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Prior knowledge has long been known to influence retention of newly learned information. In particular, known semantic associations across items facilitates subsequent retrieval for these items, and this effect has been shown to increase with measures of semantic relatedness. In the field of concepts and categories, the processing of taxonomic (e.g., cup-fork, dog-bird) versus thematic (e.g., cup-drink, dog-leash) conceptual relations has been a topic of extensive investigation. Recent work indicates that these two types of conceptual relations can be dissociated at the behavioral and neural levels. However, while semantic relatedness has been explored more broadly, the precise effects of these distinct conceptual relations on associative memory remain unresolved. In this study, we demonstrate that these relations might provide a principled approach to understanding the influence of prior semantic knowledge on memory. We used a stimulus set which consists of word pairs that are either taxonomically or thematically related, while controlling a variety of lexical features relevant to memory performance (e.g., written frequency, number of syllables, concreteness, etc.). We additionally generated semantically unrelated word pairs (e.g., cookie-slate, wool-basement) using word-embeddings from a pre-trained autoencoder model. Participants (n=79) were sequentially shown word pairs (taxonomic, thematic, and unrelated) and subsequently given a cued memory test, in which they were prompted to type the word previously paired with a probe word. We found that word pairs with thematic relations led to better memory performance and shorter reaction times, followed by taxonomic relations, and finally unrelated pairs. These findings may indicate that thematic relations are better remembered due to their known functional or causal properties. This study showed that different conceptual relations differ in the extent to which they facilitate memory performance, providing new insights regarding the influence of prior semantic knowledge on memory.


CogSci 2023

Thematic relations outperform taxonomic relations in a cued recall task

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The 45th Annual Meeting of the Cognitive Science Society will take place in Sydney, Australia as a modified hybrid conference. Presentations from the main-session room will be live-streamed every day for all events. This will include all invited talks and award sessions. Recordings of all CogSci 2023 sessions will be made available for on-demand viewing after the conference.<br>
The in-person component will be held at the International Convention Centre Sydney at Darling Harbour. The Conference will take place Wednesday July 26th – Saturday July 29th, 2023 (Wednesday, July 26th is the Workshops Day).

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The 45th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Key questions in the study of categorization are how individuals form categories from experience and extend that knowledge to assess membership of novel examples. Popular accounts predict generalization to be based on either similarity to reference points or the application of rules or bounds. However, recent data show that some categorization behavior defies the predictions of leading accounts. Expanding on these findings, in the present experiment participants learned a one or two dimensional alternating category structure and were then tested on near and far transfer tasks. Findings reveal that individuals can extend a learned alternating category structure across multidimensional spaces and increasingly distant generalization regions. A new far transfer task suggests that alternation is learned in the form of a relational category at the level of the domain space within which subjects have learned an attribute-based categorization scheme operating at the item level.

Alternation as a Relational Category

Some people say they routinely think in an “inner voice,” while others assume this phrase is just a figure of speech. Across two preregistered experiments (N = 190), we investigated whether such subjective differences in internal verbalization predict attested effects of language on perceptual discrimination. Participants completed a canonical discrimination task assessing language-driven categorical perception of facial expressions, plus a self-report measure of internal verbalization and other modes of mental representation. The results replicated the behavioral signatures of categorical perception—faster and more accurate responses for cross-category than within-category discriminations. However, the strength of these effects was unrelated to participants’ propensity for internal verbalization. Our findings suggest that subjective experiences of inner voice use are not a reliable indicator of linguistic involvement in perceptual discrimination. These findings add to an emerging body of research showing that even large differences in mental experiences often lack clear behavioral consequences.

Does Experiencing an “Inner Voice” Predict Language-Driven Categorical Perception?

When people make decisions, these are often sequential, and later decisions frequently depend on the outcome of the previous decision. For instance, a doctor will first decide on a patient's treatment and then its duration. Grammar learning shows that humans can learn temporal regularities between such sequential information. However, little is known about sequential category learning tasks. Here, we investigate learning of regularities between two categorization tasks and generalization to novel objects. In an experiment, we varied whether a contingency between the outcome of two categorization tasks existed and whether they were adjacent (the tasks followed each other) or non-adjacent (an intervening task in between). Participants learned to categorize the objects of the second task in adjacent condition better than other conditions. However, both regularity conditions were beneficial to categorize novel objects (generalization). The results show the importance of considering temporal regularities between decision tasks in theories of category learning.

Learning Regularity in a Sequence of Decision-Making Tasks

In this study we conducted further tests of the ability of a computational model to fit human category learning performance. The Divergent Autoencoder (DIVA) is a generative-connectionist model of human categorization that learns through error-driven adjustments to predict class membership on the basis of the fidelity of auto-associative item reconstructions with respect to each category (Kurtz 2007). DIVA was tested on the classic SHJ category structures resulting in new qualitative and quantitative fits to both the original and revised SHJ orderings that show the impact of proposed design modifications and parameters. Theoretical implications for psychological accounts of category learning are discussed.

