Impaired and Spared Auditory Category Learning in Developmental Dyslexia.

Categorization has a deep impact on behavior, but whether category learning is served by a single system or multiple systems remains debated. Here, we designed two well-equated nonspeech auditory category learning challenges to draw on putative procedural (information-integration) versus declarative (rule-based) learning systems among adult Hebrew-speaking control participants and individuals with dyslexia, a language disorder that has been linked to a selective disruption in the procedural memory system and in which phonological deficits are ubiquitous. We observed impaired information-integration category learning and spared rule-based category learning in the dyslexia group compared with the neurotypical group. Quantitative model-based analyses revealed reduced use of, and slower shifting to, optimal procedural-based strategies in dyslexia with hypothesis-testing strategy use on par with control participants. The dissociation is consistent with multiple category learning systems and points to the possibility that procedural learning inefficiencies across categories defined by complex, multidimensional exemplars may result in difficulty in phonetic category acquisition in dyslexia.

The nature of non-native speech sound representations.

Most current theories and models of second language speech perception are grounded in the notion that learners acquire speech sound categories in their target language. In this paper, this classic idea in speech perception is revisited, given that clear evidence for formation of such categories is lacking in previous research. To understand the debate on the nature of speech sound representations in a second language, an operational definition of "category" is presented, and the issues of categorical perception and current theories of second language learning are reviewed. Following this, behavioral and neuroimaging evidence for and against acquisition of categorical representations is described. Finally, recommendations for future work are discussed. The paper concludes with a recommendation for integration of behavioral and neuroimaging work and theory in this area.

Neural dynamics underlying the acquisition of distinct auditory category structures.

Despite the multidimensional and temporally fleeting nature of auditory signals we quickly learn to assign novel sounds to behaviorally relevant categories. The neural systems underlying the learning and representation of novel auditory categories are far from understood. Current models argue for a rigid specialization of hierarchically organized core regions that are fine-tuned to extracting and mapping relevant auditory dimensions to meaningful categories. Scaffolded within a dual-learning systems approach, we test a competing hypothesis: the spatial and temporal dynamics of emerging auditory-category representations are not driven by the underlying dimensions but are constrained by category structure and learning strategies. To test these competing models, we used functional Magnetic Resonance Imaging (fMRI) to assess representational dynamics during the feedback-based acquisition of novel non-speech auditory categories with identical dimensions but differing category structures: rule-based (RB) categories, hypothesized to involve an explicit sound-to-rule mapping network, and information integration (II) based categories, involving pre-decisional integration of dimensions via a procedural-based sound-to-reward mapping network. Adults were assigned to either the RB (n = 30, 19 females) or II (n = 30, 22 females) learning tasks. Despite similar behavioral learning accuracies, learning strategies derived from computational modeling and involvements of corticostriatal systems during feedback processing differed across tasks. Spatiotemporal multivariate representational similarity analysis revealed an emerging representation within an auditory sensory-motor pathway exclusively for the II learning task, prominently involving the superior temporal gyrus (STG), inferior frontal gyrus (IFG), and posterior precentral gyrus. In contrast, the RB learning task yielded distributed neural representations within regions involved in cognitive-control and attentional processes that emerged at different time points of learning. Our results unequivocally demonstrate that auditory learners' neural systems are highly flexible and show distinct spatial and temporal patterns that are not dimension-specific but reflect underlying category structures and learning strategies.

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.

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.

Individual differences in working memory impact the trajectory of non-native speech category learning.

What is the role of working memory over the course of non-native speech category learning? Prior work has predominantly focused on how working memory might influence learning assessed at a single timepoint. Here, we substantially extend this prior work by examining the role of working memory on speech learning performance over time (i.e., over several months) and leverage a multifaceted approach that provides key insights into how working memory influences learning accuracy, maintenance of knowledge over time, generalization ability, and decision processes. We found that the role of working memory in non-native speech learning depends on the timepoint of learning and whether individuals learned the categories at all. Among learners, across all stages of learning, working memory was associated with higher accuracy as well as faster and slightly more cautious decision making. Further, while learners and non-learners did not have substantially different working memory performance, learners had faster evidence accumulation and more cautious decision thresholds throughout all sessions. Working memory may enhance learning by facilitating rapid category acquisition in initial stages and enabling faster and slightly more careful decision-making strategies that may reduce the overall effort needed to learn. Our results have important implications for developing interventions to improve learning in naturalistic language contexts.

Stable, flexible, common, and distinct behaviors support rule-based and information-integration category learning.

