Changes in Situation Models Modulate Processes of Event Perception in Audiovisual Narratives

• Published in: Journal of experimental psychology. Learning, memory, and cognition memory, and cognition, 2014-09, Vol.40 (5), p.1377-1388
• Main Authors: Huff, Markus, Meitz, Tino G. K, Papenmeier, Frank
• Format: Article
• Language: English
• Subjects: Attention - physiology; Audition; Auditory Perception - physiology; Biological and medical sciences; Change; College Students; Comprehension - physiology; Concept Formation; Experiments; Foreign Countries; Fundamental and applied biological sciences. Psychology; Germany; Human; Humans; Memory; Memory - physiology; Narratives; Nonprint Media; Perception; Prediction; Psychology; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Recognition (Psychology); Sensory perception; Television; Vision; Visual Perception - physiology
• ISSN: 0278-7393; 1939-1285
• DOI: 10.1037/a0036780

Humans understand text and film by mentally representing their contents in situation models. These describe situations using dimensions like time, location, protagonist, and action. Changes in 1 or more dimensions (e.g., a new character enters the scene) cause discontinuities in the story line and are often perceived as boundaries between 2 meaningful units. Recent theoretical advances in event perception led to the assumption that situation models are represented in the form of event models in working memory. These event models are updated at event boundaries. Points in time at which event models are updated are important: Compared with situations during an ongoing event, situations at event boundaries are remembered more precisely and predictions about what happens next become less reliable. We hypothesized that these effects depend on the number of changes in the situation model. In 2 experiments, we had participants watch sitcom episodes and measured recognition memory and prediction performance for event boundaries that contained a change in 1, 2, 3, or 4 dimensions. Results showed a linear relationship: the more dimensions changed, the higher recognition performance was. At the same time, participants' predictions became less reliable with an increasing number of dimension changes. These results suggest that updating of event models at event boundaries occurs incrementally.