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.

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.

Bayesian Semiparametric Longitudinal Inverse-Probit Mixed Models for Category Learning.

Understanding how the adult human brain learns novel categories is an important problem in neuroscience. Drift-diffusion models are popular in such contexts for their ability to mimic the underlying neural mechanisms. One such model for gradual longitudinal learning was recently developed in Paulon et al. (J Am Stat Assoc 116:1114-1127, 2021). In practice, category response accuracies are often the only reliable measure recorded by behavioral scientists to describe human learning. Category response accuracies are, however, often the only reliable measure recorded by behavioral scientists to describe human learning. To our knowledge, however, drift-diffusion models for such scenarios have never been considered in the literature before. To address this gap, in this article, we build carefully on Paulon et al. (J Am Stat Assoc 116:1114-1127, 2021), but now with latent response times integrated out, to derive a novel biologically interpretable class of 'inverse-probit' categorical probability models for observed categories alone. However, this new marginal model presents significant identifiability and inferential challenges not encountered originally for the joint model in Paulon et al. (J Am Stat Assoc 116:1114-1127, 2021). We address these new challenges using a novel projection-based approach with a symmetry-preserving identifiability constraint that allows us to work with conjugate priors in an unconstrained space. We adapt the model for group and individual-level inference in longitudinal settings. Building again on the model's latent variable representation, we design an efficient Markov chain Monte Carlo algorithm for posterior computation. We evaluate the empirical performance of the method through simulation experiments. The practical efficacy of the method is illustrated in applications to longitudinal tone learning studies.

Examining cortical tracking of the speech envelope in post-stroke aphasia.

Introduction: People with aphasia have been shown to benefit from rhythmic elements for language production during aphasia rehabilitation. However, it is unknown whether rhythmic processing is associated with such benefits. Cortical tracking of the speech envelope (CTenv) may provide a measure of encoding of speech rhythmic properties and serve as a predictor of candidacy for rhythm-based aphasia interventions. Methods: Electroencephalography was used to capture electrophysiological responses while Spanish speakers with aphasia (n = 9) listened to a continuous speech narrative (audiobook). The Temporal Response Function was used to estimate CTenv in the delta (associated with word- and phrase-level properties), theta (syllable-level properties), and alpha bands (attention-related properties). CTenv estimates were used to predict aphasia severity, performance in rhythmic perception and production tasks, and treatment response in a sentence-level rhythm-based intervention. Results: CTenv in delta and theta, but not alpha, predicted aphasia severity. Neither CTenv in delta, alpha, or theta bands predicted performance in rhythmic perception or production tasks. Some evidence supported that CTenv in theta could predict sentence-level learning in aphasia, but alpha and delta did not. Conclusion: CTenv of the syllable-level properties was relatively preserved in individuals with less language impairment. In contrast, higher encoding of word- and phrase-level properties was relatively impaired and was predictive of more severe language impairments. CTenv and treatment response to sentence-level rhythm-based interventions need to be further investigated.

Transcutaneous Auricular Vagus Nerve Stimulation Modulates Performance but Not Pupil Size During Nonnative Speech Category Learning.

PURPOSE: Subthreshold transcutaneous auricular vagus nerve stimulation (taVNS) synchronized with behavioral training can selectively enhance nonnative speech category learning in adults. Prior work has demonstrated that behavioral performance increases when taVNS is paired with easier-to-learn Mandarin tone categories in native English listeners, relative to when taVNS is paired with harder-to-learn Mandarin tone categories or without taVNS. Mechanistically, this temporally precise plasticity has been attributed to noradrenergic modulation. However, prior work did not specifically utilize methodologies that indexed noradrenergic modulation and, therefore, was unable to explicitly test this hypothesis. Our goal for this study was to use pupillometry to gain mechanistic insights into taVNS behavioral effects. METHOD: Thirty-eight participants learned to categorize Mandarin tones while pupillometry was recorded. In a double-blinded design, participants were divided into two taVNS groups that, as in the prior study, differed according to whether taVNS was paired with easier-to-learn tones or harder-to-learn tones. Learning performance and pupillary responses were measured using linear mixed-effects models. RESULTS: We found that taVNS did not have any tone-specific or group behavioral or pupillary effects. However, in an exploratory analysis, we observed that taVNS did lead to faster rates of learning on trials paired with stimulation, particularly for those who were stimulated at lower amplitudes. CONCLUSIONS: Our results suggest that pupillary responses may not be a reliable marker of locus coeruleus-norepinephrine system activity in humans. However, future research should systematically examine the effects of stimulation amplitude on both behavior and pupillary responses. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24036666.

