09:00 - 10:30
Parallel sessions 1
09:00 - 10:30
Room: HSZ - N3
Chair/s:
Karin Maria Bausenhart, Markus Huff, Jeffrey M Zacks
Human cognition is shaped by the way humans perceive and segment continuous, dynamic, complex, and multimodal perceptual input into meaningful, discrete episodes. Such events and their boundaries (transitions that separate meaningful units of experience from each other) play a crucial role in structuring memory, guiding attention, and enhancing understanding. Perceiving an event boundary – for example, triggered by changes in time, location, protagonist, goal, or social interaction – evokes updates in working memory and thereby prompts the formation of new or adaptation of existing event models. This segmentation process may thus enhance comprehension and recall by creating clear divisions between contexts, allowing individuals to better encode, retrieve, and reason about sensory experience. Events and their boundaries also influence predictive processes: within a given event, reliable forecasts can be made based on contextual continuity and abstract event schemata, but predictions become less reliable when crossing event boundaries. Recent models suggest that increased uncertainty and error in predictive processing in itself may drive the updating of event models in working memory, thus reinforcing the link between predictive processing and event segmentation. Overall, events and their boundaries serve as fundamental units of organization in cognitive processing, enabling humans to make sense of and coherently act upon a dynamic and often unpredictable world. In this symposium, we will present novel empirical and theoretical developments from psychology and cognitive science that explore the functions and mechanisms of event cognition. We will focus in particular on how boundaries affect the perception and segmentation (vs. integration) of dynamic input, how event models are formed within and across modalities, and how dynamic input, schema-based prediction, and contextual factors interplay to shape event representations and higher-level cognitive processes such as categorization, memory, and problem-solving.
Submission 579
Modeling Human Event Comprehension at Human Scale
SymposiumTalk-05
Presented by: Jeffrey M. Zacks
Jeffrey M. Zacks 1, Tan T. Nguyen 1, 2, Joset A. Etzel 1, Samuel L. Gershman 3, Matthew A. Bezdek 1, Aaron F. Bobick 1, Todd S. Braver 1
1 Washington University in Saint Louis, United States
2 Google, Inc., United States
3 Harvard University, United States
A grand challenge for cognitive science and neuroscience is to explain how the human brain forms and updates stable representations of events in the stream of behavior. One family of theories propose that event updating is triggered by transient failures in prediction quality. Prediction quality has two aspects, prediction error, or surprisal; and uncertainty, or entropy. One major barrier to understanding their roles has been constructing experimental paradigms and computational frameworks that can be directly compared to human behavior and brain activity. A second barrier is posed by the fact that in naturalistic activity, these two potential signals are correlated. This means it takes a relatively large sample of activities to tease them apart. In this talk, I will describe a large corpus of highly instrumented action recordings and accompanying behavioral and functional MRI measurements. Using these together with a computational model, we have tested the roles of prediction error and prediction uncertainty in event updating. The data support important roles for both signals in human event comprehension.