Deficient Response to Altered Auditory Feedback in Dyslexia

Bunt, Mark R. van den; Groen, Margriet A.; Kleij, Sanne W. van der; Noordenbos, Mark W.; Segers, Eliane; Pugh, Kenneth R.

doi:10.1080/87565641.2018.1495723

Cited by 6 publications

(14 citation statements)

References 74 publications

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“…Ten studies also included an end phase where the perturbation was removed (ranging from 10–40 trials, M = 20.15). One study additionally included a ramp-down phase where the perturbation was gradually removed following the hold phase ( van den Bunt et al, 2018b ).…”

Section: Resultsmentioning

confidence: 99%

“…In Dutch, this manipulation included an F1 increase of 25% and an F2 increase or decrease by 12.5% ( Terband et al, 2014 ; van Brenk and Terband, 2020 respectively), in French F1 was increased by 27% and F2 decreased by 10% ( Caudrelier et al, 2019 ), and in English F1 was increased by 200 Hz or 25% and F2 was decreased by 250 Hz or 12.5% ( MacDonald et al, 2012 ; Daliri et al, 2018 ; Demopoulos et al, 2018 ). One study ( van den Bunt et al, 2018b ) individualized the manipulation so the maximum perturbation meant a change from/ı/to/ε/for each participant. Kim et al (2020) manipulated F1 and F2 upward 335 cents (adult population received manipulation of ±250 cents).…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…Phonological awareness measures were collected in three studies ( van den Bunt et al, 2018a , b ; Caudrelier et al, 2019 ). Reading measures were additionally collected in two of these studies ( van den Bunt et al, 2018a , b ). Better rapid automatized naming was found to correlate with better compensation ( van den Bunt et al, 2018a ), as well as correlated with weaker deviation from the baseline during the ramp-up phase and stronger de-adaptation during the ramp-down phase ( van den Bunt et al, 2018b ).…”

Section: Resultsmentioning

confidence: 99%

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Pediatric Responses to Fundamental and Formant Frequency Altered Auditory Feedback: A Scoping Review

Coughler

Launay

Purcell

et al. 2022

Front. Hum. Neurosci.

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PurposeThe ability to hear ourselves speak has been shown to play an important role in the development and maintenance of fluent and coherent speech. Despite this, little is known about the developing speech motor control system throughout childhood, in particular if and how vocal and articulatory control may differ throughout development. A scoping review was undertaken to identify and describe the full range of studies investigating responses to frequency altered auditory feedback in pediatric populations and their contributions to our understanding of the development of auditory feedback control and sensorimotor learning in childhood and adolescence.MethodRelevant studies were identified through a comprehensive search strategy of six academic databases for studies that included (a) real-time perturbation of frequency in auditory input, (b) an analysis of immediate effects on speech, and (c) participants aged 18 years or younger.ResultsTwenty-three articles met inclusion criteria. Across studies, there was a wide variety of designs, outcomes and measures used. Manipulations included fundamental frequency (9 studies), formant frequency (12), frequency centroid of fricatives (1), and both fundamental and formant frequencies (1). Study designs included contrasts across childhood, between children and adults, and between typical, pediatric clinical and adult populations. Measures primarily explored acoustic properties of speech responses (latency, magnitude, and variability). Some studies additionally examined the association of these acoustic responses with clinical measures (e.g., stuttering severity and reading ability), and neural measures using electrophysiology and magnetic resonance imaging.ConclusionFindings indicated that children above 4 years generally compensated in the opposite direction of the manipulation, however, in several cases not as effectively as adults. Overall, results varied greatly due to the broad range of manipulations and designs used, making generalization challenging. Differences found between age groups in the features of the compensatory vocal responses, latency of responses, vocal variability and perceptual abilities, suggest that maturational changes may be occurring in the speech motor control system, affecting the extent to which auditory feedback is used to modify internal sensorimotor representations. Varied findings suggest vocal control develops prior to articulatory control. Future studies with multiple outcome measures, manipulations, and more expansive age ranges are needed to elucidate findings.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Pediatric Responses to Fundamental and Formant Frequency Altered Auditory Feedback: A Scoping Review

Coughler

Launay

Purcell

et al. 2022

Front. Hum. Neurosci.

