Cognitive Science最新文献

This letter explores the intricate historical and contemporary links between large language models (LLMs) and cognitive science through the lens of information theory, statistical language models, and socioanthropological linguistic theories. The emergence of LLMs highlights the enduring significance of information-based and statistical learning theories in understanding human communication. These theories, initially proposed in the mid-20th century, offered a visionary framework for integrating computational science, social sciences, and humanities, which nonetheless was not fully fulfilled at that time. The subsequent development of sociolinguistics and linguistic anthropology, especially since the 1970s, provided critical perspectives and empirical methods that both challenged and enriched this framework. This letter proposes that two pivotal concepts derived from this development, metapragmatic function and indexicality, offer a fruitful theoretical perspective for integrating the semantic, textual, and pragmatic, contextual dimensions of communication, an amalgamation that contemporary LLMs have yet to fully achieve. The author believes that contemporary cognitive science is at a crucial crossroads, where fostering interdisciplinary dialogues among computational linguistics, social linguistics and linguistic anthropology, and cognitive and social psychology is in particular imperative. Such collaboration is vital to bridge the computational, cognitive, and sociocultural aspects of human communication and human−AI interaction, especially in the era of large language and multimodal models and human-centric Artificial Intelligence (AI).

Emotion is closely associated with language, but we know very little about how children express emotion in their own writing. We used a large-scale, cross-sectional, and data-driven approach to investigate emotional expression via writing in children of different ages, and whether it varies for boys and girls. We first used a lexicon-based bag-of-words approach to identify emotional content in a large corpus of stories (N>100,000) written by 7- to 13-year-old children. Generalized Additive Models were then used to model changes in sentiment across age and gender. Two other machine learning approaches (BERT and TextBlob) validated and extended these analyses, converging on the finding that positive sentiments in children's writing decrease with age. These findings echo reports from previous studies showing a decrease in mood and an increased use of negative emotion words with age. We also found that stories by girls contained more positive sentiments than stories by boys. Our study shows the utility of large-scale data-driven approaches to reveal the content and nature of children's writing. Future experimental work should build on these observations to understand the likely complex relationships between written language and emotion, and how these change over development.

The interest in crossmodal correspondences, including those involving sounds and involving tastes, has experienced rapid growth in recent years. However, the mechanisms underlying these correspondences are not well understood. In the present study (N = 302), we used an associative learning paradigm, based on previous literature using simple sounds with no consensual taste associations (i.e., square and triangle wave sounds at 200 Hz) and taste words (i.e., sweet and bitter), to test the influence of two potential mechanisms in establishing sound–taste correspondences and investigate whether either learning mechanism could give rise to new and long-lasting associations. Specifically, we examined an emotional mediation account (i.e., using sad and happy emoji facial expressions) and a transitive path (i.e., sound-taste correspondence being mediated by color, using red and black colored squares). The results revealed that the associative learning paradigm mapping the triangle wave tone with a happy emoji facial expression induced a novel crossmodal correspondence between this sound and the word sweet. Importantly, we found that this novel association was still present two months after the experimental learning paradigm. None of the other mappings, emotional or transitive, gave rise to any significant associations between sound and taste. These findings provide evidence that new crossmodal correspondences between sounds and tastes can be created by leveraging the affective connection between both dimensions, helping elucidate the mechanisms underlying these associations. Moreover, these findings reveal that these associations can last for several weeks after the experimental session through which they were induced.

Regular polysemes are sets of ambiguous words that all share the same relationship between their meanings, such as CHICKEN and LOBSTER both referring to an animal or its meat. To probe how a distributional semantic model, here exemplified by bidirectional encoder representations from transformers (BERT), represents regular polysemy, we analyzed whether its embeddings support answering sense analogy questions similar to “is the mapping between CHICKEN (as an animal) and CHICKEN (as a meat) similar to that which maps between LOBSTER (as an animal) to LOBSTER (as a meat)?” We did so using the LRcos model, which combines a logistic regression classifier of different categories (e.g., animal vs. meat) with a measure of cosine similarity. We found that (a) the model was sensitive to the shared structure within a given regular relationship; (b) the shared structure varies across different regular relationships (e.g., animal/meat vs. location/organization), potentially reflective of a “regularity continuum;” (c) some high-order latent structure is shared across different regular relationships, suggestive of a similar latent structure across different types of relationships; and (d) there is a lack of evidence for the aforementioned effects being explained by meaning overlap. Lastly, we found that both components of the LRcos model made important contributions to accurate responding and that a variation of this method could yield an accuracy boost of 10% in answering sense analogy questions. These findings enrich previous theoretical work on regular polysemy with a computationally explicit theory and methods, and provide evidence for an important organizational principle for the mental lexicon and the broader conceptual knowledge system.