The ability to organize variable sensory signals into discrete categories is a fundamental process in human cognition thought to underlie many real-world learning problems. Decades of research suggests that two learning systems may support category learning and that categories with different distributional structures (rule-based, information-integration) optimally rely on different learning systems. However, it remains unclear how the same individual learns these different categories and whether the behaviors that support learning success are common or distinct across different categories. In two experiments, we investigate learning and develop a taxonomy of learning behaviors to investigate which behaviors are stable or flexible as the same individual learns rule-based and information-integration categories and which behaviors are common or distinct to learning success for these different types of categories. We found that some learning behaviors are stable in an individual across category learning tasks (learning success, strategy consistency), while others are flexibly task-modulated (learning speed, strategy, stability). Further, success in rule-based and information-integration category learning was supported by both common (faster learning speeds, higher working memory ability) and distinct factors (learning strategies, strategy consistency). Overall, these results demonstrate that even with highly similar categories and identical training tasks, individuals dynamically adjust some behaviors to fit the task and success in learning different kinds of categories is supported by both common and distinct factors. These results illustrate a need for theoretical perspectives of category learning to include nuances of behavior at the level of an individual learner.

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 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).

A neural network model of the effect of prior experience with regularities on subsequent category learning.

Categories are often structured by the similarities of instances within the category defined across dimensions or features. Researchers typically assume that there is a direct, linear relationship between the physical input dimensions across which category exemplars are defined and the psychological representation of these dimensions. However, this assumption is not always warranted. Through a set of simulations, we demonstrate that the psychological representations of input dimensions developed through long-term prior experience can place very strong constraints on category learning. We compare the model's behavior to auditory, visual, and cross-modal human category learning and make conclusions regarding the nature of the psychological representations of the dimensions in those studies. These simulations support the conclusion that the nature of psychological representations of input dimensions is a critical aspect to understanding the mechanisms underlying category learning.

Long-term priors constrain category learning in the context of short-term statistical regularities.

Cognitive systems face a constant tension of maintaining existing representations that have been fine-tuned to long-term input regularities and adapting representations to meet the needs of short-term input that may deviate from long-term norms. Systems must balance the stability of long-term representations with plasticity to accommodate novel contexts. We investigated the interaction between perceptual biases or priors acquired across the long-term and sensitivity to statistical regularities introduced in the short-term. Participants were first passively exposed to short-term acoustic regularities and then learned categories in a supervised training task that either conflicted or aligned with long-term perceptual priors. We found that the long-term priors had robust and pervasive impact on categorization behavior. In contrast, behavior was not influenced by the nature of the short-term passive exposure. These results demonstrate that perceptual priors place strong constraints on the course of learning and that short-term passive exposure to acoustic regularities has limited impact on directing subsequent category learning.

Auditory and visual category learning in musicians and nonmusicians.

Across three experiments, we compare the ability of amateur musicians and nonmusicians in learning artificial auditory and visual categories that can be described as either rule-based (RB) or information-integration (II) category structures. RB categories are optimally learned using a reflective reasoning process, whereas II categories are optimally learned by integrating information from two stimulus dimensions at a reflexive, predecisional processing stage. We found that musicians have selective advantages for learning auditory RB categories, specifically when they are instructed about the dimensions that define the categories. In Experiment 1, musicians enrolled in a music college demonstrated advantages over nonmusicians in learning auditory RB categories defined on frequency and duration dimensions but did not demonstrate differences in learning auditory II categories or either visual RB or II categories. In Experiment 2, a broader online sample of musicians who were not instructed about the dimensions did not demonstrate any advantage in auditory or visual learning. In Experiment 3, an online sample of musicians when given dimension instructions demonstrated early advantages over nonmusicians for auditory RB but not visual RB categories. Musicians do not demonstrate a global categorization advantage. Musicians' category learning advantage is limited to their modality of expertise, is enhanced with dimension instructions, and is specific to categories that can be described with verbalizable rules. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The representational glue for incidental category learning is alignment with task-relevant behavior.

Category learning is fundamental to cognition, but little is known about how it proceeds in real-world environments when learners do not have instructions to search for category-relevant information, do not make overt category decisions, and do not experience direct feedback. Prior research demonstrates that listeners can acquire task-irrelevant auditory categories incidentally as they engage in primarily visuomotor tasks. The current study examines the factors that support this incidental category learning. Three experiments systematically manipulated the relationship of four novel auditory categories with a consistent visual feature (color or location) that informed a simple behavioral keypress response regarding the visual feature. In both an in-person experiment and two online replications with extensions, incidental auditory category learning occurred reliably when category exemplars consistently aligned with visuomotor demands of the primary task, but not when they were misaligned. The presence of an additional irrelevant visual feature that was uncorrelated with the primary task demands neither enhanced nor harmed incidental learning. By contrast, incidental learning did not occur when auditory categories were aligned consistently with one visual feature, but the motor response in the primary task was aligned with another, category-unaligned visual feature. Moreover, category learning did not reliably occur across passive observation or when participants made a category-nonspecific, generic motor response. These findings show that incidental learning of categories is strongly mediated by the character of coincident behavior. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Working memory relates to individual differences in speech category learning: Insights from computational modeling and pupillometry.

