Development of implicit and explicit category learning

Feedback and observational learning differ in effectiveness during category learning in early school aged children and adults

When learning new categories, do children benefit from the same types of training as adults? We compared the effects of feedback-based training with observational training in young adults (ages 18-25) and early school aged children (ages 6-7) across two different multimodal category learning tasks: conjunctive rule based and information integration. We used multimodal stimuli that varied across a visual feature (rotation speed of the "planet" stimulus) and an auditory feature (pitch frequency of a pure tone stimulus). We found an interaction between age and training type for the rule-based category task, such that adults performed better in feedback training than in observational training, whereas training type had no significant effect on children's category learning performance. Overall adults performed better than children in learning both the rule based and information integration category structures. In information integration category learning, feedback versus observational training did not have a significant effect on either adults' or children's category learning. Computational modelling revealed that children defaulted to univariate rules in both tasks. The finding that children do not benefit from feedback training and can learn successfully via observational learning has implications for the design of educational interventions appropriate for children.

Procedural auditory category learning is selectively disrupted in developmental language disorder

Speech communication depends on accurate perception and identification of speech sounds, which vary across talkers and word or sentence contexts. The ability to map this variable input onto discrete speech sound representations relies on categorization. Recent research and theoretical models implicate the procedural learning system in the ability to learn novel speech and non-speech categories. This connection is particularly intriguing because several language disorders that demonstrate linguistic impairments are proposed to stem from procedural learning and memory dysfunction. One such disorder, Developmental Language Disorder (DLD), affects 7.5% of children and persists into adulthood. While DLD is associated with general linguistic impairments, it is not yet clear how fundamental perceptual and cognitive processes supporting language are impacted, such as the ability to learn novel auditory categories. We examined auditory category learning in children with DLD and typically developed (TD) children using two well-matched nonspeech auditory category learning challenges to draw upon presumed procedural (information-integration) versus declarative (rule-based) learning systems. We observed impaired information-integration category learning and intact rule-based category learning in the DLD group. Quantitative model-based analyses revealed reduced use of, and slower shifting to, optimal procedural-based strategies in DLD and slower shifting to but similarly efficient use of optimal hypothesis-testing strategies. The dissociation is consistent with the Procedural Deficit Hypothesis of language disorders and supports the theoretical distinction of multiple category learning systems. These findings demonstrate that highly controlled experimental tasks assessing perceptual and cognitive abilities can relate to real-world challenges facing individuals with DLD in forming stable linguistic representations.

Auditory Category Learning in Children With Dyslexia

PURPOSE

Developmental dyslexia is proposed to involve selective procedural memory deficits with intact declarative memory. Recent research in the domain of category learning has demonstrated that adults with dyslexia have selective deficits in Information-Integration (II) category learning that is proposed to rely on procedural learning mechanisms and unaffected Rule-Based (RB) category learning that is proposed to rely on declarative, hypothesis testing mechanisms. Importantly, learning mechanisms also change across development, with distinct developmental trajectories in both procedural and declarative learning mechanisms. It is unclear how dyslexia in childhood should influence auditory category learning, a critical skill for speech perception and reading development.

METHOD

We examined auditory category learning performance and strategies in 7- to 12-year-old children with dyslexia (n = 25; nine females, 16 males) and typically developing controls (n = 25; 13 females, 12 males). Participants learned nonspeech auditory categories of spectrotemporal ripples that could be optimally learned with either RB selective attention to the temporal modulation dimension or procedural integration of information across spectral and temporal dimensions. We statistically compared performance using mixed-model analyses of variance and identified strategies using decision-bound computational models.

RESULTS

We found that children with dyslexia have an apparent selective RB category learning deficit, rather than a selective II learning deficit observed in prior work in adults with dyslexia.

CONCLUSION

These results suggest that the important skill of auditory category learning is impacted in children with dyslexia and throughout development, individuals with dyslexia may develop compensatory strategies that preserve declarative learning while developing difficulties in procedural learning.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25148519.

Nameability supports rule-based category learning in children and adults

The present study tested the hypothesis that verbal labels support category induction by providing compact hypotheses. Ninety-seven 4- to 6-year-old children (M = 63.2 months; 46 female, 51 male; 77% White, 8% more than one race, 4% Asian, and 3% Black; tested 2018) and 90 adults (M = 20.1 years; 70 female, 20 male) in the Midwestern United States learned novel categories with features that were easy (e.g., "red") or difficult (e.g., "mauve") to name. Adults (d = 1.06) and-to a lesser extent-children (d = 0.57; final training block) learned categories composed of more nameable features better. Children's knowledge of difficult-to-name color words predicted their learning for categories with difficult-to-name features. Rule-based category learning may be supported by the emerging ability to form verbal hypotheses.

