Mechanisms of voice control related to prosody in autism spectrum disorder and first‐degree relatives

Patel, Shivani; Kim, Jason H.; Larson, Charles R.; Losh, Molly

doi:10.1002/aur.2156

Cited by 28 publications

(26 citation statements)

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“…Given that pragmatic impairment is a de ning feature of ASD (1)(2)(3)(4)(5), and subclinical pragmatic language differences have been repeatedly documented in ASD relatives (12,(16)(17)(18)20), associations between pragmatics and neural processing of speech sounds are signi cant in implicating FFR as neural mechanism related to a core symptom domain in ASD. Associations between response latencies and key pragmatic language skills in parents are also intriguing in suggesting that even subtle differences in neural processing of sound might have reverberating effects on downstream, more complex language abilities, such as pragmatics, which rely on the integration of many foundational mechanisms and skills.…”

Section: Discussionmentioning

confidence: 99%

“…Given repeated observations that parents of individuals with ASD may display subclinical pragmatic language differences (16,17,20), and speci cally in neural mechanisms contributing to audio-vocal integration impacting prosody (12), we predicted that the ASD parent group would display increased neural response latencies and reduced delity of neural pitch compared to parent controls. We predicted that atypicalities in FFR would relate to pragmatic and prosodic abilities in individuals with ASD and their parents, and that parent-child associations would emerge in the delity of neural response to speech sounds, which would support FFR as a potential heritable neural marker of language-related impairments in ASD.…”

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confidence: 99%

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Neural Processing of Speech Sounds in ASD and First-Degree Relatives

Patel¹,

Winston²,

Guilfoyle³

et al. 2020

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Background: Efficient neural encoding of sound plays a critical and widespread role in speech and language, and when impaired, may have reverberating effects on a range of communication skills. Autism spectrum disorder (ASD) is a condition involving impaired communication abilities, including atypical prosody (e.g., intonation modulation, rate, rhythm), in which atypical neural processing of speech has been implicated. Parallel patterns of communication differences have been noted in parents of individuals with ASD, who may exhibit subclinical language-related differences believed to reflect genetic liability to ASD. The present study investigated disruptions to neural processing of temporal and spectral (i.e., frequency/pitch) properties of speech sounds as a potential neurobiological mechanism underlying specific language-related impairments in ASD and related subclinical differences documented among first-degree relatives of individuals with ASD. Methods: Participants included individuals with ASD, their parents, and respective control groups. Group differences in temporal and spectral processing based on the neural FFR were assessed using MANCOVAs controlling for chronological age. Relationships between the FFR, pragmatic language ability, and receptive and expressive prosody skills were assessed using Pearson correlations. Familiality of the FFR in mother-child dyads were also examined using Pearson correlations.Results: Findings revealed inefficiencies in neural encoding of speech sounds in both individuals with ASD and their parents (specifically, increased neural noise and delayed neural processing of speech sounds), as well as a less robust neural representation of spectral properties of speech sounds in individuals with ASD. Associations between neural processing of speech sounds and language-related abilities were detected in both groups, along with evidence of familiality of neural pitch processing in the ASD family groups. Limitations: Additional investigation is necessary to determine whether relationships between FFR and pragmatic language and prosody extend to individuals with more severe language and/or cognitive impairments. Conclusions: Overall, results suggest atypical neural processing of speech sounds may constitute an important, heritable ingredient contributing to the ASD language phenotype and subclinical phenotypic expression of genetic liability in parents.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Neural Processing of Speech Sounds in ASD and First-Degree Relatives

Patel¹,

Winston²,

Guilfoyle³

et al. 2020

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“…Auditory feedback control of speech in autistic children and adults, and their first-degree relatives, has also been examined by Patel et al [2019]. In this study, when exposed to FAF perturbations, larger compensatory vocal responses were produced by both autistic individuals and their first-degree relatives, relative to age-matched control groups.…”

Section: Discussionmentioning

confidence: 83%

“…The results of this study indicated that children with 16p11.2 deletions produced larger magnitude responses relative to siblings without the 16p11.2 deletion ( n = 4) and neurotypical comparisons ( n = 5). More recently, Patel, Kim, Larson, and Losh [2019] also examined responses to FAF in a sample ( n = 17) of autistic children and adults between the ages of 9 and 32 years. The results indicated that autistic participants produced larger vocal responses to the FAF.…”

