Abnormal motor cortex excitability during linguistic tasks in adductor‐type spasmodic dysphonia

Suppa, Antonio; Marsili, Luca; Giovannelli, Fabio; Stasio, Flavio Di; Rocchi, Lorenzo; Pantano, P.; Ruoppolo, Giovanni; Cincotta, Massimo; Berardelli, Alfredo

doi:10.1111/ejn.12977

Cited by 23 publications

(27 citation statements)

References 48 publications

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“…Future cohort studies comparing voice recordings in a larger number of samples of different ages (e.g., large samples of subjects in early, middle and late adulthood) will better examine whether age-related changes in voice can be considered biomarkers of human ageing. Furthermore, we believe that our study would provide new helpful information to clinicians to better distinguish physiologic ageing from pathological changes of the human voice in subjects affected by various speech disorders [ 77 , 84 ].…”

Section: Discussionmentioning

confidence: 99%

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender

Asci

Costantini

Leo

et al. 2020

Sensors

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Background: Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynamic interaction. To examine the complexity of age-related changes in voice, more advanced techniques based on machine learning have been recently applied to voice recordings but only in a laboratory setting. We here recorded voice samples in a large sample of healthy subjects. To improve the ecological value of our analysis, we collected voice samples directly at home using smartphones. Methods: 138 younger adults (65 males and 73 females, age range: 15–30) and 123 older adults (47 males and 76 females, age range: 40–85) produced a sustained emission of a vowel and a sentence. The recorded voice samples underwent a machine learning analysis through a support vector machine algorithm. Results: The machine learning analysis of voice samples from both speech tasks discriminated between younger and older adults, and between males and females, with high statistical accuracy. Conclusions: By recording voice samples through smartphones in an ecological setting, we demonstrated the combined effect of age and gender on voice. Our machine learning analysis demonstrates the effect of ageing on voice.

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Section: Discussionmentioning

confidence: 99%

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender

Asci

Costantini

Leo

et al. 2020

Sensors

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“…1 Moreover, a recent transcranial magnetic stimulation study found abnormal left motor cortex excitability during a "readingaloud" task in adductor SD patients compared with healthy controls; no significant changes in excitability were found in the right motor cortex. 45 A recent resting-state fMRI study found significant abnormal connectivity in the left inferior parietal cortex (together with the left sensorimotor cortex) in SD compared with healthy controls. 2 This likely contributes to abnormal sensorimotor integration, loss of proprioceptive and tactile feedback, and inappropriate modulation of learned speech production present in SD.…”

Section: Unilateral Dbs For Spasmodic Dysphonia: Sufficient or Insuffmentioning

confidence: 98%

“…48,49 A significant portion of the pallidal outflow is directed to the Voa thalamic nucleus. 30 Some focal dystonias have been treated with thalamic lesions 45 and neuromodulation of that portion of the motor thalamus. 11 Since SD (also known as laryngeal dystonia) is a focal dystonia, we were surprised that Voa (pallidal outflow) thalamic stimulation produced no benefit in vocal dysfunction.…”

Section: Treating Cerebellar Dysfunction May Mediate Improvement In Sdmentioning

confidence: 99%

The effect of unilateral thalamic deep brain stimulation on the vocal dysfunction in a patient with spasmodic dysphonia: interrogating cerebellar and pallidal neural circuits