Cortical Tracking of Continuous Speech Under Bimodal Divided Attention.

Speech processing often occurs amid competing inputs from other modalities, for example, listening to the radio while driving. We examined the extent to which dividing attention between auditory and visual modalities (bimodal divided attention) impacts neural processing of natural continuous speech from acoustic to linguistic levels of representation. We recorded electroencephalographic (EEG) responses when human participants performed a challenging primary visual task, imposing low or high cognitive load while listening to audiobook stories as a secondary task. The two dual-task conditions were contrasted with an auditory single-task condition in which participants attended to stories while ignoring visual stimuli. Behaviorally, the high load dual-task condition was associated with lower speech comprehension accuracy relative to the other two conditions. We fitted multivariate temporal response function encoding models to predict EEG responses from acoustic and linguistic speech features at different representation levels, including auditory spectrograms and information-theoretic models of sublexical-, word-form-, and sentence-level representations. Neural tracking of most acoustic and linguistic features remained unchanged with increasing dual-task load, despite unambiguous behavioral and neural evidence of the high load dual-task condition being more demanding. Compared to the auditory single-task condition, dual-task conditions selectively reduced neural tracking of only some acoustic and linguistic features, mainly at latencies >200 ms, while earlier latencies were surprisingly unaffected. These findings indicate that behavioral effects of bimodal divided attention on continuous speech processing occur not because of impaired early sensory representations but likely at later cognitive processing stages. Crossmodal attention-related mechanisms may not be uniform across different speech processing levels.

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.

The relationship between sentence intelligibility, band importance, and signal covariance.

The present study investigates the relationship between sentence intelligibility, band importance, and patterns of spectro-temporal covariation between frequency bands. Sixteen listeners transcribed sentences acoustically degraded to 5, 8, or 15 frequency bands. Half of the sentences retained the frequency bands that captured more signal covariance. The other half retained the bands accounting for less signal covariance. Sentence intelligibility was significantly higher in the high-covariance condition. Critically, this finding was predicted by differences in band importance across reconstructed sentences. These findings provide a mechanistic relationship between the contributions of signal covariance and band importance to sentence intelligibility.

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).

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.

Language experience during the sensitive period narrows infants' sensory encoding of lexical tones-Music intervention reverses it.

The sensitive period for phonetic learning (6∼12 months), evidenced by improved native speech processing and declined non-native speech processing, represents an early milestone in language acquisition. We examined the extent that sensory encoding of speech is altered by experience during this period by testing two hypotheses: (1) early sensory encoding of non-native speech declines as infants gain native-language experience, and (2) music intervention reverses this decline. We longitudinally measured the frequency-following response (FFR), a robust indicator of early sensory encoding along the auditory pathway, to a Mandarin lexical tone in 7- and 11-months-old monolingual English-learning infants. Infants received either no intervention (language-experience group) or music intervention (music-intervention group) randomly between FFR recordings. The language-experience group exhibited the expected decline in FFR pitch-tracking accuracy to the Mandarin tone, while the music-intervention group did not. Our results support both hypotheses and demonstrate that both language and music experiences alter infants' speech encoding.

Neural responses in human superior temporal cortex support coding of voice representations.

The ability to recognize abstract features of voice during auditory perception is an intricate feat of human audition. For the listener, this occurs in near-automatic fashion to seamlessly extract complex cues from a highly variable auditory signal. Voice perception depends on specialized regions of auditory cortex, including superior temporal gyrus (STG) and superior temporal sulcus (STS). However, the nature of voice encoding at the cortical level remains poorly understood. We leverage intracerebral recordings across human auditory cortex during presentation of voice and nonvoice acoustic stimuli to examine voice encoding at the cortical level in 8 patient-participants undergoing epilepsy surgery evaluation. We show that voice selectivity increases along the auditory hierarchy from supratemporal plane (STP) to the STG and STS. Results show accurate decoding of vocalizations from human auditory cortical activity even in the complete absence of linguistic content. These findings show an early, less-selective temporal window of neural activity in the STG and STS followed by a sustained, strongly voice-selective window. Encoding models demonstrate divergence in the encoding of acoustic features along the auditory hierarchy, wherein STG/STS responses are best explained by voice category and acoustics, as opposed to acoustic features of voice stimuli alone. This is in contrast to neural activity recorded from STP, in which responses were accounted for by acoustic features. These findings support a model of voice perception that engages categorical encoding mechanisms within STG and STS to facilitate feature extraction.