Section: Introductionmentioning

confidence: 99%

“…In order to examine the relations between social competence and the development of other skills like prosodic control, we utilized the Multidimensional Social Competence Scale (MSCS), developed by Yager and Iarocci [2013, which is a parent‐report questionnaire that measures social competence in autistic and non‐autistic children. Based on the results of previous FAF studies aimed at investigating the relations between speech motor control and ASD [Demopoulos et al, 2018; Patel et al, 2019; Russo et al, 2008], we expected that a subset of autistic children would produce larger responses to the FAF, relative to the non‐autistic children. Previous studies had not reported differences in response latency across autistic and non‐autistic speakers [Demopoulos et al, 2018; Russo et al, 2008], thus, we did not expect to find latency differences across our samples.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Relationship between Prosodic Control and Social Competence in Children with and without Autism Spectrum Disorder

2020

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Autism spectrum disorder (ASD) is a developmental disorder characterized by persistent deficits in social communication and interaction. Speech is an important form of social communication. Prosody (e.g. vocal pitch, rhythm, etc.), one aspect of the speech signal, is crucial for ensuring information about the emotionality, excitability, and intent of the speaker, is accurately expressed. The objective of this study was to gain a better understanding of how auditory information is used to regulate speech prosody in autistic and non-autistic children, while exploring the relationship between the prosodic control of speech and social competence. Eighty autistic (M = 8.48 years, SD = 2.55) and non-autistic (M = 7.36 years, SD = 2.51) participants produced vocalizations while exposed to unaltered and frequency altered auditory feedback. The parent-report Multidimensional Social Competence Scale was used to assess social competence, while the Autism-Spectrum Quotient and the Autism Spectrum Rating Scales were used to assess autism characteristics. Results indicate that vocal response magnitudes and vocal variability were similar across autistic and non-autistic children. However, autistic children produced significantly faster responses to the auditory feedback manipulation. Hierarchical multiple regressions indicated that these faster responses were significantly associated with poorer parent-rated social competence and higher autism characteristics. These findings suggest that prosodic speech production differences are present in at least a subgroup of autistic children. These results represent a key step in understanding how atypicalities in the mechanisms supporting speech production may manifest in social-communication deficits, as well as broader social competence, and vice versa.

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Vocal markers of autism: Assessing the generalizability of machine learning models

et al. 2022

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Machine learning (ML) approaches show increasing promise in their ability to identify vocal markers of autism. Nonetheless, it is unclear to what extent such markers generalize to new speech samples collected, for example, using a different speech task or in a different language. In this paper, we systematically assess the generalizability of ML findings across a variety of contexts. We train promising published ML models of vocal markers of autism on novel cross‐linguistic datasets following a rigorous pipeline to minimize overfitting, including cross‐validated training and ensemble models. We test the generalizability of the models by testing them on (i) different participants from the same study, performing the same task; (ii) the same participants, performing a different (but similar) task; (iii) a different study with participants speaking a different language, performing the same type of task. While model performance is similar to previously published findings when trained and tested on data from the same study (out‐of‐sample performance), there is considerable variance between studies. Crucially, the models do not generalize well to different, though similar, tasks and not at all to new languages. The ML pipeline is openly shared. Generalizability of ML models of vocal markers of autism is an issue. We outline three recommendations for strategies researchers could take to be more explicit about generalizability and improve it in future studies. Lay Summary Machine learning approaches promise to be able to identify autism from voice only. These models underestimate how diverse the contexts in which we speak are, how diverse the languages used are and how diverse autistic voices are. Machine learning approaches need to be more careful in defining their limits and generalizability.

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Mechanisms of voice control related to prosody in autism spectrum disorder and first‐degree relatives

Cited by 28 publications

References 77 publications

Neural Processing of Speech Sounds in ASD and First-Degree Relatives

Neural Processing of Speech Sounds in ASD and First-Degree Relatives

Exploring the Relationship between Prosodic Control and Social Competence in Children with and without Autism Spectrum Disorder

Vocal markers of autism: Assessing the generalizability of machine learning models

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