View full text Add to dashboard Cite

show abstract

“…The adaptations of these posterior brain regions represent brain markers of reading development, and their hypoactivation and altered function, markers of dyslexia. As markers of risk for dyslexia, understanding how these regions function and adapt can potentially inform earlier identification of risk for dyslexia and better understanding of reading treatment response (Gabrieli, 2009 ; Van Den Bunt et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Visual Explanation for Identification of the Brain Bases for Developmental Dyslexia on fMRI Data

Silva

Esper

Ruiz

et al. 2021

Front. Comput. Neurosci.

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Problem: Brain imaging studies of mental health and neurodevelopmental disorders have recently included machine learning approaches to identify patients based solely on their brain activation. The goal is to identify brain-related features that generalize from smaller samples of data to larger ones; in the case of neurodevelopmental disorders, finding these patterns can help understand differences in brain function and development that underpin early signs of risk for developmental dyslexia. The success of machine learning classification algorithms on neurofunctional data has been limited to typically homogeneous data sets of few dozens of participants. More recently, larger brain imaging data sets have allowed for deep learning techniques to classify brain states and clinical groups solely from neurofunctional features. Indeed, deep learning techniques can provide helpful tools for classification in healthcare applications, including classification of structural 3D brain images. The adoption of deep learning approaches allows for incremental improvements in classification performance of larger functional brain imaging data sets, but still lacks diagnostic insights about the underlying brain mechanisms associated with disorders; moreover, a related challenge involves providing more clinically-relevant explanations from the neural features that inform classification.Methods: We target this challenge by leveraging two network visualization techniques in convolutional neural network layers responsible for learning high-level features. Using such techniques, we are able to provide meaningful images for expert-backed insights into the condition being classified. We address this challenge using a dataset that includes children diagnosed with developmental dyslexia, and typical reader children.Results: Our results show accurate classification of developmental dyslexia (94.8%) from the brain imaging alone, while providing automatic visualizations of the features involved that match contemporary neuroscientific knowledge (brain regions involved in the reading process for the dyslexic reader group and brain regions associated with strategic control and attention processes for the typical reader group).Conclusions: Our visual explanations of deep learning models turn the accurate yet opaque conclusions from the models into evidence to the condition being studied.

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Transfer of sensorimotor learning reveals phoneme representations in preliterate children

et al. 2019

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Reading acquisition is strongly intertwined with phoneme awareness that relies on implicit phoneme representations. We asked whether phoneme representations emerge before literacy. We recruited two groups of children, 4 to 5-year-old preschoolers (N=29) and 7 to 8year-old schoolchildren (N=24), whose phonological awareness was evaluated, and one adult control group (N=17). We altered speakers' auditory feedback in real time to elicit persisting pronunciation changes, referred to as auditory-motor adaptation or learning. Assessing the transfer of learning at phoneme level enabled us to investigate the developmental time-course of phoneme representations. Significant transfer at phoneme level occurred in preschoolers, as well as schoolchildren and adults. In addition, we found a relationship between auditorymotor adaptation and phonological awareness in both groups of children. Overall, these results suggest that phoneme representations emerge before literacy acquisition, and that these sensorimotor representations may set the ground for phonological awareness.

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Deficient Response to Altered Auditory Feedback in Dyslexia

Cited by 6 publications

References 74 publications

Pediatric Responses to Fundamental and Formant Frequency Altered Auditory Feedback: A Scoping Review

Pediatric Responses to Fundamental and Formant Frequency Altered Auditory Feedback: A Scoping Review

Visual Explanation for Identification of the Brain Bases for Developmental Dyslexia on fMRI Data

Transfer of sensorimotor learning reveals phoneme representations in preliterate children

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