Category Flexibility in Emotion Learning

Learners flexibly update category boundaries to adjust to the range of experiences they encounter. However, little is known about whether the degree of flexibility is consistent across domains. We examined whether categorization of social input, specifically emotions, is afforded more flexibility as compared to other biological input. To address this question, children (6-12 years; 32 female, 37 male; 7 Hispanic or Latino, 62 not Hispanic or Latino; 8 Black or African American, 14 multiracial, 46 White, 1 selected "other") categorized faces morphed from calm to upset and animals morphed from a horse to a cow across task phases that differed in the distribution of stimuli presented. Learners flexibly adjusted both emotion and animal category boundaries according to distributional information, yet children showed more flexibility when updating their category boundaries for emotions. These results provide support for the idea that children-who must adjust to the vast and varied emotional signals of their social partners-respond to social signals dynamically in order to make predictions about the internal states and future behaviors of others.

When Time Shifts the Boundaries: Isolating the Role of Forgetting in Children's Changing Category Representations

In studies of children's categorization, researchers have typically studied how encoding characteristics of exemplars contribute to children's generalization. However, it is unclear whether children's internal cognitive processes alone, independent of new information, may also influence their generalization. Thus, we examined the role that one cognitive process, forgetting, plays in shaping children's category representations by conducting three experiments. In the first two experiments, participants (NExp1=37, Mage=4.02 years; NExp2=32, Mage=4.48 years) saw a novel object labeled by the experimenter and then saw five new objects with between one and five features changed from the learned exemplar. The experimenter asked whether each object was a member of the same category as the exemplar; children saw the five new objects either immediately or after a five-minute delay. Children endorsed category membership at higher rates at immediate test than at delayed test, suggesting that children's category representations became narrower over time. In Experiment 3, we investigated forgetting as a key mechanism underlying the narrowing found in Experiments 1 and 2. We showed participants (NExp3=34, Mage=4.20 years) the same exemplars used in Experiments 1 and 2; then, either immediately or after a five-minute delay, we showed children seven individual object features and asked if each one had been part of the exemplar. Children's accuracy was lower after the delay, showing that they did indeed forget individual features. Taken together, these results show that forgetting plays an important role in changing children's newly-learned categories over time.

Auditory and visual category learning in children and adults

Categories are fundamental to everyday life and the ability to learn new categories is relevant across the lifespan. Categories are ubiquitous across modalities, supporting complex processes such as object recognition and speech perception. Prior work has proposed that different categories may engage learning systems with unique developmental trajectories. There is a limited understanding of how perceptual and cognitive development influences learning as prior studies have examined separate participants in a single modality. The current study presents a comprehensive assessment of category learning in 8-12-year-old children (12 female; 34 white, 1 Asian, 1 more than one race; M household income $85-$100 K) and 18-61-year-old adults (13 female; 32 white, 10 Black or African American, 4 Asian, 2 more than one race, 1 other; M household income $40-55 K) in a broad sample collected online from the United States. Across multiple sessions, participants learned categories across modalities (auditory, visual) that engage different learning systems (explicit, procedural). Unsurprisingly, adults outperformed children across all tasks. However, this enhanced performance was asymmetrical across categories and modalities. Adults far outperformed children in learning visual explicit categories and auditory procedural categories, with fewer differences across development for other types of categories. Adults' general benefit over children was due to enhanced information processing, while their superior performance for visual explicit and auditory procedural categories was associated with less cautious correct responses. These results demonstrate an interaction between perceptual and cognitive development that influences learning of categories that may correspond to the development of real-world skills such as speech perception and reading. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Latent Markov Models to Test the Strategy Use of 3-Year-Olds in a Rule-Based Feedback-Learning Task

This study is the first to investigate how 3-year-olds learn simple rules from feedback using the Toddler Card Sorting Task (TCST). To account for intra- and inter- individual differences in the learning process, latent Markov models were fitted to the time series of accuracy responses using maximum likelihood techniques (Visser et al., 2002). In a first, exploratory study (N = 110, 3- to 5-years olds) a considerable group of 3-year olds applied a hypothesis testing learning strategy. A second study confirmed these results with a preregistered study (3-years olds, N = 60). Under supportive learning conditions, a majority of 3-year- olds was capable of hypothesis testing. Furthermore, older children and those with bigger working memory capacities were more likely to use hypothesis testing, even though the latter group perseverated more than younger children or those with smaller working memory capacities. 3-year-olds are more advanced feedback-learners than assumed.

