"The eyes are the window to the representation": Linking gaze to memory precision and decision weights in object discrimination tasks.

Humans selectively attend to task-relevant information in order to make accurate decisions. However, selective attention incurs consequences if the learning environment changes unexpectedly. This trade-off has been underscored by studies that compare learning behaviors between adults and young children: broad sampling during learning comes with a breadth of information in memory, often allowing children to notice details of the environment that are missed by their more selective adult counterparts. The current work extends the exemplar-similarity account of object discrimination to consider both the intentional and consequential aspects of selective attention when predicting choice. In a novel direct input approach, we used trial-level eye-tracking data from training and test to replace the otherwise freely estimated attention dynamics of the model. We demonstrate that only a model imbued with gaze correlates of memory precision in addition to decision weights can accurately predict key behaviors associated with (a) selective attention to a relevant dimension, (b) distributed attention across dimensions, and (c) flexibly shifting strategies between tasks. Although humans engage in selective attention with the intention of being accurate in the moment, our findings suggest that its consequences on memory constrain the information that is available for making decisions in the future. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

When is a word in good company for learning?

Although identifying the referents of single words is often cited as a key challenge for getting word learning off the ground, it overlooks the fact that young learners consistently encounter words in the context of other words. How does this company help or hinder word learning? Prior investigations into early word learning from children's real-world language input have yielded conflicting results, with some influential findings suggesting an advantage for words that keep a diverse company of other words, and others suggesting the opposite. Here, we sought to triangulate the source of this conflict, comparing different measures of diversity and approaches to controlling for correlated effects of word frequency across multiple languages. The results were striking: while different diversity measures on their own yielded conflicting results, once nonlinear relationships with word frequency were controlled, we found convergent evidence that contextual consistency supports early word learning. RESEARCH HIGHLIGHTS: The words children learn occur in a sea of other words. The company words keep ranges from highly variable to highly consistent and circumscribed. Prior findings conflict over whether variability versus consistency helps early word learning. Accounting for correlated effects of word frequency resolved the conflict across multiple languages. Results reveal convergent evidence that consistency helps early word learning.

No frills: Simple regularities in language can go a long way in the development of word knowledge.

Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of these models raise the intriguing possibility that exposure to word use in language also shapes the word knowledge that children amass during development. However, this possibility is strongly challenged by the fact that models use language input and learning mechanisms that may be unavailable to children. Across three studies, we found that unrealistically complex input and learning mechanisms are unnecessary. Instead, simple regularities of word use in children's language input that they have the capacity to learn can foster knowledge about word meanings. Thus, exposure to language may play a simple but powerful role in children's growing word knowledge. A video abstract of this article can be viewed at https://youtu.be/dT83dmMffnM. RESEARCH HIGHLIGHTS: Natural Language Processing (NLP) models can learn that words are similar in meaning from higher-order statistical regularities of word use. Unlike NLP models, infants and children may primarily learn only simple co-occurrences between words. We show that infants' and children's language input is rich in simple co-occurrence that can support learning similarities in meaning between words. We find that simple co-occurrences can explain infants' and children's knowledge that words are similar in meaning.

Experience and maturation: The contribution of co-occurrence regularities in language to the development of semantic organization.

With development knowledge becomes organized according to semantic links, including early-developing associative (e.g., juicy-apple) and gradually developing taxonomic links (e.g., apple-pear). Word co-occurrence regularities may foster these links: Associative links may form from direct co-occurrence (e.g., juicy-apple), and taxonomic links from shared co-occurrence (e.g., apple and pear co-occur with juicy). Four experiments (2017-2020) investigated this possibility with 4- to 8-year-olds (N = 148, 82 female) and adults (N = 116, 35 female) in a U.S. city with 58.6% White; 29.0% Black, and 5.8% Asian demographics. Results revealed earlier development of the abilities to form direct (ds > 0.536) than the abilities to form shared co-occurrence-based links (ds > 1.291). We argue that the asynchronous development of abilities to form co-occurrence-based links may explain developmental changes in semantic organization.

Category learning is shaped by the multifaceted development of selective attention.

Categories are a fundamental building block of cognition that simplify the multitude of entities we encounter into equivalence classes. By simplifying this barrage of inputs, categories support reasoning about and interacting with their members. For example, despite differences in size, color, and other features, we can treat members of the category of dogs as equivalent, and thus generalize information about any given dog to other dogs. Simplifying entities into categories in adulthood is supported by selective attention, in which people focus on category-relevant attributes, while filtering out category-irrelevant attributes. However, much category learning takes place in infancy and early childhood, when selective attention undergoes substantial development. We designed two experiments to disentangle the contributions of the focusing and filtering aspects of selective attention to category learning over development. Experiment 1 provided evidence that learning simple categories was accompanied by selective attention in both 4- and 5- year-old children and adults. Experiment 2 provided evidence that only focusing contributed to selective attention in 4-year-olds, whereas both focusing and filtering contributed to selective attention in 5-year-olds and adults. Thus, category learning may recruit different aspects of selective attention across development.

Ready to Learn: Incidental Exposure Fosters Category Learning.

