Reduced Learning of Sound Categories in Dyslexia Is Associated with Reduced Regularity-Induced Auditory Cortex Adaptation

Neural tracking of auditory statistical regularities in adults with and without dyslexia

Listeners implicitly use statistical regularities to segment continuous sound input into meaningful units, eg transitional probabilities between syllables to segment a speech stream into separate words. Implicit learning of such statistical regularities in a novel stimulus stream is reflected in a synchronization of neural responses to the sequential stimulus structure. The present study aimed to test the hypothesis that neural tracking of the statistical stimulus structure is reduced in individuals with dyslexia who have weaker reading and spelling skills, and possibly also weaker statistical learning abilities in general, compared to healthy controls. To this end, adults with and without dyslexia were presented with continuous streams of (non-speech) tones, which were arranged into triplets, such that transitional probabilities between single tones were higher within triplets and lower between triplets. We found that the so-called Triplet Learning Index (ie the ratio of neural phase coherence at the triplet rate relative to the tone rate) was lower in adults with dyslexia compared to the control group. Moreover, a higher Triplet Learning Index was associated with better spelling skills. These results suggest that individuals with dyslexia have a rather broad deficit in processing structure in sound instead of a merely phonological deficit.

Distinct impact modes of polygenic disposition to dyslexia in the adult brain

Dyslexia is a common and partially heritable condition that affects reading ability. In a study of up to 35,231 adults, we explored the structural brain correlates of genetic disposition to dyslexia. Individual dyslexia-disposing genetic variants showed distinct patterns of association with brain structure. Independent component analysis revealed various brain networks that each had their own genomic profiles related to dyslexia susceptibility. Circuits involved in motor coordination, vision, and language were implicated. Polygenic scores for eight traits genetically correlated with dyslexia, including cognitive, behavioral, and reading-related psychometric measures, showed partial similarities to dyslexia in terms of brain-wide associations. Notably, microstructure of the internal capsule was consistently implicated across all of these genetic dispositions, while lower volume of the motor cortex was more specifically associated with dyslexia genetic disposition alone. These findings reveal genetic and neurobiological features that may contribute to dyslexia and its associations with other traits at the population level.

Perceptual anchoring: Children with dyslexia benefit less than controls from contextual repetitions in speech processing

OBJECTIVES

Individuals with dyslexia perceive and utilize statistical features in the auditory input deficiently. The present study investigates whether affected children also benefit less from repeating context tones as perceptual anchors for subsequent speech processing.

METHODS

In an event-related potential study, eleven-year-old children with dyslexia (n = 21) and without dyslexia (n = 20) heard syllable pairs, with the first syllable either receiving a constant pitch (anchor) or variable pitch (no-anchor), while second syllables were identical across conditions.

RESULTS

Children with and without dyslexia showed smaller auditory P2 responses to constant-pitch versus variable-pitch first syllables, while only control children additionally showed smaller N1 and faster P1 responses. This suggests less automatic processing of anchor repetitions in dyslexia. For the second syllables, both groups showed faster P2 responses following anchor than no-anchor first syllables, but only controls additionally showed smaller P2 responses.

CONCLUSIONS

Children with and without dyslexia show differences in anchor effects. While both groups seem to allocate less attention to speech stimuli after contextual repetitions, children with dyslexia display less facilitation in speech processing from acoustic anchors.

SIGNIFICANCE

Altered anchoring in the linguistic domain may contribute to the difficulties of individuals with dyslexia in establishing long-term representations of speech.

The shared neurobiological basis of developmental dyslexia and developmental stuttering: A meta-analysis of functional and structural MRI studies

Background

Developmental dyslexia (DD) and persistent developmental stuttering (PDS) are the most representative written and spoken language disorders, respectively, and both significantly hinder life success. Although widespread brain alterations are evident in both DD and PDS, it remains unclear to what extent these two language disorders share common neural substrates.

Methods

A systematic review and meta-analysis of task-based functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) studies of PDS and DD were conducted to explore the shared functional and anatomical alterations across these disorders.