Sleep affects higher-level categorization of speech sounds, but not frequency encoding.

Sleep can increase consolidation of new knowledge and skills. It is less clear whether sleep plays a role in other aspects of experience-dependent neuroplasticity, which underlie important human capabilities such as spoken language processing. Theories of sensory learning differ in their predictions; some imply rapid learning at early sensory levels, while other propose a slow, progressive timecourse such that higher-level categorical representations guide immediate, novice learning, while lower-level sensory changes do not emerge until later stages. In this study, we investigated the role of sleep across both behavioural and physiological indices of auditory neuroplasticity. Forty healthy young human adults (23 female) who did not speak a tonal language participated in the study. They learned to categorize non-native Mandarin lexical tones using a sound-to-category training paradigm, and were then randomly assigned to a Nap or Wake condition. Polysomnographic data were recorded to quantify sleep during a 3 h afternoon nap opportunity, or equivalent period of quiet wakeful activity. Measures of behavioural performance accuracy revealed a significant improvement in learning the sound-to-category training paradigm between Nap and Wake groups. Conversely, a neural index of fine sound encoding fidelity of speech sounds known as the frequency-following response (FFR) suggested no change due to sleep, and a null model was supported, using Bayesian statistics. Together, these results support theories that propose a slow, progressive and hierarchical timecourse for sensory learning. Sleep's effect may play the biggest role in the higher-level learning, although contributions to more protracted processes of plasticity that exceed the study duration cannot be ruled out.

Continuous speech tracking in bilinguals reflects adaptation to both language and noise.

Listeners regularly comprehend continuous speech despite noisy conditions. Previous studies show that neural tracking of speech degrades under noise, predicts comprehension, and increases for non-native listeners. We test the hypothesis that listeners similarly increase tracking for both L2 and noisy L1 speech, after adjusting for comprehension. Twenty-four Chinese-English bilinguals underwent EEG while listening to one hour of an audiobook, mixed with three levels of noise, in Mandarin and English and answered comprehension questions. We estimated tracking of the speech envelope in EEG for each one-minute segment using the multivariate temporal response function (mTRF). Contrary to our prediction, L2 tracking was significantly lower than L1, while L1 tracking significantly increased with noise maskers without reducing comprehension. However, greater L2 proficiency was positively associated with greater L2 tracking. We discuss how studies of speech envelope tracking using noise and bilingualism might be reconciled through a focus on exerted rather than demanded effort.

The emergence of idiosyncratic patterns in the frequency-following response during the first year of life.

The frequency-following response (FFR) is a scalp-recorded signal that reflects phase-locked activity from neurons across the auditory system. In addition to capturing information about sounds, the FFR conveys biometric information, reflecting individual differences in auditory processing. To investigate the development of FFR biometric patterns, we trained a pattern recognition model to recognize infants (N = 16) from FFRs collected at 7 and 11 months. Model recognition scores were used to index the robustness of FFR biometric patterns at each time. Results showed better recognition scores at 11 months, demonstrating the emergence of robust FFR idiosyncratic patterns during this first year of life.

Principal component decomposition of acoustic and neural representations of time-varying pitch reveals adaptive efficient coding of speech covariation patterns.

Understanding the effects of statistical regularities on speech processing is a central issue in auditory neuroscience. To investigate the effects of distributional covariance on the neural processing of speech features, we introduce and validate a novel approach: decomposition of time-varying signals into patterns of covariation extracted with Principal Component Analysis. We used this decomposition to assay the sensory representation of pitch covariation patterns in native Chinese listeners and non-native learners of Mandarin Chinese tones. Sensory representations were examined using the frequency-following response, a far-field potential that reflects phase-locked activity from neural ensembles along the auditory pathway. We found a more efficient representation of the covariation patterns that accounted for more redundancy in the form of distributional covariance. Notably, long-term language and short-term training experiences enhanced the sensory representation of these covariation patterns.

Structural Connectivity of Human Inferior Colliculus Subdivisions Using in vivo and post mortem Diffusion MRI Tractography.