Our knowledge of the world is populated with categories such as dogs, cups, and chairs. Such categories shape how we perceive, remember, and reason about their members. Much of our exposure to the entities we come to categorize occurs incidentally as we experience and interact with them in our everyday lives, with limited access to explicit teaching. This research investigated whether incidental exposure contributes to building category knowledge by rendering people "ready to learn"-allowing them to rapidly capitalize on brief access to explicit teaching. Across five experiments (N = 438 adults), we found that incidental exposure did produce a ready-to-learn effect, even when learners showed no evidence of robust category learning during exposure. Importantly, this readiness to learn occurred only when categories possessed a rich structure in which many features were correlated within categories. These findings offer a window into how our everyday experiences may contribute to building category knowledge.

Exposure to co-occurrence regularities in language drives semantic integration of new words.

Human word learning is remarkable: We not only learn thousands of words but also form organized semantic networks in which words are interconnected according to meaningful links, such as those between apple, juicy, and pear. These links play key roles in our abilities to use language. How do words become integrated into our semantic networks? Here, we investigated whether humans integrate new words by harnessing simple statistical regularities of word use in language, including: (a) Direct co-occurrence (e.g., eat-apple) and (b) Shared co-occurrence (e.g., apple and pear both co-occur with eat). In four reported experiments (N = 139), semantic priming (Experiments 1-3) and eye-tracking (Experiment 4) paradigms revealed that new words became linked to familiar words following exposure to sentences in which they either directly co-occurred, or shared co-occurrence. This finding highlights a potentially key role for co-occurrence in building organized word knowledge that is fundamental to our unique fluency with language. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Emergence of Richly Organized Semantic Knowledge from Simple Statistics: A Synthetic Review.

As adults, we draw upon our ample knowledge about the world to support such vital cognitive feats as using language, reasoning, retrieving knowledge relevant to our current goals, planning for the future, adapting to unexpected events, and navigating through the environment. Our knowledge readily supports these feats because it is not merely a collection of stored facts, but rather functions as an organized, semantic network of concepts connected by meaningful relations. How do the relations that fundamentally organize semantic concepts emerge with development? Here, we cast a spotlight on a potentially powerful but often overlooked driver of semantic organization: Rich statistical regularities that are ubiquitous in both language and visual input. In this synthetic review, we show that a driving role for statistical regularities is convergently supported by evidence from diverse fields, including computational modeling, statistical learning, and semantic development. Finally, we identify a number of key avenues of future research into how statistical regularities may drive the development of semantic organization.

The Role of Co-Occurrence Statistics in Developing Semantic Knowledge.

The organization of our knowledge about the world into an interconnected network of concepts linked by relations profoundly impacts many facets of cognition, including attention, memory retrieval, reasoning, and learning. It is therefore crucial to understand how organized semantic representations are acquired. The present experiment investigated the contributions of readily observable environmental statistical regularities to semantic organization in childhood. Specifically, we investigated whether co-occurrence regularities with which entities or their labels more reliably occur together than with others (a) contribute to relations between concepts independently and (b) contribute to relations between concepts belonging to the same taxonomic category. Using child-directed speech corpora to estimate reliable co-occurrences between labels for familiar items, we constructed triads consisting of a target, a related distractor, and an unrelated distractor in which targets and related distractors consistently co-occurred (e.g., sock-foot), belonged to the same taxonomic category (e.g., sock-coat), or both (e.g., sock-shoe). We used an implicit, eye-gaze measure of relations between concepts based on the degree to which children (N = 72, age 4-7 years) looked at related versus unrelated distractors when asked to look for a target. The results indicated that co-occurrence both independently contributes to relations between concepts and contributes to relations between concepts belonging to the same taxonomic category. These findings suggest that sensitivity to the regularity with which different entities co-occur in children's environments shapes the organization of semantic knowledge during development. Implications for theoretical accounts and empirical investigations of semantic organization are discussed.

Statistical regularities shape semantic organization throughout development.

Our knowledge about the world is represented not merely as a collection of concepts, but as an organized lexico-semantic network in which concepts can be linked by relations, such as "taxonomic" relations between members of the same stable category (e.g., cat and sheep), or association between entities that occur together or in the same context (e.g., sock and foot). To date, accounts of the origins of semantic organization have largely overlooked how sensitivity to statistical regularities ubiquitous in the environment may play a powerful role in shaping semantic development. The goal of the present research was to investigate how associations in the form of statistical regularities with which labels for concepts co-occur in language (e.g., sock and foot) and taxonomic relatedness (e.g., sock and pajamas) shape semantic organization of 4-5-year-olds and adults. To examine these aspects of semantic organization across development, we conducted three experiments examining effects of co-occurrence and taxonomic relatedness on cued recall (Experiment 1), word-picture matching (Experiment 2), and looking dynamics in a Visual World paradigm (Experiment 3). Taken together, the results of the three experiments provide evidence that co-occurrence-based links between concepts manifest in semantic organization from early childhood onward, and are increasingly supplemented by taxonomic links. We discuss these findings in relation to theories of semantic development.

