Topics in Cognitive Science最新文献

Ruminative thinking, characterized by a recurrent focus on negative and self-related thought, is a key cognitive vulnerability marker of depression and, therefore, a key individual difference variable. This study aimed to develop a computational cognitive model of rumination focusing on the organization and retrieval of information in memory, and how these mechanisms differ in individuals prone to rumination and individuals less prone to rumination. Adaptive Control of Thought-Rational (ACT-R) was used to develop a rumination model by adding memory chunks with negative valence to the declarative memory. In addition, their strength of association was increased to simulate recurrent negative focus, thereby making it harder to disengage from. The ACT-R models were validated by comparing them against two empirical datasets containing data from control and depressed participants. Our general and ruminative models were able to recreate the benchmarks of free recall while matching the behavior exhibited by the control and the depressed participants, respectively. Our study shows that it is possible to build a computational theory of rumination that can accurately simulate the differences in free recall dynamics between control and depressed individuals. Such a model could enable a more fine-tuned investigation of underlying cognitive mechanisms of depression and potentially help to improve interventions by allowing them to more specifically target key mechanisms that instigate and maintain depression.

Over two decades have passed since the publication of van Gelder's (1998) "dynamical hypothesis." In that paper, van Gelder proposed that cognitive agents were not digital computers-per the representational computational approach-but dynamical systems. The evolution of the dynamical hypothesis was driven by parallel advances in three areas. Theoretically, a deeper understanding of genetics, biology, neuroscience, and cognitive science inspired questions about how systems within each domain dynamically interact and extend their effects across spatiotemporal scales. Methodologically, more sophisticated and domain-general tools allowed researchers to discover, model, and quantify system dynamics, structure, and patterns across multiple scales to generate a more comprehensive system-level understanding of behaviors. Empirically, we can analyze a system's behavior while preserving its natural dynamics, revealing evidence that the reductionist approach leads to an incomplete understanding of the components and the overall system. Researchers have traditionally reduced a complex system into its component processes and assumed that the parts can be recombined to explain the whole. These three advances fundamentally altered our understanding of a "cognitive agent:" How their behaviors are driven by long-range coordination across multiple processes, how the interdependent and nested structure of interacting variables produces behaviors that are greater than the sum of its parts, and how environmental constraints shape adaptive yet stable behavioral patterns.

For young children, gesture is found to precede and predict language development. However, we are still building a knowledge base about the specific nature of the relationship between gesture and speech. While much of the research on this topic has been conducted with neurotypical children, there is a growing body of work with children who have or are at increased likelihood of autism spectrum disorder (ASD). Here, we summarize the literature on relations between gesture and speech, including the role of child gesture production as well as that of gesture exposure (caregiver gesture). We include literature on both neurotypical children and children with or at likelihood of ASD, highlight the similarities and differences across populations, and offer implications for research as well as early identification and intervention.

Modulation of visual attention in the Visual World Paradigm relies on parallel processing of linguistic and visual information. Previous studies have argued that the human linguistic capacity includes an aspect of anticipation of upcoming material. Such anticipation can be triggered by both lexical and grammatical/morphosyntactic cues. In this study, we investigated the relationship between comprehension and prediction by testing how subtle changes in visual representations can affect the processing of grammatical case cues in Russian by Russian-German bilingual children (n = 49, age 8-13). The linguistic manipulation followed previous designs, contrasting SVO and OVS sentences, where the first NP (NP1) was marked with nominative or accusative case, respectively. Three types of visual displays were compared: (i) individual referents (potential agent/theme); (ii) pairs of referents (NP1 + potential agent/theme); and (iii) events (representing interactions between the referents). Participants were significantly more sensitive to the case manipulation when presented with events compared to the other two types of visual display. This suggests that they were able to quickly integrate the thematic role information signaled by grammatical case in the event representations. However, they were less likely to use the case information to anticipate upcoming arguments when the target pictures represented individual referents or pairs of noninteracting referents. We hypothesize that the process of argument anticipation is mediated by the activation of syntactic templates (SVO or OSV, depending on the case marking on NP1). The relatively weak anticipation effect observed may be attributed to the absence, or weak representation, of the noncanonical OVS template in the bilingual children's long-term memory.

