The impact of threat and cognitive stress on speech motor control in people who stutter

Lieshout, Pascal van; Ben‐David, Boaz M.; Lipski, Melinda; Namasivayam, Aravind Kumar

doi:10.1016/j.jfludis.2014.02.003

Cited by 48 publications

(35 citation statements)

References 88 publications

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“…First, one-way ANOVA indicated that CWS took significantly longer (M= 85.5 seconds, SD=21.9) to name the 30 pictures than their normally fluent peers (M= 72.46 seconds, SD=17.67); F (1, 74) = 8.17, p = .006, a finding consistent previous findings that children and adults who stutter exhibit longer reaction times (RTs) during a variety of (non-speech tasks (e.g., Bloodstein & Bernstein Ratner, 2008; van Lieshout, Ben-David, Lipski, Namasivayam, 2014). …”

Section: Resultssupporting

confidence: 85%

Sympathetic arousal of young children who stutter during a stressful picture naming task

Zengin-Bolatkale

Conture

Walden

2015

Journal of Fluency Disorders

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Section: Resultssupporting

confidence: 85%

Sympathetic arousal of young children who stutter during a stressful picture naming task

Zengin-Bolatkale

Conture

Walden

2015

Journal of Fluency Disorders

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“…Similarly, smaller interlip phase differences in AWS compared to controls were reported by van Lieshout et al [66] when speaking under cognitively stressful conditions. An increase in intergestural stability may reflect a less flexible system that can lead to a reduced ability to respond to environmental changes, increasing the system’s susceptibility to breakdown.…”

Section: Introductionsupporting

confidence: 66%

“…Slower reaction times [65, 66] and movement durations [51] have been reported in both children and AWS when performing under cognitively stressful conditions. A recent investigation by Bauerly and Paxton [67] assessed the F2 slopes (frequency extent/duration) of AWS and ANS during the production of consonant-vowel + final /t/ (CV t ) nonwords in arousing conditions (excited-calm), both positively and negatively valenced.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Emotion on Second Formant Frequency Fluctuations in Adults Who Stutter

Bauerly¹

2018

Folia Phoniatr Logop

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Objective: Changes in second formant frequency fluctuations (FFF2) were examined in adults who stutter (AWS) and adults who do not stutter (ANS) when producing nonwords under varying emotional conditions. Methods: Ten AWS and 10 ANS viewed images selected from the International Affective Picture System representing dimensions of arousal (e.g., excited versus bored) and hedonic valence (e.g., happy versus sad). Immediately following picture presentation, participants produced a consonant-vowel + final /t/ (CVt) nonword consisting of the initial sounds /p/, /b/, /s/, or /z/, followed by a vowel (/i/, /u/, /ε/) and a final /t/. CVt tokens were assessed for word duration and FFF2. Results: Significantly slower word durations were shown in the AWS compared to the ANS across conditions. Although these differences appeared to increase under arousing conditions, no interaction was found. Results for FFF2 revealed a significant group-condition interaction. Post hoc analysis indicated that this was due to the AWS showing significantly greater FFF2 when speaking under conditions eliciting increases in arousal and unpleasantness. ANS showed little change in FFF2 across conditions. Conclusions: The results suggest that AWS’ articulatory stability is more susceptible to breakdown under negative emotional influences.

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“…The filters generated a list of 471 words. From this list morphemic derivatives and proper nouns were removed, as well as words eliciting general and stuttering-specific threats, as suggested by recent studies (Hennessey et al, 2014; van Lieshout et al, 2014). The final list consisted of semantically neutral 414 words.…”

Section: Methodsmentioning

confidence: 99%

Sensorimotor Oscillations Prior to Speech Onset Reflect Altered Motor Networks in Adults Who Stutter

Mersov

Jobst

Cheyne

et al. 2016

Front. Hum. Neurosci.

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Adults who stutter (AWS) have demonstrated atypical coordination of motor and sensory regions during speech production. Yet little is known of the speech-motor network in AWS in the brief time window preceding audible speech onset. The purpose of the current study was to characterize neural oscillations in the speech-motor network during preparation for and execution of overt speech production in AWS using magnetoencephalography (MEG). Twelve AWS and 12 age-matched controls were presented with 220 words, each word embedded in a carrier phrase. Controls were presented with the same word list as their matched AWS participant. Neural oscillatory activity was localized using minimum-variance beamforming during two time periods of interest: speech preparation (prior to speech onset) and speech execution (following speech onset). Compared to controls, AWS showed stronger beta (15–25 Hz) suppression in the speech preparation stage, followed by stronger beta synchronization in the bilateral mouth motor cortex. AWS also recruited the right mouth motor cortex significantly earlier in the speech preparation stage compared to controls. Exaggerated motor preparation is discussed in the context of reduced coordination in the speech-motor network of AWS. It is further proposed that exaggerated beta synchronization may reflect a more strongly inhibited motor system that requires a stronger beta suppression to disengage prior to speech initiation. These novel findings highlight critical differences in the speech-motor network of AWS that occur prior to speech onset and emphasize the need to investigate further the speech-motor assembly in the stuttering population.

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The impact of threat and cognitive stress on speech motor control in people who stutter

Cited by 48 publications

References 88 publications

Sympathetic arousal of young children who stutter during a stressful picture naming task

Sympathetic arousal of young children who stutter during a stressful picture naming task

The Effects of Emotion on Second Formant Frequency Fluctuations in Adults Who Stutter

Sensorimotor Oscillations Prior to Speech Onset Reflect Altered Motor Networks in Adults Who Stutter

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