Rapid, experience-related changes in the organization of children's semantic knowledge.

The organization of knowledge according to relations between concepts is crucially important for many cognitive processes, and its emergence during childhood is a key focus of cognitive development research. Prior evidence about the role of learning and experience in the development of knowledge organization primarily comes from studies investigating differences between preexisting, naturally occurring groups (e.g., children from rural vs. urban settings, children who own a pet vs. children who do not) and a handful of studies on the effects of researcher-developed educational interventions. However, we know little about whether knowledge organization can be relatively rapidly molded by shorter-term real-world learning experiences (e.g., on a timescale of days vs. years or months). The current study investigated whether naturalistic learning experiences can drive rapid measurable changes in knowledge organization in children by investigating the effects of a week-long zoo summer camp (compared with a control school-based camp) on the degree to which 4- to 9-year-old children's knowledge about animals was organized according to taxonomic relations. Although there were no differences in taxonomic organization between the zoo camp and the school-based camp at pretest, only children who participated in the zoo camp showed increases in taxonomic organization at posttest. Moreover, analyses of changes in taxonomic organization in zoo camp children suggested that these changes were primarily driven by improvements in the degree to which children differentiated between taxonomic categories. These findings provide novel evidence that naturalistic experiences can drive rapid changes in knowledge organization.

Developmental changes in semantic knowledge organization.

Semantic knowledge is a crucial aspect of higher cognition. Theoretical accounts of semantic knowledge posit that relations between concepts provide organizational structure that converts information known about individual entities into an interconnected network in which concepts can be linked by many types of relations (e.g., taxonomic, thematic). The goal of the current research was to address several methodological shortcomings of prior studies on the development of semantic organization, by using a variant of the spatial arrangement method (SpAM) to collect graded judgments of relatedness for a set of entities that can be cross-classified into either taxonomic or thematic groups. In Experiment 1, we used the cross-classify SpAM (CC-SpAM) to obtain graded relatedness judgments and derive a representation of developmental changes in the organization of semantic knowledge. In Experiment 2, we validated the findings of Experiment 1 by using a more traditional pairwise similarity judgment paradigm. Across both experiments, we found that an early recognition of links between entities that are both taxonomically and thematically related preceded an increasing recognition of links based on a single type of relation. The utility of CC-SpAM for evaluating theoretical accounts of semantic development is discussed.

Development of category-based induction and semantic knowledge.

Category-based induction is a hallmark of mature cognition; however, little is known about its origins. This study evaluated the hypothesis that category-based induction is related to semantic development. Computational studies suggest that early on there is little differentiation among concepts, but learning and development lead to increased differentiation based on taxonomic relatedness. This study reports findings from a new task aimed to (a) examine this putative increase in semantic differentiation and (b) test whether individual differences in semantic differentiation are related to category-based induction in 4- to 7-year-old children (N = 85). The results provide the first empirical evidence of an age-related increase in differentiation of representations of animal concepts and suggest that category-based induction is related to increased semantic differentiation.

Single pulse TMS differentially modulates reward behavior.

Greater knowledge of cortical brain regions in reward processing may set the stage for using transcranial magnetic stimulation (TMS) as a treatment in patients with avolition, apathy or other drive-related symptoms. This study examined the effects of single pulse (sp) TMS to two reward circuit targets on drive in healthy subjects. Fifteen healthy subjects performed the monetary incentive delay task (MID) while receiving fMRI-guided spTMS to either inferior parietal lobe (IPL) or supplemental motor area (SMA). The study demonstrated decreasing reaction times (RT) for increasing reward. It also showed significant differences in RT modulation for TMS pulses to the IPL versus the SMA. TMS pulses during the delay period produced significantly more RT slowing when targeting the IPL than those to the SMA. This RT slowing carried over into subsequent trials without TMS stimulation, with significantly slower RTs in sessions that had targeted the IPL compared to those targeting SMA. The results of this study suggest that both SMA and IPL are involved in reward processing, with opposite effects on RT in response to TMS stimulation. TMS to these target cortical regions may be useful in modulating reward circuit deficits in psychiatric populations.

Dissociating averageness and attractiveness: attractive faces are not always average.

Although the averageness hypothesis of facial attractiveness proposes that the attractiveness of faces is mostly a consequence of their averageness, 1 study has shown that caricaturing highly attractive faces makes them mathematically less average but more attractive. Here the authors systematically test the averageness hypothesis in 5 experiments using both rating and visual adaptation paradigms. Visual adaptation has previously been shown to increase both preferences for previously viewed face types (i.e., attractiveness) and their perceived normality (i.e., averageness). The authors used a visual adaptation procedure to test whether facial attractiveness is dependent upon faces' proximity to average (averageness hypothesis) or their location relative to average along an attractiveness dimension in face space (contrast hypothesis). While the typical pattern of change due to visual adaptation was found for judgments of normality, judgments of attractiveness resulted in a very different pattern. The results of these 5 experiments conclusively support the proposal that there are specific nonaverage characteristics that are particularly attractive. The authors discuss important implications for the interpretation of studies using a visual adaptation paradigm to investigate attractiveness.