Results

The results of fMRI studies indicated shared hypoactivation in the left inferior temporal gyrus and inferior parietal gyrus across PDS and DD compared to healthy controls. When examined separately for children and adults, we found that child participants exhibited reduced activation in the left inferior temporal gyrus, inferior parietal gyrus, precentral gyrus, middle temporal gyrus, and inferior frontal gyrus, possibly reflecting the universal causes of written and spoken language disorders. In contrast, adult participants exhibited hyperactivation in the right precentral gyrus and left cingulate motor cortex, possibly reflecting common compensatory mechanisms. Anatomically, the analysis of VBM studies revealed decreased gray matter volume in the left inferior frontal gyrus across DD and PDS, which was exclusively observed in children. Finally, meta-analytic connectivity modeling and brain-behavior correlation analyses were conducted to explore functional connectivity patterns and related cognitive functions of the brain regions commonly involved in DD and PDS.

Conclusions

This study identified concordances in brain abnormalities across DD and PDS, suggesting common neural substrates for written and spoken language disorders and providing new insights into the transdiagnostic neural signatures of language disorders.

Reduced categorical learning of faces in dyslexia

The perception of phonological categories in dyslexia is less refined than in typically developing (TD) individuals. Traditionally, this characteristic was considered unique to phonology, yet many studies showed non-phonological perceptual difficulties. Importantly, measuring the dynamics of cortical adaptation, associated with category acquisition, revealed a broadly distributed faster decay of cortical adaptation. Taken together, these observations suggest that the acquisition of perceptual categories in dyslexia may be slower across modalities. To test this, we tested adult individuals with developmental dyslexia (IDDs) and TDs on learning of two unknown faces, yielding face-specific categorization. Initial accuracy was similar in the two groups, yet practice-induced increase in accuracy was significantly larger in TDs. Modeling the learning process (using Drift Diffusion Model) revealed that TDs' steeper learning results from a larger increase in their effective face-specific signal. We propose that IDDs' slower item-specific categorical learning of unknown faces indicates that slower categorical learning in dyslexia is a core, domain-general difficulty.

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.

Neural correlates of statistical learning in developmental dyslexia: An electroencephalography study

The human brain extracts statistical regularities from the surrounding environment in a process called statistical learning. Behavioural evidence suggests that developmental dyslexia affects statistical learning. However, surprisingly few studies have assessed how developmental dyslexia affects the neural processing underlying this type of learning. We used electroencephalography to explore the neural correlates of an important aspect of statistical learning - sensitivity to transitional probabilities - in individuals with developmental dyslexia. Adults diagnosed with developmental dyslexia (n = 17) and controls (n = 19) were exposed to a continuous stream of sound triplets. Every so often, a triplet ending had a low transitional probability given the triplet's first two sounds ("statistical deviants"). Furthermore, every so often a triplet ending was presented from a deviant location ("acoustic deviants"). We examined mismatch negativity elicited by statistical deviants (sMMN), and MMN elicited by location deviants (i.e., acoustic changes). Acoustic deviants elicited a MMN which was larger in the control group than in the developmental dyslexia group. Statistical deviants elicited a small, yet significant, sMMN in the control group, but not in the developmental dyslexia group. However, the difference between the groups was not significant. Our findings indicate that the neural mechanisms underlying pre-attentive acoustic change detection and implicit statistical auditory learning are both affected in developmental dyslexia.

Adaptation in auditory processing

Adaptation is an essential feature of auditory neurons, which reduces their responses to unchanging and recurring sounds and allows their response properties to be matched to the constantly changing statistics of sounds that reach the ears. As a consequence, processing in the auditory system highlights novel or unpredictable sounds and produces an efficient representation of the vast range of sounds that animals can perceive by continually adjusting the sensitivity and, to a lesser extent, the tuning properties of neurons to the most commonly encountered stimulus values. Together with attentional modulation, adaptation to sound statistics also helps to generate neural representations of sound that are tolerant to background noise and therefore plays a vital role in auditory scene analysis. In this review, we consider the diverse forms of adaptation that are found in the auditory system in terms of the processing levels at which they arise, the underlying neural mechanisms, and their impact on neural coding and perception. We also ask what the dynamics of adaptation, which can occur over multiple timescales, reveal about the statistical properties of the environment. Finally, we examine how adaptation to sound statistics is influenced by learning and experience and changes as a result of aging and hearing loss.

