How Movie Events Engage Childrens’ Brains to Combine Visual Attention with Domain-Specific Processing Involving Number and Theory of Mind in a Cinematic Arena
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Abstract
Using functional magnetic resonance imaging, we tested the hypothesis that cinematic structure shapes variation in social-cognitive brain activity. Using our film, we completed an exploratory analysis of how activations in the temporal-parietal junction (TPJ), and the intraparietal sulcus (IPS) are shaped by variations in insert shots (e.g., shots showing objects that a character has looked at), and by character entrances and exits. We found that IPS and TPJ consistently responded to insert shots, and the correlation between TPJ and IPS responses significantly predicted the prevalence of belief inferences during the sequence. In addition, TPJ responded significantly to entrances and exits of characters. We also completed a qualitative analysis of moments during a sequence that induced relative peaks in TPJ and IPS responding. These analyses not only demonstrate that consistent brain responses can distinguish among meaningful variations in cinematic events but also that these analyses confirm and refine our understanding of the apparent specializations for visual attention and domain-specific event processing in parietal attention networks.
Contributor Notes
Daniel T. Levin received a BA from Reed College in 1990, and a PhD from Cornell University in 1997. He is currently a Professor of Psychology in the Department of Psychology and Human Development at Vanderbilt University. His research explores the interface between cognition and perception in naturalistic settings ranging from scenes to instructional videos to cinema. This work has been supported by grants from NSF, NIMH, and the Templeton Foundation.
Andrew Mattarella-Micke received his BS in Statistics from Michigan State University in 2005, and his PhD in Psychology from The University of Chicago in 2012. Andrew completed his post-doctoral training at Vanderbilt and Stanford. Currently a Staff Data Scientist at Intuit, his work in industry enables him to study and leverage Machine and Deep Learning to methods for modeling human behavior and language.
Madison Lee is currently a doctoral student in Vanderbilt University's Psychological Sciences program working under the supervision of Dr. Daniel T. Levin. She completed her BS at Indiana University in 2020. She is broadly interested in the many facets of visual cognition and event perception. Her current research explores how visual cognition supports learning in a range of basic and applied contexts.
Lewis Baker received his BS from Loyola University New Orleans and his PhD from Vanderbilt University. He is the Director of Data Science at pymetrics, where he researches methods to reduce bias in machine learning algorithms. His academic work explores models of attention and memory when viewing natural events.
Matthew Bezdek is a senior scientist in the Department of Psychological and Brain Sciences at Washington University in St. Louis. He earned a PhD in Cognitive Psychology at Stony Brook University and completed postdoctoral training at the Georgia Institute of Technology and Washington University in St. Louis. His research examines neuropsychological processes at work when watching films and experiencing everyday life.
Bruce McCandliss received his PhD from the University of Oregon in 1997, and completed a postdoctoral fellowship at Carnegie Mellon University/University of Pittsburg. He held faculty positions at Cornell (Weill Medical College), Vanderbilt, and Stanford, and currently holds the Piggot Family Endowed Chair at Stanford's Graduate School of Education, and a Professorship in Stanford's Department of Psychology (by courtesy), where he leads Stanford's Educational Neuroscience Initiative, which supported this work. Dr. McCandliss's work explores individual differences and educational transformations in cognitive skills such as attention, literacy, and mathematics using developmental cognitive neuroscience techniques.