An Implicit-Explicit Framework for Intervention Methods in Developmental Language Disorder

PURPOSE

The growing interest in framing intervention approaches as either implicit or explicit calls for a discussion of what makes intervention approaches engage each of these learning systems, with the goal of achieving a shared framework. This tutorial presents evidence for the interaction between implicit and explicit learning systems, and it highlights the intervention characteristics that promote implicit or explicit learning as well as outcome measures that tap into implicit or explicit knowledge. This framework is then applied to eight common intervention approaches and notable combinations of approaches to unpack their differential engagement of implicit and explicit learning.

CONCLUSIONS

Many intervention characteristics (e.g., instructions, elicitation techniques, feedback) can be manipulated to move an intervention along the implicit-explicit continuum. Given the bias for using explicit learning strategies that develops throughout childhood and into adulthood, clinicians should be aware that most interventions (even those that promote implicit learning) will engage the explicit learning system. However, increased awareness of the implicit and explicit learning systems and their cognitive demands will allow clinicians to choose the most appropriate intervention for the target behavior.

Neuroanatomical differences in the memory systems of intellectual giftedness and typical development

INTRODUCTION

Studying neuro-structural markers of intellectual giftedness (IG) will inform scientific understanding of the processes helping children excel academically.

METHODS

Structural and diffusion-weighted MRI was used to compare regional brain shape and connectivity of 12 children with average to high average IQ and 18 IG children, defined as having IQ greater than 145.

RESULTS

IG had larger subcortical structures and more robust white matter microstructural organization between those structures in regions associated with explicit memory. TD had more connected, larger subcortical structures in regions associated with implicit memory.

CONCLUSIONS

It was found that the memory systems within brains of children with exceptional intellectual abilities are differently sized and connected compared to the brains of typically developing children. These different neurodevelopmental trajectories suggest different learning strategies. A spectrum of intelligence types is envisioned, facilitated by different ratios of implicit and explicit system, which was validated using a large external dataset.

iPads for Teaching Graphic Symbols to People With Autism Spectrum Disorder

Individuals with low functioning autism spectrum disorders (LFASD) who demonstrate significant cognitive and communication needs benefit from using technology for learning graphic symbols for enhancing participation. This study investigated if an iPad application would increase identification of graphic symbols by children and adults with LFASD. Adults and children with LFASD used an application to learn 15 graphic symbols. Participants were able to focus for the duration of the activity and use the educational software for learning graphic symbols. By the end to the study, 50% of the participants in both groups recognized the meaning of more symbols after intervention. iPad use enabled control of the stimulus by reducing communication barriers, which increased participants' ability to learn symbols. Even participants with little ability to focus were able to complete the whole activity. Technology enabled learning of most of the symbols though the specially created application.

Category Learning in Schoolchildren. Its Relation to Age, Academic Marks and Resolution Patterns

The aim of this research was to study the learning process using an objective and computerized task. The performance of 466 schoolchildren aged between 6 and 11 in a category learning task, the Category Learning Test (CLT), was examined. The results showed evidence of category learning throughout the trials for the whole sample, F(7, 469) = 29.979, p <.001. In addition, categorization performance improved with age, H(2) = 48.475, p <.001. However, there were old children that struggled with the task and young children that performed very well. The ability to learn the categories was related to the children's behavior when trying to solve the task: the response speed (r = -.217, p <.01) and the organization index (r = .247, p <.01). Nevertheless, performance in the task and academic marks were not related. We discuss the impact of these findings on the promotion and improvement of learning in schools: an intervention to promote slowness and organization might help some children to learn.

Perceptual dimensions influence auditory category learning

Human category learning appears to be supported by dual learning systems. Previous research indicates the engagement of distinct neural systems in learning categories that require selective attention to dimensions versus those that require integration across dimensions. This evidence has largely come from studies of learning across perceptually separable visual dimensions, but recent research has applied dual system models to understanding auditory and speech categorization. Since differential engagement of the dual learning systems is closely related to selective attention to input dimensions, it may be important that acoustic dimensions are quite often perceptually integral and difficult to attend to selectively. We investigated this issue across artificial auditory categories defined by center frequency and modulation frequency acoustic dimensions. Learners demonstrated a bias to integrate across the dimensions, rather than to selectively attend, and the bias specifically reflected a positive correlation between the dimensions. Further, we found that the acoustic dimensions did not equivalently contribute to categorization decisions. These results demonstrate the need to reconsider the assumption that the orthogonal input dimensions used in designing an experiment are indeed orthogonal in perceptual space as there are important implications for category learning.

