Inspired by, and in close relation with, the contributions of this special issue, Kuperberg elegantly links event comprehension, production, and learning. She proposes an overarching hierarchical generative framework of processing events enabling us to make sense of the world around us and to interact with it in a competent manner.

At conceptual and linguistic levels of cognition, events are said to be represented in terms of abstract categories, for example, the sentence Jackie cut the bagel with a knife encodes the categories Agent (i.e., Jackie) and Patient (i.e., the bagel). In this paper, we ask whether entities such as the knife are also represented in terms of such a category (often labeled “Instrument”) and, if so, whether this category has a prototype structure. We hypothesized the Proto-instrument is a tool: a (...) physical object manipulated by an intentional agent to affect a change in another individual or object. To test this, we asked speakers of English, Dutch, and German to complete an event description task and a sentence acceptability judgment task in which events were viewed with more or less prototypical instruments. We found broad similarities in how English, Dutch, and German partition the semantic space of instrumental events, suggesting there is a shared concept of the Instrument category. However, there was no evidence to support the specific hypothesis that tools are the core of the Instrument category—instead, our results suggest the most prototypical Instrument is the direct extension of an intentional agent. This paper supports theoretical frameworks where thematic roles are analyzed in terms of prototypes and suggests new avenues of research on how instrumental category structure differs across linguistic and conceptual domains. (shrink)

Topics in Cognitive Science, Volume 13, Issue 1, Page 187-205, January 2021.

Butz, Achimova, Bilkey, and Knott provide a topic overview and discuss whether the special issue contributions may imply that event‐predictive abilities constitute a root for conceptual human thought, because they enable complex, mutually beneficial, but also intricately competitive, social interactions and language communication.

Silent gesture is not considered to be linguistic, on par with spoken and sign languages. It is claimed that silent gestures, unlike language, represent events holistically, without compositional structure. However, recent research has demonstrated that gesturers use consistent strategies when representing objects and events, and that there are behavioral and clinically relevant limits on what form a gesture may take to effect a particular meaning. This systematicity challenges a holistic interpretation of silent gesture, which predicts that there should be no (...) stable form‐meaning correspondence across event representations. Here, we demonstrate to the contrary that untrained gesturers systematically manipulate the form of their gestures when representing events with and without a theme (e.g., Someone popped the balloon vs. Someone walked), that is, transitive and intransitive events. We elicited silent gestures and annotated them for manual features active in coding transitivity distinctions in sign languages. We trained linear support vector machines to make item‐by‐item transitivity predictions based on these features. Prediction accuracy was good across the entire dataset, thus demonstrating that systematicity in silent gesture can be explained with recourse to subunits. We argue that handshape features are constructs co‐opted from cognitive systems subserving manual action production and comprehension for communicative purposes, which may integrate into the linguistic system of emerging sign languages. We further suggest that nonsigners tend to map event participants to each hand, a strategy found across genetically and geographically distinct sign languages, suggesting the strategy's cognitive foundation. (shrink)

What is the relationship between language and event cognition? Past work has suggested that linguistic/aspectual distinctions encoding the internal temporal profile of events map onto nonlinguistic event representations. Here, we use a novel visual detection task to directly test the hypothesis that processing telic versus atelic sentences (e.g., “Ebony folded a napkin in 10 seconds” vs. “Ebony did some folding for 10 seconds”) can influence whether the very same visual event is processed as containing distinct temporal stages including a well‐defined (...) endpoint or lacking such structure, respectively. In two experiments, we show that processing (a)telicity in language shifts how people later construe the temporal structure of identical visual stimuli. We conclude that event construals are malleable representations that can align with the linguistic framing of events. (shrink)

Warren and Dresang comment on the contributions from a psycholinguistic perspective, highlighting close relations between the respective research on events and proposing that, for example, verbs may indeed directly pre‐activate templates of the typically involved event participants.

Events and event prediction are pivotal concepts across much of cognitive science, as demonstrated by the papers in this special issue. We first discuss how the study of events and the predictive processing framework may fruitfully inform each other. We then briefly point to some links to broader philosophical questions about events.

Pursuing a precise, focused train of thought requires cognitive effort. Even more effort is necessary when more alternatives need to be considered or when the imagined situation becomes more complex. Cognitive resources available to us limit the cognitive effort we can spend. In line with previous work, an information-theoretic, Bayesian brain approach to cognitive effort is pursued: to solve tasks in our environment, our brain needs to invest information, that is, negative entropy, to impose structure, or focus, away from a (...) uniform structure or other task-incompatible, latent structures. To get a more complete formalization of cognitive effort, a resourceful event-predictive inference model is introduced, which offers computational and algorithmic explanations about the latent structure of our generative models, the active inference dynamics that unfold within, and the cognitive effort required to steer the dynamics—to, for example, purposefully process sensory signals, decide on responses, and invoke their execution. REPI suggests that we invest cognitive resources to infer preparatory priors, activate responses, and anticipate action consequences. Due to our limited resources, though, the inference dynamics are prone to task-irrelevant distractions. For example, the task-irrelevant side of the imperative stimulus causes the Simon effect and, due to similar reasons, we fail to optimally switch between tasks. An actual model implementation simulates such task interactions and offers first estimates of the involved cognitive effort. The approach may be further studied and promises to offer deeper explanations about why we get quickly exhausted from multitasking, how we are influenced by irrelevant stimulus modalities, why we exhibit magnitude interference, and, during social interactions, why we often fail to take the perspective of others into account. (shrink)

Cognitive Science, Volume 46, Issue 5, May 2022.