Evidence map›Paper›PMID 41947870›Full record

ArticleFrontiers in human neuroscience2026

Quantifying vocal subsystems of adults with minimally verbal autism spectrum disorder.

Thomas F Quatieri, Tanya Talkar, James R Williamson, Sophia Yuditskaya, Chakameh Jafari, Meredith Pecukonis, Paige Townsend, Laura Sarnie, Nataliya Kosmyna, Nishat Protyasha and 4 more

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Thomas F QuatieriMIT Lincoln Laboratory, Lexington, MA, United States.
Tanya TalkarMIT Lincoln Laboratory, Lexington, MA, United States.
James R WilliamsonMIT Lincoln Laboratory, Lexington, MA, United States.
Sophia YuditskayaMIT Lincoln Laboratory, Lexington, MA, United States.
Chakameh JafariMIT Lincoln Laboratory, Lexington, MA, United States.
Meredith PecukonisMGH Lurie Center for Autism, Lexington, MA, United States.
Paige TownsendMGH Lurie Center for Autism, Lexington, MA, United States.
Laura SarnieMGH Lurie Center for Autism, Lexington, MA, United States.
Nataliya KosmynaMIT Media Lab, Cambridge, CA, United States.
Nishat ProtyashaMIT Media Lab, Cambridge, CA, United States.
Pattie MaesMIT Media Lab, Cambridge, CA, United States.
Christopher J McDougleMGH Lurie Center for Autism, Lexington, MA, United States.
Lisa NowinskiMGH Lurie Center for Autism, Lexington, MA, United States.
Maria ModyMGH Lurie Center for Autism, Lexington, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The understanding of speech production and its fine-motor underpinnings in individuals with autism spectrum disorder (ASD) has become an area of growing interest in clinical research. Here, we developed objective acoustic-based measures to characterize and contrast the respiratory, laryngeal, and articulatory vocal production subsystems based on data from 27 adults with minimally-verbal autism spectrum disorder (mv-ASD) relative to 27 age-matched neurotypical (NT) peers. The complexity of representative movement dynamics of each subsystem was determined through signal correlation analysis, associated with degrees of freedom derived from correlation structure. As proxies to underlying speech production, we used base features of signal envelope, pitch and formant trajectories associated with each subsystem, respectively, along with their velocities. In addition, we examined cepstral peak prominence and mel-frequency cepstral coefficients, associated with laryngeal and articulatory systems, widely used in assessing voice and speech in neurological and pathological conditions. With speech data from a protocol consisting of diadochokinetic sequencing (DDK), and three different single-word tasks of varying cognitive load (Imitation, Naming, Reading), we studied complexity of motor dynamics at group and individual levels under each task condition. At group level, mv-ASDs showed lower complexity than NT participants for the respiratory and laryngeal subsystems and, except for the DDK task, higher complexity for the articulatory subsystem. At the individual level, there is a range of complexity consistent with mv-ASD heterogeneity. Using Pearson and Spearman correlation measures, we correlated our subsystem characterization with measures of non-verbal IQ, expressive and receptive vocabulary, visual-motor integration, and fine motor dexterity to understand the clinical relevance of these acoustic features, as well as the effect of outliers. When combining mv-ASD and NT groups, articulatory base features were most consistent in correlating with expressive vocabulary across tasks, compared to respiratory and laryngeal features. The Pearson-based association holds within the mv-ASD group alone for the single-word tasks. Continued understanding of speech and language challenges of individuals with mv-ASD reflected in metrics of each of the three speech production subsystems (respiratory, laryngeal, and articulatory) and their relationship with standardized motor, cognitive, and language assessments, will promote design of functionally-tailored personalized and clinically acceptable interventions.

Indexed as

autismcomplexitydynamicsminimally-verbalspeech

Identifiers

PMID41947870
PMCPMC13051654

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.