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Perceivers spontaneously segment ongoing activity into discrete events. This segmentation is important for the moment-by-moment understanding of events, but may also be critical for how events are encoded into episodic memory. In 3 experiments, we used priming to test the possibility that perceptual event boundaries organize memory for everyday activity into episodic units. Viewers watched movies of everyday activities, such as someone washing a car, and then performed a yes-no recognition task using pictures taken from the movies. Some target pictures were preceded by a prime picture taken from 5 s previously in the movie. This produced priming, reducing response times for the target picture. Priming was greater when the prime was part of the same perceptual event as the target than when it was part of a different event, suggesting that event structure organizes episodic memory. This effect persisted when the sequence of activity was scrambled during encoding, which suggests that it reflects, in part, knowledge about event types and not just the specifics of a given episode. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Memory-guided predictions can improve event comprehension by guiding attention and the eyes to the location where an actor is about to perform an action. But when events change, viewers may experience predictive-looking errors and need to update their memories. In two experiments ( Ns = 38 and 98), we examined the consequences of mnemonic predictive-looking errors for comprehending and remembering event changes. University students watched movies of everyday activities with actions that were repeated exactly and actions that were repeated with changed features—for example, an actor reached for a paper towel on one occasion and a dish towel on the next. Memory guidance led to predictive-looking errors that were associated with better memory for subsequently changed event features. These results indicate that retrieving recent event features can guide predictions during unfolding events and that error signals derived from mismatches between mnemonic predictions and actual events contribute to new learning.

The ability to make accurate predictions about what is going to happen in the near future iscritical for comprehension of everyday activity. However, predictive processing may be disrupted in Posttraumatic Stress Disorder (PTSD). Hypervigilance may lead people with PTSD to make inaccurate predictions about the likelihood of future danger. This disruption in predictive processing may occur not only in response to threatening stimuli, but also during processing of neutral stimuli. Therefore, the current study investigated whether people with PTSD experienced difficulty making predictions about near-future neutral activity. Sixty-three participants with PTSD and 63 trauma controls completed two tasks, one testing explicit prediction and the other testing implicit prediction. Participants in the PTSD group displayed worse performance on these tasks, suggesting that PTSD affects predictive processing of neutral, everyday activity. These results suggest that interventions aimed at improving prediction may be important for improvements in functional outcomes in PTSD.

Event segmentation theory posits that we 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.

Humans form sequences of event models—representations of the immediate situation—topredict how activity will unfold. Two challenging questions about event models are “How isactivity segmented into events?” and “How is knowledge about different event types learned andrepresented?” We constructed a computational model combining a recurrent neural network forshort-term dynamics with Bayesian inference over event types for event-to-event transitions.This architecture learns schemas representing knowledge about event types and uses them,along with observed perceptual information, to construct a series of event models, updatingthem when predictions are violated. The architecture learned to predict activity dynamics fromone pass through an 18-hour corpus of naturalistic human activity. When tested on another 3.5hours of activities, it switched schemas at times corresponding with human segmentation andformed human-like event categories—despite being given no feedback about segmentation orcategorization. These results establish that event schemas and updating based on predictionerror can ground learning and can naturally reproduce two important features of humancomprehension.

Gallese, Vittorio, and Michele Guerra. The Empathic Screen: Cinema and Neuroscience. Trans. Frances Anderson. Oxford: Oxford University Press, 2019, 272 pp., $45.00, ISBN: 9780198793533.Rawls, Christina, Diana Neiva, and Steven S. Gouveia, eds. Philosophy and Film: Bridging Divides. New York: Routledge, 2019, 389 pp., $160 (hardback), ISBN: 978-1-138-35169-1.Moss-Wellington, Wyatt. Narrative Humanism: Kindness and Complexity in Fiction and Film. Edinburgh: Edinburgh University Press, 2019, 256 pp., $29.95 (paperback), ISBN: 9781474454322.Perez, Gilberto. The Eloquent Screen. Minneapolis: University of Minnesota Press, 2019, 448 pp., $29.95, ISBN: 978-0-8166-4133-8.

Many studies suggest that information about past experience, or episodic memory, is divided into discrete units called “events.” Yet we can often remember experiences that span multiple events. Events that occur in close succession might simply be linked because of their proximity to one another, but we can also build links between events that occur farther apart in time. Intuitively, some kind of organizing principle should enable temporally distant events to become bridged in memory. We tested the hypothesis that episodic memory exhibits a narrative-level organization, enabling temporally distant events to be better remembered if they form a coherent narrative. Furthermore, we tested whether post-encoding memory consolidation is necessary to integrate temporally distant events. In three experiments, participants learned and subsequently recalled events from fictional stories, in which pairs of temporally distant events involving side characters (“sideplots”) either formed one coherent narrative or two unrelated narratives. Across participants, we varied whether recall was assessed immediately after learning, or after a delay: 24 hours, 12 hours between morning and evening (“wake”), or 12 hours between evening and morning (“sleep”). Participants recalled more information about coherent than unrelated narrative events, in most delay conditions, including immediate recall and wake conditions, suggesting that post-encoding consolidation was not necessary to integrate temporally distant events into a larger narrative. Furthermore, post hoc modeling across experiments suggested that narrative coherence facilitated recall over and above any effects of sentence-level semantic similarity. This reliable memory benefit for coherent narrative events supports theoretical accounts which propose that narratives provide a high-level architecture for episodic memory.