Adaptive flexibility in category learning? Young children exhibit smaller costs of selective attention than adults

Previous research has shown that when learning categories, adults and young children allocate attention differently. Adults tend to attend selectively, focusing primarily on the most relevant information, whereas young children tend to distribute their attention broadly. Although selective attention is useful in many situations, it also has costs. In addition to ignoring information that may turn out to be useful later, selective attention can have long-term costs, such as learned inattention-ignoring formerly irrelevant sources of information in novel situations. In 2 reported experiments, adults and 4-year-old children completed a category learning task in which an unannounced shift occurred such that information that was most relevant became irrelevant, whereas formerly irrelevant information became relevant. Costs stemming from this shift were assessed. The results indicate that adults exhibit greater costs due to learned inattention than young children. Distributing attention may be adaptive in young children, making them flexible to changing contingencies in the world and facilitating broad information gathering, both of which are useful when general knowledge about the environment is limited. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Auditory information-integration category learning in young children and adults

Adults outperform children on category learning that requires selective attention to individual dimensions (rule-based categories) due to their more highly developed working memory abilities, but much less is known about developmental differences in learning categories that require integration across multiple dimensions (information-integration categories). The current study investigated auditory information-integration category learning in 5- to 7-year-old children (n = 34) and 18- to 25-year-old adults (n = 35). Adults generally outperformed children during learning. However, some children learned the categories well and used strategies similar to those of adults, as assessed through decision-bound computational models. The results demonstrate that information-integration learning ability continues to develop throughout at least middle childhood. These results have implications for the development of mechanisms that contribute to speech category learning.

The role of differential outcomes-based feedback on procedural memory

In categorization tasks, two memory systems may be involved in the learning of categories: one explicit and rule-based system and another implicit and procedure-based system. Learning of rule-based categories relies on some form of explicit reasoning, whereas procedural memory underlies information-integration category-learning tasks, in which performance is maximized only if information of two (or more) dimensions is integrated. The present study aimed at investigating the role of how feedback is administered, whether differential or non-differential, in procedural learning. An information-integration category-learning task was designed, where the to-be-categorized stimuli differed in two dimensions. Participants were randomly assigned to two groups: one group received the reinforcers for correct categorizations differentially, one for each category (the differential outcomes procedure, DOP), and the other group received the reinforcers randomly (the non-differential outcomes procedure, NOP). The participants of the DOP group showed better procedural learning in the categorization task, compared to the NOP group. Moreover, the analysis of learning strategies revealed that more participants developed more optimal strategies in the DOP group than in the NOP group. These results extend the benefits of the differential outcomes-based feedback to non-declarative memory tasks and help better understand the role of feedback in procedural learning.

Modulation of striatum based non-declarative and medial temporal lobe based declarative memory predicts academic achievement at university level

BACKGROUND

There is a dearth of research on the roles of non-declarative (implicit) learning linked to the striatum and declarative (explicit) learning associated with the medial temporal lobes as predictors of academic attainment.

METHODS

Participants were 120 undergraduate students, studying Psychology or Engineering, who completed several long-term memory tests.

RESULTS

There was a significant interaction between the groups (Psychology or Engineering) and task type (declarative or non-declarative): Engineers performed better at declarative and psychologists at non-declarative learning. Furthermore, non-declarative but not declarative learning scores were significant correlates of academic achievement (r = 0.326, p < .05). Moreover, competitive modulation (activation of non-declarative learning in conjunction with deactivation of declarative learning) was a significant predictor of future academic achievement in both psychology (r = 0.264, p < .05) and Engineering (r = 0.300, p < .05) groups.

CONCLUSIONS

The results confirm that these declarative and non-declarative systems interact competitively and that the extent of this competition may have implications for understanding educational attainment.

Cognitive changes in conjunctive rule-based category learning: An ERP approach

When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule ("easy" stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule ("difficult" stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.