Inferior colliculus (IC) is an obligatory station along the ascending auditory pathway that also has a high degree of top-down convergence via efferent pathways, making it a major computational hub. Animal models have attributed critical roles for the IC in in mediating auditory plasticity, egocentric selection, and noise exclusion. IC contains multiple functionally distinct subdivisions. These include a central nucleus that predominantly receives ascending inputs and external and dorsal nuclei that receive more heterogeneous inputs, including descending and multisensory connections. Subdivisions of human IC have been challenging to identify and quantify using standard brain imaging techniques such as MRI, and the connectivity of each of these subnuclei has not been identified in the human brain. In this study, we estimated the connectivity of human IC subdivisions with diffusion MRI (dMRI) tractography, using both anatomical-based seed analysis as well as unsupervised k-means clustering. We demonstrate sensitivity of tractography to overall IC connections in both high resolution post mortem and in vivo datasets. k-Means clustering of the IC streamlines in both the post mortem and in vivo datasets generally segregated streamlines based on their terminus beyond IC, such as brainstem, thalamus, or contralateral IC. Using fine-grained anatomical segmentations of the major IC subdivisions, the post mortem dataset exhibited unique connectivity patterns from each subdivision, including commissural connections through dorsal IC and lateral lemniscal connections to central and external IC. The subdivisions were less distinct in the context of in vivo connectivity, although lateral lemniscal connections were again highest to central and external IC. Overall, the unsupervised and anatomically driven methods provide converging evidence for distinct connectivity profiles for each of the IC subdivisions in both post mortem and in vivo datasets, suggesting that dMRI tractography with high quality data is sensitive to neural pathways involved in auditory processing as well as top-down control of incoming auditory information.

Non-sensory Influences on Auditory Learning and Plasticity.

Distinguishing between regular and irregular heartbeats, conversing with speakers of different accents, and tuning a guitar-all rely on some form of auditory learning. What drives these experience-dependent changes? A growing body of evidence suggests an important role for non-sensory influences, including reward, task engagement, and social or linguistic context. This review is a collection of contributions that highlight how these non-sensory factors shape auditory plasticity and learning at the molecular, physiological, and behavioral level. We begin by presenting evidence that reward signals from the dopaminergic midbrain act on cortico-subcortical networks to shape sound-evoked responses of auditory cortical neurons, facilitate auditory category learning, and modulate the long-term storage of new words and their meanings. We then discuss the role of task engagement in auditory perceptual learning and suggest that plasticity in top-down cortical networks mediates learning-related improvements in auditory cortical and perceptual sensitivity. Finally, we present data that illustrates how social experience impacts sound-evoked activity in the auditory midbrain and forebrain and how the linguistic environment rapidly shapes speech perception. These findings, which are derived from both human and animal models, suggest that non-sensory influences are important regulators of auditory learning and plasticity and are often implemented by shared neural substrates. Application of these principles could improve clinical training strategies and inform the development of treatments that enhance auditory learning in individuals with communication disorders.

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).

A Linear Superposition Model of Envelope and Frequency Following Responses May Help Identify Generators Based on Latency.

Envelope and frequency-following responses (FFRENV and FFRTFS) are scalp-recorded electrophysiological potentials that closely follow the periodicity of complex sounds such as speech. These signals have been established as important biomarkers in speech and learning disorders. However, despite important advances, it has remained challenging to map altered FFRENV and FFRTFS to altered processing in specific brain regions. Here we explore the utility of a deconvolution approach based on the assumption that FFRENV and FFRTFS reflect the linear superposition of responses that are triggered by the glottal pulse in each cycle of the fundamental frequency (F0 responses). We tested the deconvolution method by applying it to FFRENV and FFRTFS of rhesus monkeys to human speech and click trains with time-varying pitch patterns. Our analyses show that F0ENV responses could be measured with high signal-to-noise ratio and featured several spectro-temporally and topographically distinct components that likely reflect the activation of brainstem (<5 ms; 200-1000 Hz), midbrain (5-15 ms; 100-250 Hz), and cortex (15-35 ms; ~90 Hz). In contrast, F0TFS responses contained only one spectro-temporal component that likely reflected activity in the midbrain. In summary, our results support the notion that the latency of F0 components map meaningfully onto successive processing stages. This opens the possibility that pathologically altered FFRENV or FFRTFS may be linked to altered F0ENV or F0TFS and from there to specific processing stages and ultimately spatially targeted interventions.