When people experience everyday activities, their comprehension can be shaped by expectations that derive from similar recent experiences, which can affect the encoding of a new experience into memory. When a new experience includes changes—such as a driving route being blocked by construction—this can lead to interference in subsequent memory. One potential mechanism of effective encoding of event changes is the retrieval of related features from previous events. Another such mechanism is the generation of a prediction error when a predicted feature is contradicted. In two experiments, we tested for effects of these two mechanisms on memory for changed features in movies of everyday activities. Participants viewed movies of an actor performing everyday activities across two fictitious days. Some event features changed across the days, and some features violated viewers’ predictions. Retrieval of previous event features while viewing the second movie was associated with better subsequent memory, providing evidence for the retrieval mechanism. Contrary to our hypotheses, there was no support for the error mechanism: Prediction error was not associated with better memory when it was observed correlationally (Experiment 1) or directly manipulated (Experiment 2). These results support a key role for episodic retrieval in the encoding of new events. They also indicate boundary conditions on the role of prediction errors in driving new learning. Both findings have clear implications for theories of event memory.

Humans are able to bind together features of past events and use these memories to guide action in the present. There are many parallels between memory for real-life and fictional events: Both factual and fictional event representations share commonalities in how space and time are represented. Both are affected by emotional responses and by the prior knowledge brought to bear on events as they unfold. However, there are some areas in which memory for real and fictional events may differ. The parallels between memory for fact and for fiction, as well as their exceptions, support a proposal that memory for fiction depends largely on mechanisms that evolved to support retrieval of information about lived events. Narratives are ubiquitous in human culture, and are often highly sought after. One reason for this may be that memories of fictions can help people better navigate the world as it is in fact.

Humans spontaneously organize a continuous experience into discrete events and use the learned structure of these events to generalize and organize memory. We introduce theStructured Event Memory(SEM) model of event cognition, which accounts for human abilities in event segmentation, memory, and generalization. SEM is derived from a probabilistic generative model of event dynamics defined over structured symbolic scenes. By embedding symbolic scene representations in a vector space and parametrizing the scene dynamics in this continuous space, SEM combines the advantages of structured and neural network approaches to high-level cognition. Using probabilistic reasoning over this generative model, SEM can infer event boundaries, learn event schemata, and use event knowledge to reconstruct past experience. We show that SEM can scale up to high-dimensional input spaces, producing human-like event segmentation for naturalistic video data, and accounts for a wide array of memory phenomena.

Accepted for publication in Behavior Research Methods.

Effectively designed data visualizations allow viewers to use their powerful visual systems to understand patterns in data across science, education, health, and public policy. But ineffectively designed visualizations can cause confusion, misunderstanding, or even distrust—especially among viewers with low graphical literacy. We review research-backed guidelines for creating effective and intuitive visualizations oriented toward communicating data to students, coworkers, and the general public. We describe how the visual system can quickly extract broad statistics from a display, whereas poorly designed displays can lead to misperceptions and illusions. Extracting global statistics is fast, but comparing between subsets of values is slow. Effective graphics avoid taxing working memory, guide attention, and respect familiar conventions. Data visualizations can play a critical role in teaching and communication, provided that designers tailor those visualizations to their audience.

Memory-guided predictions can improve event comprehension by guiding attention and the eyes to the location where an actor is about to perform an action. But when events change, viewers may experience predictive looking errors and need to update their memories. In two experiments (Ns = 38 and 111), we examined the consequences of mnemonic predictive looking errors for comprehending and remembering event changes. University students watched movies of everyday activities with actions that repeated exactly and actions that repeated with changed features—for example, an actor reached for a paper towel on one occasion and a dish towel on the next. Memory guidance led to predictive looking errors that were associated with better memory for subsequently changed event features. These results indicate that retrieving recent event features can guide predictions during unfolding events, and that error signals derived from mismatches between mnemonic predictions and actual events contribute to new learning.

Spatial navigation and spatial memory are two important skills for independent living, and are known to be compromised with age. Here, we investigate the neural correlates of successful spatial memory in healthy older adults in order to learn more about the neural underpinnings of maintenance of navigation skill into old age. Healthy older adults watched a video shot by a person navigating a route and were asked to remember objects along the route and then attempted to remember object locations by virtually pointing to the location of hidden objects from several locations along the route. Brain activity during watching and pointing was recorded with functional MRI. Larger activations in temporal and frontal regions during watching, and larger deactivations in superior parietal cortex and intraparietal sulcus during pointing, were associated with smaller location errors. These findings suggest that larger evoked responses during learning of spatial information coupled with larger deactivation of canonical spatial memory regions at retrieval are important for effective spatial memory in late life.

When people experience everyday activities, their comprehension can be shaped by expectations that derive from similar recent experiences, which can affect the encoding of a new experience into memory. When a new experience includes changes-such as a driving route being blocked by construction-this can lead to interference in subsequent memory. One potential mechanism of effective encoding of event changes is the retrieval of related features from previous events. Another such mechanism is the generation of a prediction error when a predicted feature is contradicted. In two experiments, we tested for effects of these two mechanisms on memory for changed features in movies of everyday activities. Participants viewed movies of an actor performing everyday activities across two fictitious days. Some event features changed across the days, and some features violated viewers' predictions. Retrieval of previous event features while viewing the second movie was associated with better subsequent memory, providing evidence for the retrieval mechanism. Contrary to our hypotheses, there was no support for the error mechanism: Prediction error was not associated with better memory when it was observed correlationally (Experiment 1) or directly manipulated (Experiment 2). These results support a key role for episodic retrieval in the encoding of new events. They also indicate boundary conditions on the role of prediction errors in driving new learning. Both findings have clear implications for theories of event memory.