multimodal approach to the study of play, and lead toward a greater understanding of the neuroscientific basis of play. It may also yield insights into a new biologically grounded taxonomy of play interactions.