Episodes, events, and models

Abstract

We describe a novel computational theory of how individuals segment perceptual information into representations of events. The theory is inspired by recent findings in the cognitive science and cognitive neuroscience of event segmentation. In line with recent theories, it holds that online event segmentation is automatic, and that event segmentation yields mental simulations of events. But it posits two novel principles as well: first, discrete episodic markers track perceptual and conceptual changes, and can be retrieved to construct event models. Second, the process of retrieving and reconstructing those episodic markers is constrained and prioritized. We describe a computational implementation of the theory, as well as a robotic extension of the theory that demonstrates the processes of online event segmentation and event model construction. The theory is the first unified computational account of event segmentation and temporal inference. We conclude by demonstrating now neuroimaging data can constrain and inspire the construction of process-level theories of human reasoning.

Transcending time in the brain: How event memories are constructed from experience

“…These findings raise critical ques- One strategy that can promote the linking of information across context shifts is a deliberative, top-down associative encoding, such as creating a meaningful narrative between sequential items (DuBrow & Davachi, 2013, 2014, 2017. In this way, a cognitive context, or goal state, may supersede the influence of other context shifts on event segmentation, a concept known as "event prioritization" (Khemlani et al, 2015). According to this framework, current goals play a leading role in event perception, such that the desire to integrate incoming information into an active event model prevents lower-level perceptual changes, including locations or objects, and even subordinate goals from eliciting segmentation (Magliano, Radvansky, Forsythe, & Copeland, 2014).…”

“…It is thought that the ability to segment continuous sensory inputs is highly adaptive because it unburdens the mind of fleeting and potentially obsolete working memory representations. By helping reorient attention to salient environmental changes, such as a sudden switch in one's actions, intentions, or surroundings (Bailey, Kurby, Sargent, & Zacks, ; Khemlani, Harrison, & Trafton, ; Zwaan & Radvansky, ), these boundaries are theorized to trigger brain mechanisms that update ongoing mental representations of the current state, or context (Richmond & Zacks, ; Zacks & Sargent, ). The updating of these active “event models” may in turn promote the selection of behaviors best suited to the current environment.…”

Event boundaries in memory and cognition

“…Moreover, placing information in separate events can benefit cognitive control [35]. This suggests that building explicit event representations into computer systems may facilitate adaptive control [36]. It should also be noted that expectations and attention can be guided linguistically, such that language may affect how we think about events [32, 33].…”

Constructing Experience: Event Models from Perception to Action

“…Khemlani, Harrison, and Trafton [133] described an architecture to enable a robot to segment and represent events while coordinating its actions with a team of humans. In this architecture, segmentation is organized by goals, locations, and characters and objects; changes in these features correspond to event boundaries.…”