Decades of research have established that learners benefit when instruction includes hand gestures. This benefit is seen when learners watch an instructor gesture, as well as when they are taught or encouraged to gesture themselves. However, there is substantial individual variability with respect to this phenomenon-not all individuals benefit equally from gesture instruction. In the current paper, we explore the sources of this variability. First, we review the existing research on individual differences that do or do not predict learning from gesture instruction, including differences that are either context-dependent (linked to the particular task at hand) or context-independent (linked to the learner across multiple tasks). Next, we focus on one understudied measure of individual difference: the learner's own spontaneous gesture rate. We present data showing rates of "non-gesturers" across a number of studies and we provide theoretical motivation for why this is a fruitful area for future research. We end by suggesting ways in which research on individual differences will help gesture researchers to further refine existing theories and develop specific predictions about targeted gesture intervention for all kinds of learners.

The International Conference on Cognitive Modelling is dedicated to understanding how the complex processes of the mind can be explained in terms of detailed inner processing. In this issue, we present four representative papers of this field of research from our 20th meeting, ICCM 2022. This meeting was our first hybrid meeting, with a virtual version happening July 11-15, 2022, and an in-person event from July 23-27, 2022, held in Toronto, Canada. The four papers presented here were the top-ranked papers across both the virtual and in-person events. Three of the papers develop novel computational theories about low-level components within the mind and how those components result in high-level phenomena such as motivation, anhedonia, and attention. The final paper demonstrates the use of cognitive modeling to develop novel explanations of a paired associate learning task, and uses those insights to develop and explain human performance in a more complex version of that task.

Internal representations guide our navigation of the world, while language allows us to share some of what is encoded internally with others. I have been interested in the content of thought, the nature of word meanings and what they reveal about thought, and how thoughts are expressed in words. My work has combined evidence from laboratory experimentation with observation of word use in natural settings, including from people who speak different languages. Some of the ideas guiding the work are these: understanding entities in the world non-linguistically engages different representations and processes than talking about them; patterns of word use in a language reflect cultural and linguistic history, not only conceptual representations of current speakers; linguistic and non-linguistic knowledge is therefore at least partially independent, and so language and thought will not always closely parallel one another; the beliefs people express about their concepts and word meanings may not accurately reflect the implicit knowledge they draw on in interacting with and talking about the world; and only by carefully observing actual word use can we understand how word meanings come about and how linguistic knowledge is used to select words for communication.

Many cultures share common constellations and common narratives about the stars in the night sky. Previous research has shown that this overlap in asterisms, minimal star groupings inside constellations, is clearly present across 27 distinct culture groups and can be explained in part by properties of individual stars (brightness) and properties of pairs of stars (proximity) (Kemp, Hamacher, Little, & Cropper, 2022). The same work, however, found no evidence that properties of triples (angle) and quadruples (good continuation) predicted constellation formation. We developed a behavioral experiment to explore how individuals form constellations under conditions that reduce cultural learning. We found that participants independently selected and connected similar stars, and that their responses were predicted by two properties of triples (angle and even spacing) in addition to the properties of brightness and proximity supported by previous work. Our findings lend further evidence to the theory that commonality of constellations across cultures is not a result of shared human history but rather stems from shared human nature.

Great storytelling takes us on a journey the way ordinary reality rarely does. But what exactly do we mean by this "journey?" Recently, literary theorist Karin Kukkonen proposed that storytelling is "probability design:" the art of giving an audience pieces of information bit by bit, to craft the journey of their changing beliefs about the fictional world. A good "probability design" choreographs a delicate dance of certainty and surprise in the reader's mind as the story unfolds from beginning to end. In this paper, we computationally model this conception of storytelling. Building on the classic Bayesian inverse planning model of human social cognition, we treat storytelling as inverse inverse planning: the task of choosing actions to manipulate an inverse planner's inferences, and therefore a human audience's beliefs. First, we use an inverse inverse planner to depict social and physical situations, and present behavioral studies indicating that inverse inverse planning produces more expressive behavior than ordinary "naïve planning." Then, through a series of examples, we demonstrate how inverse inverse planning captures many storytelling elements from first principles: character, narrative arcs, plot twists, irony, flashbacks, and deus ex machina are all naturally encoded in the flexible language of probability design.