Poologaindran¹,

Ivanishvili²,

Morrison

et al. 2018

Journal of Neurosurgery

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Spasmodic dysphonia (SD) is a neurological disorder of the voice where a patient's ability to speak is compromised due to involuntary contractions of the intrinsic laryngeal muscles. Since the 1980s, SD has been treated with botulinum toxin A (BTX) injections into the throat. This therapy is limited by the delayed-onset of benefits, wearing-off effects, and repeated injections required every 3 months. In a patient with essential tremor (ET) and coincident SD, the authors set out to quantify the effects of thalamic deep brain stimulation (DBS) on vocal function while investigating the underlying motor thalamic circuitry. A 79-year-old right-handed woman with ET and coincident adductor SD was referred to our neurosurgical team. While primarily treating her limb tremor, the authors studied the effects of unilateral, thalamic DBS on vocal function using the Unified Spasmodic Dysphonia Rating Scale (USDRS) and voice-related quality of life (VRQOL). Since dystonia is increasingly being considered a multinodal network disorder, an anterior trajectory into the left thalamus was deliberately chosen such that the proximal contacts of the electrode were in the ventral oralis anterior (Voa) nucleus (pallidal outflow) and the distal contacts were in the ventral intermediate (Vim) nucleus (cerebellar outflow). In addition to assessing on/off unilateral thalamic Vim stimulation on voice, the authors experimentally assessed low-voltage unilateral Vim, Voa, or multitarget stimulation in a prospective, randomized, doubled-blinded manner. The evaluators were experienced at rating SD and were familiar with the vocal tremor of ET. A Wilcoxon signed-rank test was used to study the pre- and posttreatment effect of DBS on voice. Unilateral left thalamic Vim stimulation (DBS on) significantly improved SD vocal dysfunction compared with no stimulation (DBS off), as measured by the USDRS (p < 0.01) and VRQOL (p < 0.01). In the experimental interrogation, both low-voltage Vim (p < 0.01) and multitarget Vim + Voa (p < 0.01) stimulation were significantly superior to low-voltage Voa stimulation. For the first time, the effects of high-frequency stimulation of different neural circuits in SD have been quantified. Unexpectedly, focused Voa (pallidal outflow) stimulation was inferior to Vim (cerebellar outflow) stimulation despite the classification of SD as a dystonia. While only a single case, scattered reports exist on the positive effects of thalamic DBS on dysphonia. A Phase 1 pilot trial (DEBUSSY; clinical trial no. NCT02558634, clinicaltrials.gov) is underway at the authors' center to evaluate the safety and preliminary efficacy of DBS in SD. The authors hope that this current report stimulates neurosurgeons to investigate this new indication for DBS.

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“…Based on previous studies in SD [3][4][5][6][7][8][9][10], we hypothesized that SD as a disorder can be distinguished from a normal state based on significant alterations within the sensorimotor network (SMN), whereas different SD forms can be categorized based on additional and combined abnormalities within the SMN and frontoparietal network (FPN). As SD is a task-specific disorder impairing a highly learned behavior, i.e.…”

Section: Introductionmentioning

confidence: 99%

Cortical sensorimotor alterations classify clinical phenotype and putative genotype of spasmodic dysphonia

Battistella

Fuertinger

Fleysher

et al. 2016

Euro J of Neurology

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Background Spasmodic dysphonia (SD), or laryngeal dystonia, is a task-specific isolated focal dystonia of unknown causes and pathophysiology. Although functional and structural abnormalities have been described in this disorder, the influence of its different clinical phenotypes and genotypes remains scant, making it difficult to explain SD pathophysiology and to identify potential biomarkers. Methods We used a combination of independent component analysis and linear discriminant analysis of resting-state functional MRI data to investigate brain organization in different SD phenotypes (abductor vs. adductor type) and putative genotypes (familial vs. sporadic cases) and to characterize neural markers for genotype/phenotype categorization. Results We found abnormal functional connectivity within sensorimotor and frontoparietal networks in SD patients compared to healthy individuals as well as phenotype- and genotype-distinct alterations of these networks, involving primary somatosensory, premotor and parietal cortices. The linear discriminant analysis achieved 71% accuracy classifying SD and healthy individuals using connectivity measures in the left inferior parietal and sensorimotor cortex. When categorizing between different forms of SD, the combination of measures from left inferior parietal, premotor and right sensorimotor cortices achieved 81% discriminatory power between familial and sporadic SD cases, whereas the combination of measures from the right superior parietal, primary somatosensory and premotor cortices led to 71% accuracy in the classification of adductor and abductor SD forms. Conclusions Our findings present the first effort to identify and categorize isolated focal dystonia based on its brain functional connectivity profile, which may have a potential impact on the future development of biomarkers for this rare disorder.

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Abnormal motor cortex excitability during linguistic tasks in adductor‐type spasmodic dysphonia

Cited by 23 publications

References 48 publications

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender

The effect of unilateral thalamic deep brain stimulation on the vocal dysfunction in a patient with spasmodic dysphonia: interrogating cerebellar and pallidal neural circuits

Cortical sensorimotor alterations classify clinical phenotype and putative genotype of spasmodic dysphonia

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