Structural Learning in a Visuomotor Adaptation Task Is Explicitly Accessible

Structural learning is a phenomenon characterized by faster learning in a new situation that shares features of previously experienced situations. One prominent example within the sensorimotor domain is that human participants are faster to counter a novel rotation following experience with a set of variable visuomotor rotations. This form of learning is thought to occur implicitly through the updating of an internal forward model, which predicts the sensory consequences of motor commands. However, recent work has shown that much of rotation learning occurs through an explicitly accessible process, such as movement re-aiming. We sought to determine if structural learning in a visuomotor rotation task is purely implicit (e.g., driven by an internal model) or explicitly accessible (i.e., re-aiming). We found that participants exhibited structural learning: following training with a variable set of rotations, they more quickly learned a novel rotation. This benefit was entirely conferred by the explicit re-aiming of movements. Implicit learning offered little to no contribution. Next, we investigated the specificity of this learning benefit by exposing participants to a novel perturbation drawn from a statistical structure either congruent or incongruent with their prior experience. We found that participants who experienced congruent training and test phase structure (i.e., rotations to rotation) learned more quickly than participants exposed to incongruent training and test phase structure (i.e., gains to rotation) and a control group. These results suggest that structural learning in a visuomotor rotation task is specific to previously experienced statistical structure and expressed via explicit re-aiming of movements.

Encouraging top-down attention in visual search:A developmental perspective

Four experiments are reported in which 60 younger children (7-8 years old), 60 older children (10-11 years old), and 60 young adults (18-25 years old) performed a conjunctive visual search task (15 per group in each experiment). The number of distractors of each feature type was unbalanced across displays to evaluate participants' ability to restrict search to the smaller subset of features. The use of top-down attention processes to restrict search was encouraged by providing external aids for identifying and maintaining attention on the smaller set. In Experiment 1, no external assistance was provided. In Experiment 2, precues and instructions were provided to focus attention on that subset. In Experiment 3, trials in which the smaller subset was represented by the same feature were presented in alternating blocks to eliminate the need to switch attention between features from trial to trial. In Experiment 4, consecutive blocks of the same subset features were presented in the first or second half of the experiment, providing additional consistency. All groups benefited from external support of top-down attention, although the pattern of improvement varied across experiments. The younger children benefited most from precues and instruction, using the subset search strategy when instructed. Furthermore, younger children benefited from blocking trials only when blocks of the same features did not alternate. Older participants benefited from the blocking of trials in both Experiments 3 and 4, but not from precues and instructions. Hence, our results revealed both malleability and limits of children's top-down control of attention.

Differential Impact of Visuospatial Working Memory on Rule-based and Information-integration Category Learning

Previous studies have indicated that the category learning system is a mechanism with multiple processing systems, and that working memory has different effects on category learning. But how does visuospatial working memory affect perceptual category learning? As there is no definite answer to this question, we conducted three experiments. In Experiment 1, the dual-task paradigm with sequential presentation was adopted to investigate the influence of visuospatial working memory on rule-based and information-integration category learning. The results showed that visuospatial working memory interferes with rule-based but not information-integration category learning. In Experiment 2, the dual-task paradigm with simultaneous presentation was used, in which the categorization task was integrated into the visuospatial working memory task. The results indicated that visuospatial working memory affects information-integration category learning but not rule-based category learning. In Experiment 3, the dual-task paradigm with simultaneous presentation was employed, in which visuospatial working memory was integrated into the category learning task. The results revealed that visuospatial working memory interferes with both rule-based and information-integration category learning. Through these three experiments, we found that, regarding the rule-based category learning, working memory load is the main mechanism by which visuospatial working memory influences the discovery of the category rules. In addition, regarding the information-integration category learning, visual resources mainly operates on the category representation.

Selective attention, diffused attention, and the development of categorization

How do people learn categories and what changes with development? The current study attempts to address these questions by focusing on the role of attention in the development of categorization. In Experiment 1, participants (adults, 7-year-olds, and 4-year-olds) were trained with novel categories consisting of deterministic and probabilistic features, and their categorization and memory for features were tested. In Experiment 2, participants' attention was directed to the deterministic feature, and in Experiment 3 it was directed to the probabilistic features. Attentional cueing affected categorization and memory in adults and 7-year-olds: these participants relied on the cued features in their categorization and exhibited better memory of cued than of non-cued features. In contrast, in 4-year-olds attentional cueing affected only categorization, but not memory: these participants exhibited equally good memory for both cued and non-cued features. Furthermore, across the experiments, 4-year-olds remembered non-cued features better than adults. These results coupled with computational simulations provide novel evidence (1) pointing to differences in category representation and mechanisms of categorization across development, (2) elucidating the role of attention in the development of categorization, and (3) suggesting an important distinction between representation and decision factors in categorization early in development. These issues are discussed with respect to theories of categorization and its development.

