Topics in Cognitive Science最新文献

Language is inherently multimodal. In spoken languages, combined spoken and visual signals (e.g., co-speech gestures) are an integral part of linguistic structure and language representation. This requires an extension of the parallel architecture, which needs to include the visual signals concomitant to speech. We present the evidence for the multimodality of language. In addition, we propose that distributional semantics might provide a format for integrating speech and co-speech gestures in a common semantic representation.

Successful spoken discourse requires a speaker to be informative to deliver a coherent, meaningful message. The informativeness of discourse can be conveyed by the variety of vocabulary produced (i.e., lexical diversity [LD]), the typicality of vocabulary items used (i.e., core lexicon [CL]), and the amount of relevant content produced (i.e., information units). Yet, it is well documented that older adults produce less informative content compared to younger adults despite relatively subtle changes to LD. The typicality of core lexical items has not been assessed in healthy aging. Paradoxically, these results indicate that some aspects of discourse informativeness remain stable or even improve across the adult lifespan, while other aspects decline. The purpose of the current study is to understand how microlinguistic processes of informativeness change across the adult lifespan. The cross-sectional study included narrative language samples from two wordless picture books collected from 420 healthy participants between 20 and 89 years old. LD and percent of correct information units (%CIUs) were analyzed, as well as CL nouns and verbs. The results indicate that %CIUs and CL nouns demonstrate a quadratic decline starting around the ages of 40 and 60, respectively. LD shows a slight linear decline as a function of age. CL verbs are resistant to age-related changes but are influenced greater by education. The differing findings across the microlinguistic measures can be explained by the weakened connections within the language system and the differential characteristics of the measures. The findings contribute to the aging literature by systematically identifying the trajectory of how variables of informativeness change with age.

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.