The Role of Attention in Category Representation.

Numerous studies have found that selective attention affects category learning. However, previous research did not distinguish between the contribution of focusing and filtering components of selective attention. This study addresses this issue by examining how components of selective attention affect category representation. Participants first learned a rule-plus-similarity category structure, and then were presented with category priming followed by categorization and recognition tests. Additionally, to evaluate the involvement of focusing and filtering, we fit models with different attentional mechanisms to the data. In Experiment 1, participants received rule-based category training, with specific emphasis on a single deterministic feature (D feature). Experiment 2 added a recognition test to examine participants' memory for features. Both experiments indicated that participants categorized items based solely on the D feature, showed greater memory for the D feature, were primed exclusively by the D feature without interference from probabilistic features (P features), and were better fit by models with focusing and at least one type of filtering mechanism. The results indicated that selective attention distorted category representation by highlighting the D feature and attenuating P features. To examine whether the distorted representation was specific to rule-based training, Experiment 3 introduced training, emphasizing all features. Under such training, participants were no longer primed by the D feature, they remembered all features well, and they were better fit by the model assuming only focusing but no filtering process. The results coupled with modeling provide novel evidence that while both focusing and filtering contribute to category representation, filtering can also result in representational distortion.

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.

Exploration, exploitation, and development: Developmental shifts in decision-making.

Decision-making requires balancing exploration with exploitation, yet children are highly exploratory, with exploration decreasing with development. Less is known about what drives these changes. We examined the development of decision-making in 188 three- to eight-year-old children (M = 64 months; 98 girls) and 26 adults (M = 19 years; 13 women). Children were recruited from ethnically diverse suburban middle-class neighborhoods of Columbus, Ohio, USA. Results indicate that mature reward-based choices emerge relatively late in development, with children tending to over-explore. Computational modeling suggests that this exploration is systematic rather than random, as children tend to avoid repeating choices made on the previous trial. This pattern of exploration (reminiscent of novelty preference) decreased with development, whereas the tendency to exploit increased.

The development of visual cognition: The emergence of spatial congruency bias.

In adults, spatial location plays a special role in visual object processing. People are more likely to judge two sequentially presented objects as being identical when they appear in the same location compared to in different locations (a phenomenon referred to as Spatial Congruency Bias [SCB]). However, no comparable Identity Congruency Bias (ICB) is found, suggesting an asymmetric location-identity relationship in object binding. What gives rise to this asymmetric congruency bias? This paper considered two possible hypotheses. Hypothesis 1 suggests that the asymmetric congruency bias results from an inherently special role of location in the visual system. In contrast, Hypothesis 2 suggests that the asymmetric congruency bias is a product of development, reflecting people's experience with the world. To distinguish the two hypotheses, we tested both adults' and 5-year-old children's SCB and ICB by Identity Judgment Experiments and Spatial Judgment Experiments, respectively. The study found that adults only exhibited a SCB, but no ICB. However, young children exhibited both SCB and ICB, suggesting a symmetric congruency bias and reciprocal influences between location and identity in early development. The results indicate that the asymmetric location-identity relationship develops as object identity's influence on location gets pruned away, while location's influence on identity is preserved, possibly due to people's gained experiences with regularities of the world. RESEARCH HIGHLIGHTS: Adults exhibit Spatial Congruency Bias-an asymmetric location-identity relationship with location biasing their judgment of object identities, but not vice versa. Asymmetric congruency bias may result from an inherently special role of location in visual system (Hypothesis 1) or accumulated experiences with the world (Hypothesis 2). To distinguish the two hypotheses, the study investigated the Spatial Congruency Bias and Identity Congruency Bias in both adults and 5-year-old children. Unlike adults who exhibited only Spatial Congruency Bias, 5-year-old children exhibited both Spatial Congruency Bias and Identity Congruency Bias.

From features to categories: The development of inductive generalization.

Young children can generalize from known to novel, but the underlying mechanism is still debated. Some argue that from an early age generalization is category-based and undergoes little development, while others believe that early generalization is similarity-based, and the use of categories emerges over time. The current research brings new evidence to the debate. In Experiment 1 (N = 118), we presented 3- to 5-year-olds and adults with a category learning task followed by an exemplar generation task. Then, in Experiment 2 (N = 126), we presented the same tasks but provided participants with additional conceptual information about the category members. Our results indicate that early reasoning undergoes dramatic development: whereas young children rely mostly on salient features, adults rely on category information. These results challenge category-based accounts of early generalization while supporting similarity-based accounts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cognition: The power of simple associative learning.