Developmental changes between childhood and adulthood in passive observational and interactive feedback-based categorization rule learning

As children start attending school they are more likely to face situations where they have to autonomously learn about novel object categories (e.g. by reading a picture book with descriptions of novel animals). Such autonomous observational category learning (OCL) gradually complements interactive feedback-based category learning (FBCL), where a child hypothesizes about the nature of a novel object, acts based on his prediction, and then receives feedback indicating the correctness of his prediction. Here we tested OCL and FBCL skills of elementary school children and adults. In both conditions, participants performed complex rule-based categorization tasks that required associating novel objects with novel category-labels. We expected children to perform better in FBCL tasks than in OCL tasks, whereas adults to be skilled in both tasks. As hypothesized, in early-phase learning children performed better in FBCL tasks than in OCL tasks. Unexpectedly, adults performed somewhat better in OCL tasks. Early-phase FBCL performance in the two age groups was matched, but the OCL performance of adults was higher than that of children. In late-phase learning there was only an age group main effect (adults > children). Moreover, performance in post-learning categorization tasks, that did not require label recollection, indicated that in FBCL tasks children were likely to directly learn the associations between an object and a category label, whereas in the OCL tasks they were likely to first learn which feature-dimensions were relevant. These findings shed light on developmental changes in cognitive control and learning mechanisms. Implications for educational settings are discussed.

The role of age and executive function in auditory category learning

Auditory categorization is a natural and adaptive process that allows for the organization of high-dimensional, continuous acoustic information into discrete representations. Studies in the visual domain have identified a rule-based learning system that learns and reasons via a hypothesis-testing process that requires working memory and executive attention. The rule-based learning system in vision shows a protracted development, reflecting the influence of maturing prefrontal function on visual categorization. The aim of the current study was twofold: (a) to examine the developmental trajectory of rule-based auditory category learning from childhood through adolescence and into early adulthood and (b) to examine the extent to which individual differences in rule-based category learning relate to individual differences in executive function. A sample of 60 participants with normal hearing-20 children (age range=7-12years), 21 adolescents (age range=13-19years), and 19 young adults (age range=20-23years)-learned to categorize novel dynamic "ripple" sounds using trial-by-trial feedback. The spectrotemporally modulated ripple sounds are considered the auditory equivalent of the well-studied "Gabor" patches in the visual domain. Results reveal that auditory categorization accuracy improved with age, with young adults outperforming children and adolescents. Computational modeling analyses indicated that the use of the task-optimal strategy (i.e., a conjunctive rule-based learning strategy) improved with age. Notably, individual differences in executive flexibility significantly predicted auditory category learning success. The current findings demonstrate a protracted development of rule-based auditory categorization. The results further suggest that executive flexibility coupled with perceptual processes play important roles in successful rule-based auditory category learning.

Compensatory processing during rule-based category learning in older adults

Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.

The time course of explicit and implicit categorization

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization.

Dissociation of category-learning systems via brain potentials

Behavioral, neuropsychological, and neuroimaging evidence has suggested that categories can often be learned via either an explicit rule-based (RB) mechanism critically dependent on medial temporal and prefrontal brain regions, or via an implicit information-integration (II) mechanism relying on the basal ganglia. In this study, participants viewed sine-wave gratings (Gabor patches) that varied on two dimensions and learned to categorize them via trial-by-trial feedback. Two different stimulus distributions were used; one was intended to encourage an explicit RB process and the other an implicit II process. We monitored brain activity with scalp electroencephalography (EEG) while each participant: (1) passively observed stimuli represented of both distributions; (2) categorized stimuli from one distribution, and, 1 week later; (3) categorized stimuli from the other distribution. Categorization accuracy was similar for the two distributions. Subtractions of Event-Related Potentials (ERPs) for correct and incorrect trials were used to identify neural differences in RB and II categorization processes. We identified an occipital brain potential that was differentially modulated by categorization condition accuracy at an early latency (150-250 ms), likely reflecting the degree of holistic processing. A stimulus-locked Late Positive Complex (LPC) associated with explicit memory updating was modulated by accuracy in the RB, but not the II task. Likewise, a feedback-locked P300 ERP associated with expectancy was correlated with performance only in the RB, but not the II condition. These results provide additional evidence for distinct brain mechanisms supporting RB vs. implicit II category learning and use.

Ego depletion interferes with rule-defined category learning but not non-rule-defined category learning

Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants’ executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory.

