Stawarczyk, Bezdek, and Zacks offer neuroscience evidence for a midline default network core, which appears to coordinate internal, top‐down mentation with externally‐triggered, bottom‐up attention in a push‐pull relationship. The network may enable the flexible pursuance of thoughts tuned into or detached from the current environment.

Much of our behavior is guided by our understanding of events. We perceive events when we observe the world unfolding around us, participate in events when we act on the world, simulate events that we hear or read about, and use our knowledge of events to solve problems. In this book, Gabriel A. Radvansky and Jeffrey M. Zacks provide the first integrated framework for event cognition and attempt to synthesize the available psychological and neuroscience data surrounding it. This synthesis leads (...) to new proposals about several traditional areas in psychology and neuroscience including perception, attention, language understanding, memory, and problem solving.Radvansky and Zacks have written this book with a diverse readership in mind. It is intended for a range of researchers working within cognitive science including psychology, neuroscience, computer science, philosophy, anthropology, and education. Readers curious about events more generally such as those working in literature, film theory, and history will also find it of interest. (shrink)

In order to understand ongoing activity, observers segment it into meaningful temporal parts. Segmentation can be based on bottom‐up processing of distinctive sensory characteristics, such as movement features. Segmentation may also be affected by top‐down effects of knowledge structures, including information about actors' intentions. Three experiments investigated the role of movement features and intentions in perceptual event segmentation, using simple animations. In all conditions, movement features significantly predicted where participants segmented. This relationship was stronger when participants identified larger units than (...) when they identified smaller units, and stronger when the animations were generated randomly than when they were generated by goal‐directed human activity. This pattern suggests that bottom‐up processing played an important role in segmentation of these stimuli, but that this was modulated by top‐down influence of knowledge structures. To describe accurately how observers perceive ongoing activity, one must account for the effects of distinctive sensory characteristics, the effects of knowledge structures, and their interactions. (shrink)

People tend to perceive ongoing continuous activity as series of discrete events. This partitioning of continuous activity may occur, in part, because events correspond to dynamic patterns that have recurred across different contexts. Recurring patterns may lead to reliable sequential dependencies in observers' experiences, which then can be used to guide perception. The current set of simulations investigated whether this statistical structure within events can be used 1) to develop stable internal representations that facilitate perception and 2) to learn when (...) to update such representations in a self-organizing manner. These simulations demonstrate that experience with recurring patterns enables a system to accurately predict upcoming stimuli within an event, to identify boundaries between such events based on transient increases in prediction error, and to use such boundaries to improve prediction about subsequent activities. (shrink)

Filmmakers use continuity editing to engender a sense of situational continuity or discontinuity at editing boundaries. The goal of this study was to assess the impact of continuity editing on how people perceive the structure of events in a narrative film and to identify brain networks that are associated with the processing of different types of continuity editing boundaries. Participants viewed a commercially produced film and segmented it into meaningful events, while brain activity was recorded with functional magnetic resonance imaging (...) (MRI). We identified three degrees of continuity that can occur at editing locations: edits that are continuous in space, time, and action; edits that are discontinuous in space or time but continuous in action; and edits that are discontinuous in action as well as space or time. Discontinuities in action had the biggest impact on behavioral event segmentation, and discontinuities in space and time had minor effects. Edits were associated with large transient increases in early visual areas. Spatial-temporal changes and action changes produced strikingly different patterns of transient change, and they provided evidence that specialized mechanisms in higher order perceptual processing regions are engaged to maintain continuity of action in the face of spatiotemporal discontinuities. These results suggest that commercial film editing is shaped to support the comprehension of meaningful events that bridge breaks in low-level visual continuity, and even breaks in continuity of spatial and temporal location. (shrink)

The Theory of Event Coding deals with brief events but has implications for longer, complex events, particularly goal-directed activities. Two of the theory's central claims are consistent with or assumed by theories of complex events. However, the claim that event codes arise from the rapid activation and integration of features presents challenges for scaling up to larger events.

Event segmentation theory posits that people segment continuous experience into discrete events and that event boundaries occur when there are large transient increases in prediction error. Here, we set out to test this theory in the context of story listening, by using a deep learning language model (GPT‐2) to compute the predicted probability distribution of the next word, at each point in the story. For three stories, we used the probability distributions generated by GPT‐2 to compute the time series of (...) prediction error. We also asked participants to listen to these stories while marking event boundaries. We used regression models to relate the GPT‐2 measures to the human segmentation data. We found that event boundaries are associated with transient increases in Bayesian surprise but not with a simpler measure of prediction error (surprisal) that tracks, for each word in the story, how strongly that word was predicted at the previous time point. These results support the hypothesis that prediction error serves as a control mechanism governing event segmentation and point to important differences between operational definitions of prediction error. (shrink)