Associative learning is traditionally considered to be slow and inefficient compared to 'smarter' rule-based learning. New research reveals the remarkable ability of associative learning in acquiring exceedingly complex categories.

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.

The benefits of immature cognitive control: How distributed attention guards against learning traps.

Cognitive control allows one to focus one's attention efficiently on relevant information while filtering out irrelevant information. This ability provides a means of rapid and effective learning, but using this control also brings risks. Importantly, useful information may be ignored and missed, and learners may fall into "learning traps" (e.g., learned inattention) wherein they fail to realize that what they ignore carries important information. Previous research has shown that adults may be more prone to such traps than young children, but the mechanisms underlying this difference are unclear. The current study used eye tracking to examine the role of attentional control during learning in succumbing to these learning traps. The participants, 4-year-old children and adults, completed a category learning task in which an unannounced switch occurred wherein the feature dimensions most relevant to correct categorization became irrelevant and formerly irrelevant dimensions became relevant. After the switch, adults were more likely than children to ignore the new highly relevant dimension and settle on a suboptimal categorization strategy. Furthermore, eye-tracking analyses reveal that greater attentional selectivity during learning (i.e., optimizing attention to focus only on the most relevant sources of information) predicted this tendency to miss important information later. Children's immature cognitive control, leading to broadly distributed attention, appears to protect children from this trap-although at the cost of less efficient and slower learning. These results demonstrate the double-edged sword of cognitive control and suggest that immature control may serve an adaptive function early in development.

The quest for simplicity in human learning: Identifying the constraints on attention.

For better or worse, humans live a resource-constrained existence; only a fraction of physical sensations ever reach conscious awareness, and we store a shockingly small subset of these experiences in memory for later use. Here, we examined the effects of attention constraints on learning. Among models that frame selective attention as an optimization problem, attention orients toward information that will reduce errors. Using this framing as a basis, we developed a suite of models with a range of constraints on the attention available during each learning event. We fit these models to both choice and eye-fixation data from four benchmark category-learning data sets, and choice data from another dynamic categorization data set. We found consistent evidence for computations we refer to as "simplicity", where attention is deployed to as few dimensions of information as possible during learning, and "competition", where dimensions compete for selective attention via lateral inhibition.

As within, so without, as above, so below: Common mechanisms can support between- and within-trial category learning dynamics.

Two fundamental difficulties when learning novel categories are deciding (a) what information is relevant and (b) when to use that information. Although previous theories have specified how observers learn to attend to relevant dimensions over time, those theories have largely remained silent about how attention should be allocated on a within-trial basis, which dimensions of information should be sampled, and how the temporal order of information sampling influences learning. Here, we use the adaptive attention representation model (AARM) to demonstrate that a common set of mechanisms can be used to specify: (a) How the distribution of attention is updated between trials over the course of learning and (b) how attention dynamically shifts among dimensions within a trial. We validate our proposed set of mechanisms by comparing AARM's predictions to observed behavior in four case studies, which collectively encompass different theoretical aspects of selective attention. We use both eye-tracking and choice response data to provide a stringent test of how attention and decision processes dynamically interact during category learning. Specifically, how does attention to selected stimulus dimensions gives rise to decision dynamics, and in turn, how do decision dynamics influence which dimensions are attended to via gaze fixations? (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Sources of Interference in Memory Across Development.

Episodic memory involves remembering not only what happened but also where and when the event happened. This multicomponent nature introduces different sources of interference that stem from previous experience. However, it is unclear how the contributions of these sources change across development and what might cause the changes. To address these questions, we tested 4- to 5-year-olds (n = 103), 7- to 8-year-olds (n = 82), and adults (n = 70) using item- and source-recognition memory tasks with various manipulations (i.e., list length, list strength, word frequency), and we decomposed sources of interference using a computational model. We found that interference stemming from other items on the study list rapidly decreased with development, whereas interference from preexperimental contexts gradually decreased but remained the major source of interference. The model further quantified these changes, indicating that the ability to discriminate items undergoes rapid development, whereas the ability to discriminate contexts undergoes protracted development. These results elucidate fundamental aspects of memory 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).

Intraobject and extraobject memory binding across early development.