Learning categories via rules and similarity: comparing adults and children

Two experiments explored the different strategies used by children and adults when learning new perceptual categories. Participants were asked to learn a set of categories for which both a single-feature rule and overall similarity would allow for perfect performance. Other rules allowed for suboptimal performance. Transfer stimuli (Experiments 1 and 2) and single features (Experiment 2) were presented after training to help determine how the categories were learned. In both experiments, we found that adults made significantly more optimal rule-based responses to the test stimuli than children. Children showed a variety of categorization styles, with a few relying on the optimal rules, many relying on suboptimal single-feature rules, and only a few relying on overall family resemblance. We interpret these results within a multiple systems framework, and we argue that children show the pattern they do because they lack the necessary cognitive resources to fully engage in hypothesis testing, rule selection, and verbally mediated category learning.

Drift in children's categories: when experienced distributions conflict with prior learning

Psychological intuitions about natural category structure do not always correspond to the true structure of the world. The current study explores young children's responses to conflict between intuitive structure and authoritative feedback using a semi-supervised learning (Zhu et al., 2007) paradigm. In three experiments, 160 children between the ages of 4 and 8 learned a one-dimensional decision criterion for distinguishing yummy and yucky 'alien fruits'. They then categorized a large number of new fruits without corrective feedback. The distribution of the new fruits was manipulated such that the natural boundary in the stimuli did not always correspond to the learned boundary. Children changed their decision criteria to reflect the structure of the new stimuli, effectively unlearning the original boundary. Younger children were especially swayed by the distributional information, being relatively insensitive to feedback that the original non-natural boundary was, in fact, still correct. Results are discussed in terms of children's ability to selectively attend to specific information (i.e. feedback vs. distribution), and their interests in forming generally useful representations of experience.

Continuous executive function disruption interferes with application of an information integration categorization strategy

Category learning is often characterized as being supported by two separate learning systems. A verbal system learns rule-defined (RD) categories that can be described using a verbal rule and relies on executive functions (EFs) to learn via hypothesis testing. A nonverbal system learns non-rule-defined (NRD) categories that cannot be described by a verbal rule and uses automatic, procedural learning. The verbal system is dominant in that adults tend to use it during initial learning but may switch to the nonverbal system when the verbal system is unsuccessful. The nonverbal system has traditionally been thought to operate independently of EFs, but recent studies suggest that EFs may play a role in the nonverbal system-specifically, to facilitate the transition away from the verbal system. Accordingly, continuously interfering with EFs during the categorization process, so that EFs are never fully available to facilitate the transition, may be more detrimental to the nonverbal system than is temporary EF interference. Participants learned an NRD or an RD category while EFs were untaxed, taxed temporarily, or taxed continuously. When EFs were continuously taxed during NRD categorization, participants were less likely to use a nonverbal categorization strategy than when EFs were temporarily taxed, suggesting that when EFs were unavailable, the transition to the nonverbal system was hindered. For the verbal system, temporary and continuous interference had similar effects on categorization performance and on strategy use, illustrating that EFs play an important but different role in each of the category-learning systems.

Toward a dual-learning systems model of speech category learning

More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article, we describe a neurobiologically constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, unidimensional rules to more complex, reflexive, multi-dimensional rules. In a second application, we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions.

Rule-based and information-integration perceptual category learning in children with attention-deficit/hyperactivity disorder

OBJECTIVE

Suboptimal functioning of the basal ganglia is implicated in attention-deficit/hyperactivity disorder (ADHD). These structures are important to the acquisition of associative knowledge, leading some to theorize that associative learning deficits might be expected, despite the fact that most extant research in ADHD has focused on effortful control. We present 2 studies that examined the acquisition of explicit rule-based (RB) and associative information integration (II) category learning among school-age children with ADHD.

METHOD AND RESULTS

In Study 1, we found deficits in both RB and II category learning tasks among children with ADHD (n = 81) versus controls (n = 42). Children with ADHD tended to sort by the more salient but irrelevant dimension (in the RB paradigm) and were unable to acquire a consistent sorting strategy (in the II paradigm). To disentangle whether the deficit was localized to II category learning versus a generalized inability to consider more than 1 stimulus dimension, in Study 2 children completed a conjunctive RB paradigm that required consideration of 2 stimulus dimensions. Children with ADHD (n = 50) continued to underperform controls (n = 33).

CONCLUSIONS

Results provide partial support for neurocognitive developmental theories of ADHD that suggest that associative learning deficits should be found, and highlight the importance of using analytic approaches that go beyond asking whether an ADHD-related deficit exists to why such deficits exist.