Modeling Human Performance on SHJ Category Structures with a Divergent Autoencoder

It is well known that continuous encoding and recall of similar semantic content leads to memory deficits caused by the build-up of proactive interference. This build-up can be released if the content is switched to a different semantic category. While release from proactive interference has been studied using non-semantic content, it has yet to be studied with relational categories (i.e., categories that cohere based on fulfilling a particular semantic relationship such as obstacles). Recent findings suggest that relational information may be stored as individual entities similar to traditional entity categories. To assess the extent to which entity and relational content are similarly stored and retrieved, participants repeatedly encode and recall lists of word singletons in either an entity or relational category condition. Recall performance is evaluated for each list to compare the build-up and release of proactive interference for participants exposed to a semantic content switch or corresponding no-switch controls.

Release from Proactive Interference with Relational Categories Versus Traditional Entity Categories

Humans can readily generalize their learning to new visual concepts, and infer their associated meanings. How do people align the different conceptual systems learned from different modalities? In the present paper, we examine emojis— pictographs uniquely situated between visual and linguistic modalities—to explore the role of alignment and multimodality in visual and linguistic semantics. Simulation experiments show that relational structures of emojis captured in visual and linguistic conceptual systems can be aligned, and that the ease of alignment increases as the number of emojis increases. We also found that emojis with subjective impressions of high popularity are easier to align between their visual and linguistic representations, suggesting the expressive power of these emojis is likely associated with their popularity. A behavioral experiment was conducted to measure similarity patterns between 48 emojis, and to compare human similarity judgments with three models. We found that the model trained with multimodal data by aligning visual and semantic spaces best accounts for human judgments.

Human similarity judgments of emojis support alignment of conceptual systems across modalities

This work tests three coping mechanisms for time pressure in similarity-based inferences from multiple features. Specifically, we test whether time pressure makes people attend to fewer object features, respond less precisely, or simplify the psychological similarity computation. We ran two preregistered time pressure experiments (Ns = 61 and 175), in which people classified objects or rated the similarity of object pairs. Inferential statistics and computational modeling in an exemplar-similarity framework indicate that time pressure mostly reduced participants’ response precision, especially concerning their similarity judgments. Specifically, participants’ categorizations were less deterministic and their similarity judgments became more variable as time pressure increased. In contrast, we do not find evidence that participants attend to fewer features or simplify the similarity computation. These results add to the evidence that time pressure and other cognitive load do not necessarily affect cognitive processes themselves but rather lower the precision of response selection.

Understanding Speeded Categorizations and Similarity Judgments Using Computational Cognitive Modeling

Conceptions of social disparities as natural and biologically-caused, known as “essentialist” conceptions, lead to the maintenance social disparities. Surprisingly little research has examined whether formal educational experiences – directly teaching people about the nature and origins of social disparities – can reduce essentialist conceptions. We investigate how social science coursework (e.g., sociology, history, anthropology) impact (a) essentialist vs. structural explanations for racial disparities, and (b) social essentialism more broadly, in a diverse group of undergraduates (n = 246). Results suggest that students who have completed such coursework show reduced endorsement of essentialist explanations for racial disparities, but enhanced endorsement of other dimensions of social essentialist thought (e.g., the view that social categories are meaningfully distinct from one another). Thus, social science coursework may have a nuanced impact on social essentialism. We discuss the questions these results raise regarding the relations between explanatory thinking and other dimensions of social essentialism.

How does higher education in the social sciences impact social essentialist thinking?

In two experiments (N=888), we explored to what extent the folk concept of art is compatible with the most famous philosophical definitions of art. We also investigated whether the folk concept of art is an essentialist or a non-essentialist concept. We manipulated three factors: whether an object is created intentionally, whether it has aesthetic value, and whether it is institutionally recognized. In addition, we also manipulated the artistic domain (visual art or music). The results suggest that none of the three properties is seen by the folk as necessary for an object to be considered art. The folk concept of art might be a cluster concept.

What Is Art? The Role of Intention, Beauty, and Institutional Recognition

How do children – who are undeniably productive learners – think about their learning? Do children understand, as adults do, that learning is a process of continuous improvement over time? To explore children’s emerging representations of the learning process, we created a non-verbal motor learning paradigm where 4- to 8-year-olds predicted their own learning without prior experience. We found that by age 7, children conceptualized learning as a process of getting better over time. Younger children, however, were overly optimistic about how well they would do at the game and often predicted near- perfect performance across trials. This work suggests that children’s understanding of learning as a process develops across childhood, which may have implications for young children’s learning decisions.

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Thematic relations outperform taxonomic relations in a cued recall task

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