The ability to bind, or link, different aspects of an experience in memory undergoes protracted development across childhood. Most studies of memory binding development have assessed extraobject binding between an object and some external element such as another object, whereas little work has examined the development of intraobject binding, such as between shape and color features within the same object. In this work, we investigate the development of intra- and extraobject memory binding in five-year-olds, eight-year-olds, and young adults with a memory interference paradigm. Between two experiments, we manipulate whether stimuli are presented as coherent objects (Experiment 1: n5-year-olds = 32, 19 males, 13 females; n8-year-olds = 30, 15 males, 15 females; nadults = 30, 15 males, 15 females), requiring intraobject binding between shape and color features, or as spatially separated features (Experiment 2: n5-year-olds = 24, 16 males, 8 females; n8-year-olds = 41, 19 males, 22 females; nadults = 31, 13 males, 18 females), requiring extraobject binding. To estimate the contributions of different binding structures to performance, we present a novel computational model that mathematically instantiates the memory binding, forgetting, and retrieval processes we hypothesize to underlie performance on the task. The results provide evidence of substantial developmental improvements in both intraobject and extraobject binding of shape and color features between 5 and 8 years of age, as well as stronger intraobject compared with extraobject binding of features in all age groups. These findings provide key insights into memory binding across early development. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Examining three-way binding as a constraint on statistical learning.

Models of statistical learning do not place constraints on the complexity of the memory structure that is formed during statistical learning, while empirical studies using the statistical learning task have only examined the formation of simple memory structures (e.g., two-way binding). On the contrary, the memory literature, using explicit memory tasks, has shown that people are able to form memory structures of different complexities and that more complex memory structures (e.g., three-way binding) are usually more difficult to form. We examined whether complex memory structures such as three-way bindings can be implicitly formed through statistical learning by utilizing manipulations that have been used in the paired-associate learning paradigm (e.g., AB/ABr condition). Through three experiments, we show that while simple two-way binding structures can be formed implicitly, three-way bindings can only be formed with explicit instructions. The results indicate that explicit attention may be a necessary component in forming three-way memory structures and suggest that existing models should place constraints on the representational structures that can be formed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Systematic exploration and uncertainty dominate young children's choices.

Organisms need to constantly balance the competing demands of gathering information and using previously acquired information to obtain rewarding outcomes (i.e., the "exploration-exploitation" dilemma). Exploration is critical to obtain information to discover how the world works, which should be particularly important for young children. While studies have shown that young children explore in response to surprising events, little is known about how they balance exploration and exploitation across multiple decisions or about how this process changes with development. In this study, we compare decision-making patterns of children and adults and evaluate the relative influences of reward seeking, random exploration, and systematic switching (which approximates uncertainty-directed exploration). In a second experiment, we directly test the effect of uncertainty on children's choices. Influential models of decision-making generally describe systematic exploration as a computationally refined capacity that relies on top-down cognitive control. We demonstrate that (a) systematic patterns dominate young children's behavior (facilitating exploration), despite protracted development of cognitive control; and (b) that uncertainty plays a major, but complicated, role in determining children's choices. We conclude that while young children's immature top-down control should hinder adult-like systematic exploration, other mechanisms may pick up the slack, facilitating broad information gathering in a systematic fashion to build a foundation of knowledge for use later in life.

The Development of Attention to Objects and Scenes: From Object-Biased to Unbiased.

Selective attention is the ability to focus on goal-relevant information while filtering out irrelevant information. This work examined the development of selective attention to natural scenes and objects with a rapid serial visual presentation paradigm. Children (N = 69, ages 4-6 years) and adults (N = 80) were asked to attend to either objects or scenes, while ignoring the other type of stimulus. A multinomial processing tree model was used to decompose selective attention into focusing and filtering components. The results suggest that attention is object-biased in children, due to difficulty filtering attention to goal-irrelevant objects, whereas attention in adults is relatively unbiased. The findings suggest important developmental asymmetries in selective attention to scenes and objects.

Selective and distributed attention in human and pigeon category learning.

Attention to relevant stimulus features in a categorization task helps to optimize performance. However, the relationship between attention and categorization is not fully understood. For example, even when human adults and young children exhibit comparable categorization behavior, adults tend to attend selectively during learning, whereas young children tend to attend diffusely (Deng & Sloutsky, 2016). Here, we used a comparative approach to investigate the link between attention and categorization in two different species. Given the noteworthy categorization ability of avian species, we compared the attentional profiles of pigeons and human adults. We gave human adults (Experiment 1) and pigeons (Experiment 2) a categorization task that could be learned on the basis of either one deterministic feature (encouraging selective attention) or multiple probabilistic features (encouraging distributed attention). Both humans and pigeons relied on the deterministic feature to categorize the stimuli, albeit humans did so to a much greater degree. Furthermore, computational modeling revealed that most of the adults exhibited maximal selectivity, whereas pigeons tended to distribute their attention among several features. Our findings indicate that human adults focus their attention on deterministic information and filter less predictive information, but pigeons do not. Implications for the underlying brain mechanisms of attention and categorization are discussed.