Prior experience with negative spectral correlations promotes information integration during auditory category learning

Complex sounds vary along a number of acoustic dimensions. These dimensions may exhibit correlations that are familiar to listeners due to their frequent occurrence in natural sounds-namely, speech. However, the precise mechanisms that enable the integration of these dimensions are not well understood. In this study, we examined the categorization of novel auditory stimuli that differed in the correlations of their acoustic dimensions, using decision bound theory. Decision bound theory assumes that stimuli are categorized on the basis of either a single dimension (rule based) or the combination of more than one dimension (information integration) and provides tools for assessing successful integration across multiple acoustic dimensions. In two experiments, we manipulated the stimulus distributions such that in Experiment 1, optimal categorization could be accomplished by either a rule-based or an information integration strategy, while in Experiment 2, optimal categorization was possible only by using an information integration strategy. In both experiments, the pattern of results demonstrated that unidimensional strategies were strongly preferred. Listeners focused on the acoustic dimension most closely related to pitch, suggesting that pitch-based categorization was given preference over timbre-based categorization. Importantly, in Experiment 2, listeners also relied on a two-dimensional information integration strategy, if there was immediate feedback. Furthermore, this strategy was used more often for distributions defined by a negative spectral correlation between stimulus dimensions, as compared with distributions with a positive correlation. These results suggest that prior experience with such correlations might shape short-term auditory category learning.

Rule-based category learning in Down syndrome

Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III ( Woodock, McGrew, & Mather, 2001 ). In regression-based analyses, DS and ID groups performed below the level expected for their nonverbal ability. In cross-sectional developmental trajectory analyses, results depended on the task. On the MCST, the DS and ID groups were similar to the TD group. On the Concept Formation test, the DS group had slower cross-sectional change than the other 2 groups. Category learning may be an area of difficulty for those with ID, but task-related factors may affect trajectories for youths with DS.

Preschoolers can form abstract rule representations regardless of cognitive flexibility

The abstractness of rule representations in the pre-switch phase of the Dimensional Change Card Sorting (DCCS) task was studied by letting 3- and 4-year-old children perform a standard DCCS task and a separate generalization task. In the generalization task, children were asked to generalize their sorting rules to novel stimuli in one of three conditions. In the relevant change condition, values of the relevant dimension changed; in the irrelevant change condition, values of the irrelevant dimension changed; and in the total change condition, values of both dimensions changed. All children showed high performance on the generalization task in the relevant change condition, implying an abstract rule representation at the level of dimensions ("same colors go together"). Performance in the relevant change condition was significantly better (and faster) than performance in the other two conditions. Children with high cognitive flexibility (switchers on the DCCS task) more often switched their attention to the irrelevant dimension in the generalization task only if values of the irrelevant dimension changed. Children with low cognitive flexibility (perseverators) were more often inconsistent in their sorting on the generalization task if values of both dimensions changed. The difference in performance on the DCCS task between switchers and perseverators seems to result from the processes that operate on the learned sorting rules and not from the abstractness of the rule representations children have.

Rule-based category learning in children: the role of age and executive functioning

Rule-based category learning was examined in 4–11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning.

Posterror slowing predicts rule-based but not information-integration category learning

We examined whether error monitoring, operationalized as the degree to which individuals slow down after committing an error (i.e., posterror slowing), is differentially important in the learning of rule-based versus information-integration category structures. Rule-based categories are most efficiently solved through the application of an explicit verbal strategy (e.g., "sort by color"). In contrast, information-integration categories are believed to be learned in a trial-by-trial, associative manner. Our results indicated that posterror slowing predicts enhanced rule-based but not information-integration category learning. Implications for multiple category-learning systems are discussed.

Developing representations of compound stimuli

Classification based on multiple dimensions of stimuli is usually associated with similarity-based representations, whereas uni-dimensional classifications are associated with rule-based representations. This paper studies classification of stimuli and category representations in school-aged children and adults when learning to categorize compound, multi-dimensional stimuli. Stimuli were such that both similarity-based and rule-based representations would lead to correct classification. This allows testing whether children have a bias for formation of similarity-based representations. The results are at odds with this expectation. Children use both uni-dimensional and multi-dimensional classification, and the use of both strategies increases with age. Multi-dimensional classification is best characterized as resulting from an analytic strategy rather than from procedural processing of overall-similarity. The conclusion is that children are capable of using complex rule-based categorization strategies that involve the use of multiple features of the stimuli. The main developmental change concerns the efficiency and consistency of the explicit learning system.