Diminished Repetition Suppression Reveals Selective and Systems-Level Face Processing Differences in ASD

Repeated exposure to a stimulus results in reduced neural response, or repetition suppression, in brain regions responsible for processing that stimulus. This rapid accommodation to repetition is thought to underlie learning, stimulus selectivity, and strengthening of perceptual expectations. Importantly, reduced sensitivity to repetition has been identified in several neurodevelopmental, learning, and psychiatric disorders, including autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by challenges in social communication and repetitive behaviors and restricted interests. Reduced ability to exploit or learn from repetition in ASD is hypothesized to contribute to sensory hypersensitivities, and parallels several theoretical frameworks claiming that ASD individuals show difficulty using regularities in the environment to facilitate behavior. Using fMRI in autistic and neurotypical human adults (females and males), we assessed the status of repetition suppression across two modalities (vision, audition) and with four stimulus categories (faces, objects, printed words, and spoken words). ASD individuals showed domain-specific reductions in repetition suppression for face stimuli only, but not for objects, printed words, or spoken words. Reduced repetition suppression for faces was associated with greater challenges in social communication in ASD. We also found altered functional connectivity between atypically adapting cortical regions and higher-order face recognition regions, and microstructural differences in related white matter tracts in ASD. These results suggest that fundamental neural mechanisms and system-wide circuits are selectively altered for face processing in ASD and enhance our understanding of how disruptions in the formation of stable face representations may relate to higher-order social communication processes.SIGNIFICANCE STATEMENT A common finding in neuroscience is that repetition results in plasticity in stimulus-specific processing regions, reflecting selectivity and adaptation (repetition suppression [RS]). RS is reduced in several neurodevelopmental and psychiatric conditions including autism spectrum disorder (ASD). Theoretical frameworks of ASD posit that reduced adaptation may contribute to associated challenges in social communication and sensory processing. However, the scope of RS differences in ASD is unknown. We examined RS for multiple categories across visual and auditory domains (faces, objects, printed words, spoken words) in autistic and neurotypical individuals. We found reduced RS in ASD for face stimuli only and altered functional connectivity and white matter microstructure between cortical face-recognition areas. RS magnitude correlated with social communication challenges among autistic individuals.

Is there evidence for a noisy computation deficit in developmental dyslexia?

The noisy computation hypothesis of developmental dyslexia (DD) is particularly appealing because it can explain deficits across a variety of domains, such as temporal, auditory, phonological, visual and attentional processes. A key prediction is that noisy computations lead to more variable and less stable word representations. A way to test this hypothesis is through repetition of words, that is, when there is noise in the system, the neural signature of repeated stimuli should be more variable. The hypothesis was tested in an functional magnetic resonance imaging experiment with dyslexic and typical readers by repeating words twelve times. Variability measures were computed both at the behavioral and neural levels. At the behavioral level, we compared the standard deviation of reaction time distributions of repeated words. At the neural level, in addition to standard univariate analyses and measures of intra-item variability, we also used multivariate pattern analyses (representational similarity and classification) to find out whether there was evidence for noisier representations in dyslexic readers compared to typical readers. Results showed that there were no significant differences between the two groups in any of the analyses despite robust results within each group (i.e., high representational similarity between repeated words, good classification of words vs. non-words). In summary, there was no evidence in favor of the idea that dyslexic readers would have noisier neural representations than typical readers.

Functional Plasticity Coupled With Structural Predispositions in Auditory Cortex Shape Successful Music Category Learning

Categorizing sounds into meaningful groups helps listeners more efficiently process the auditory scene and is a foundational skill for speech perception and language development. Yet, how auditory categories develop in the brain through learning, particularly for non-speech sounds (e.g., music), is not well understood. Here, we asked musically naïve listeners to complete a brief (∼20 min) training session where they learned to identify sounds from a musical interval continuum (minor-major 3rds). We used multichannel EEG to track behaviorally relevant neuroplastic changes in the auditory event-related potentials (ERPs) pre- to post-training. To rule out mere exposure-induced changes, neural effects were evaluated against a control group of 14 non-musicians who did not undergo training. We also compared individual categorization performance with structural volumetrics of bilateral Heschl's gyrus (HG) from MRI to evaluate neuroanatomical substrates of learning. Behavioral performance revealed steeper (i.e., more categorical) identification functions in the posttest that correlated with better training accuracy. At the neural level, improvement in learners' behavioral identification was characterized by smaller P2 amplitudes at posttest, particularly over right hemisphere. Critically, learning-related changes in the ERPs were not observed in control listeners, ruling out mere exposure effects. Learners also showed smaller and thinner HG bilaterally, indicating superior categorization was associated with structural differences in primary auditory brain regions. Collectively, our data suggest successful auditory categorical learning of music sounds is characterized by short-term functional changes (i.e., greater post-training efficiency) in sensory coding processes superimposed on preexisting structural differences in bilateral auditory cortex.