Great effort is invested in identifying ways to change people's minds on an issue. A first priority should perhaps be enriching their thinking about the issue. With a goal of enriching their thinking, we studied the views of community adults on the DACA issue—young adults who entered the United States illegally as children. A dialogic method was employed, offering dual benefits in providing participants the opportunity to further develop their own ideas and to consider differing ideas. Yet, participants engaged in dialog only vicariously by observing the talk of a pair of actors who held opposing positions on DACA. The effect on participants’ thinking was greatest in the condition in which they viewed a dialog between the two actors, rather than a comparison condition in which the actors individually expressed their positions. In control conditions, no presentation was observed. Probing questions included in all conditions encouraged a participant to examine and clarify for themselves their own position, potentially enriching it. This condition proved unsuccessful in enriching thinking; participants’ justifications for their own positions in fact became simpler and less qualified. In contrast, observing a video of a like-minded and opposing other did enrich observers’ thinking, yet to a greater degree in the dialogic than nondialogic condition. The findings thus suggest observed dialog as a promising practical approach in promoting deeper thinking.

People can be uncertain in their moral judgments. Philosophers have argued that such uncertainty can either refer to the underlying empirical facts (empirical uncertainty) or to the normative evaluation of these facts itself (normative uncertainty). Psychological investigations of this distinction, however, are rare. In this paper, we combined factor-analytical and experimental approaches to show that empirical and normative uncertainty describe two related but different psychological states. In Study 1, we asked N = 265 participants to describe a case of moral uncertainty and to rate different aspects of their uncertainty about this case. Across this wide range of moral scenarios, our items loaded onto three reliable factors: lack of information, unclear consequences, and normative uncertainty. In Study 2, we confirmed this factor structure using predefined stimulus material. N = 402 participants each rated eight scenarios that systematically varied in their degree of uncertainty regarding the consequences of the described actions and in the value conflict that was inherent to them. The empirical uncertainty factors were mainly affected by the introduction of uncertainty regarding consequences, and the normative uncertainty factor was mainly affected by the introduction of value conflict. Our studies provide evidence that the distinction between empirical and normative uncertainty accurately describes a psychological reality. We discuss the relevance of our findings for research on moral judgments and decision-making, and folk metaethics.

Lexical alignment, a communication phenomenon where conversational partners adapt their word choices to become more similar, plays an important role in the development of language and social communication skills. While this has been studied extensively in the conversations of preschool-aged children and their parents in Western, Educated, Industrialized, Rich, and Democratic (WEIRD) communities, research in other pediatric populations is sparse. This study makes significant expansions on the existing literature by focusing on alignment in naturalistic conversations of school-aged children from a non-WEIRD population across multiple conversational tasks and with different types of adult partners. Typically developing children aged 5 to 8 years (n = 45) engaged in four semi-structured conversations that differed by task (problem-solving vs. play-based) and by partner (parent vs. university student), resulting in a corpus of 180 conversations. Lexical alignment scores were calculated and compared to sham conversations, representing alignment occurring at the level of chance. Both children and adults coordinated their conversational utterances by re-using or aligning each other's word choices. This alignment behavior persisted across conversational tasks and partners, although the degree of alignment was moderated by the conversational context. These findings suggest that lexical alignment is a robust phenomenon in conversations between school-age children and adults. Furthermore, this study extends lexical alignment findings to a non-WEIRD culture, suggesting that alignment may be a coordination strategy employed by adults and children across diverse linguistic and cultural backgrounds.

In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab-based experiments, using artificial languages, many of the cues and features that are part of real-world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed feedback on the gradual learning of language-like statistical regularities within an active guessing game paradigm. In Experiment 1, participants received deterministic feedback (100%), whereas probabilistic feedback (i.e., 75% or 50%) was introduced in Experiment 2. Finally, Experiment 3 explored the impact of mixed probabilistic feedback (33% positive, 33% negative, 33% no feedback). The results showed that cross-situational learning of words was observed without feedback, but participants were able to learn structural regularities of the miniature language only when feedback was provided. Interestingly, the presence of positive feedback was particularly helpful for the learner, promoting more in-depth learning of the artificial language.

This letter addresses two issues in language research that are important to cognitive science: the comparability of word meanings across languages and the neglect of an integrated approach to writing systems. The first issue challenges generativist claims by emphasizing the importance of comparability of data, drawing on typologists’ findings about different languages. The second issue addresses the exclusion of diverse writing systems from linguistic investigation and argues for a more extensive study of their effects on language and cognition. We argue for a refocusing of cognitive science research on linguistic diversity in all modalities to develop the most robust understanding of language and its role in human cognition more broadly.

Social cognition differs from general cognition in its focus on understanding, perceiving, and interpreting social information. However, we argue that the significance of domain-general processes for controlling cognition has been historically undervalued in social cognition and social neuroscience research. We suggest much of social cognition can be characterized as specialized feature representations supported by domain-general cognitive control systems. To test this proposal, we develop a comprehensive working model, based on an interactive activation and competition architecture and applied to the control of action. As such, we label the model “ICON” (interactive activation and competition model for the control of action). We used the ICON model to simulate human performance across various laboratory tasks. Our simulations emphasize that many laboratory-based social tasks do not require socially specific control systems, such as those that are argued to rely on neural networks associated with theory-of-mind. Moreover, our model clarifies that perceived disruptions in social cognition, even in what appears to be disruption to the control of social cognition, can stem from deficits in social representation instead. We advocate for a “default stance” in social cognition, where control is usually general, but representation is specific. This study underscores the importance of integrating social cognition within the broader realm of domain-general control processing, offering a unified perspective on task processing.