Across two experiments, we examine the relationship between individual differences in working memory (WM) and the acquisition of non-native speech categories in adulthood. While WM is associated with individual differences in a variety of learning tasks, successful acquisition of speech categories is argued to be contingent on WM-independent procedural-learning mechanisms. Thus, the role of WM in speech category learning is unclear. In Experiment 1, we show that individuals with higher WM acquire non-native speech categories faster and to a greater extent than those with lower WM. In Experiment 2, we replicate these results and show that individuals with higher WM use more optimal, procedural-based learning strategies and demonstrate more distinct speech-evoked pupillary responses for correct relative to incorrect trials. We propose that higher WM may allow for greater stimulus-related attention, resulting in more robust representations and optimal learning strategies. We discuss implications for neurobiological models of speech category learning.

Comparing perceptual category learning across modalities in the same individuals.

Category learning is a fundamental process in human cognition that spans the senses. However, much still remains unknown about the mechanisms supporting learning in different modalities. In the current study, we directly compared auditory and visual category learning in the same individuals. Thirty participants (22 F; 18-32 years old) completed two unidimensional rule-based category learning tasks in a single day - one with auditory stimuli and another with visual stimuli. We replicated the results in a second experiment with a larger online sample (N = 99, 45 F, 18-35 years old). The categories were identically structured in the two modalities to facilitate comparison. We compared categorization accuracy, decision processes as assessed through drift-diffusion models, and the generalizability of resulting category representation through a generalization test. We found that individuals learned auditory and visual categories to similar extents and that accuracies were highly correlated across the two tasks. Participants had similar evidence accumulation rates in later learning, but early on had slower rates for visual than auditory learning. Participants also demonstrated differences in the decision thresholds across modalities. Participants had more categorical generalizable representations for visual than auditory categories. These results suggest that some modality-general cognitive processes support category learning but also suggest that the modality of the stimuli may also affect category learning behavior and outcomes.

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.

Task and distribution sampling affect auditory category learning.

There is substantial evidence that two distinct learning systems are engaged in category learning. One is principally engaged when learning requires selective attention to a single dimension (rule-based), and the other is drawn online by categories requiring integration across two or more dimensions (information-integration). This distinction has largely been drawn from studies of visual categories learned via overt category decisions and explicit feedback. Recent research has extended this model to auditory categories, the nature of which introduces new questions for research. With the present experiment, we addressed the influences of incidental versus overt training and category distribution sampling on learning information-integration and rule-based auditory categories. The results demonstrate that the training task influences category learning, with overt feedback generally outperforming incidental feedback. Additionally, distribution sampling (probabilistic or deterministic) and category type (information-integration or rule-based) both affect how well participants are able to learn. Specifically, rule-based categories are learned equivalently, regardless of distribution sampling, whereas information-integration categories are learned better with deterministic than with probabilistic sampling. The interactions of distribution sampling, category type, and kind of feedback impacted category-learning performance, but these interactions have not yet been integrated into existing category-learning models. These results suggest new dimensions for understanding category learning, inspired by the real-world properties of auditory categories.

Listening Into 2030 Workshop: An Experiment in Envisioning the Future of Hearing and Communication Science.

Here we report the methods and output of a workshop examining possible futures of speech and hearing science out to 2030. Using a design thinking approach, a range of human-centered problems in communication were identified that could provide the motivation for a wide range of research. Nine main research programs were distilled and are summarized: (a) measuring brain and other physiological parameters, (b) auditory and multimodal displays of information, (c) auditory scene analysis, (d) enabling and understanding shared auditory virtual spaces, (e) holistic approaches to health management and hearing impairment, (f) universal access to evolving and individualized technologies, (g) biological intervention for hearing dysfunction, (h) understanding the psychosocial interactions with technology and other humans as mediated by technology, and (i) the impact of changing models of security and privacy. The design thinking approach attempted to link the judged level of importance of different research areas to the "end in mind" through empathy for the real-life problems embodied in the personas created during the workshop.