OBJECTIVES/HYPOTHESIS: Spasmodic dysphonia (SD) is a task-specific laryngeal dystonia that affects speech production. Co-occurring voice tremor (VT) often complicates the diagnosis and clinical management of SD. Treatment of SD and VT is largely limited to botulinum toxin injections into laryngeal musculature; other pharmacological options are not sufficiently developed. STUDY DESIGN: Open-label study. METHODS: We conducted an open-label study in 23 SD and 22 SD/VT patients to examine the effects of sodium oxybate (Xyrem), an oral agent with therapeutic effects similar to those of alcohol in these patients. Blinded randomized analysis of voice and speech samples assessed symptom improvement before and after drug administration. RESULTS: Sodium oxybate significantly improved voice symptoms (P = .001) primarily by reducing the number of SD-characteristic voice breaks and severity of VT. Sodium oxybate further showed a trend for improving VT symptoms (P = .03) in a subset of patients who received successful botulinum toxin injections for the management of their SD symptoms. The drug's effects were observed approximately 30 to 40 minutes after its intake and lasted about 3.5 to 4 hours. CONCLUSIONS: Our study demonstrated that sodium oxybate reduced voice symptoms in 82.2% of alcohol-responsive SD patients both with and without co-occurring VT. Our findings suggest that the therapeutic mechanism of sodium oxybate in SD and SD/VT may be linked to that of alcohol, and as such, sodium oxybate might be beneficial for alcohol-responsive SD and SD/VT patients. LEVEL OF EVIDENCE: 4 Laryngoscope, 127:1402-1407, 2017.
Franca Vulinovic, Susen Schaake, Aloysius Domingo, Kishore Raj Kumar, Giovanni Defazio, Pablo Mir, Kristina Simonyan, Laurie J Ozelius, Norbert Brüggemann, Sun Ju Chung, Aleksandar Rakovic, Katja Lohmann, and Christine Klein. 2017. “Screening study of TUBB4A in isolated dystonia.” Parkinsonism Relat Disord, 41, Pp. 118-120.Abstract
Mutations in TUBB4A have been identified to cause a wide phenotypic spectrum ranging from hereditary generalized dystonia with whispering dysphonia (DYT4) to the leukodystrophy hypomyelination syndrome with atrophy of the basal ganglia and cerebellum (H-ABC). To test for the contribution of TUBB4A mutations in different ethnicities (Spanish, Italian, Korean, Japanese), we screened 492 isolated dystonia cases for mutations in this gene and for the first time determined TUBB4A copy number variations in 336 dystonia patients. A potentially pathogenic rare 3bp-in-frame deletion was found in a patient with cervical dystonia but no copy number variations were detected in this study, suggesting that TUBB4A mutations exceedingly rarely contribute to the etiology of isolated dystonia.
BACKGROUND AND PURPOSE: 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 magnetic resonance imaging data to investigate brain organization in different SD phenotypes (abductor versus adductor type) and putative genotypes (familial versus sporadic cases) and to characterize neural markers for genotype/phenotype categorization. RESULTS: We found abnormal functional connectivity within sensorimotor and frontoparietal networks in patients with SD compared with 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 cortices. When categorizing between different forms of SD, the combination of measures from the 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.
Dystonia is a brain disorder causing involuntary, often painful movements. Apart from a role for dopamine deficiency in some forms, the cellular mechanisms underlying most dystonias are currently unknown. Here, we discover a role for deficient eIF2α signaling in DYT1 dystonia, a rare inherited generalized form, through a genome-wide RNAi screen. Subsequent experiments including patient-derived cells and a mouse model support both a pathogenic role and therapeutic potential for eIF2α pathway perturbations. We further find genetic and functional evidence supporting similar pathway impairment in patients with sporadic cervical dystonia, due to rare coding variation in the eIF2α effector ATF4. Considering also that another dystonia, DYT16, involves a gene upstream of the eIF2α pathway, these results mechanistically link multiple forms of dystonia and put forth a new overall cellular mechanism for dystonia pathogenesis, impairment of eIF2α signaling, a pathway known for its roles in cellular stress responses and synaptic plasticity.
OBJECTIVE: Cortical high-frequency oscillations (HFOs; 100-500 Hz) play a critical role in the pathogenesis of epilepsy; however, whether they represent a true epileptogenic process remains largely unknown. HFOs have been recorded in the human cortex but their network dynamics during the transitional period from interictal to ictal phase remain largely unknown. We sought to determine the high-frequency network dynamics of these oscillations in patients with epilepsy who were undergoing intracranial electroencephalographic recording for seizure localization. METHODS: We applied a graph theoretical analysis framework to high-resolution intracranial electroencephalographic recordings of 24 interictal and 24 seizure periods to identify the spatiotemporal evolution of community structure of high-frequency cortical networks at rest and during multiple seizure episodes in patients with intractable epilepsy. RESULTS: Cortical networks at all examined frequencies showed temporally stable community architecture in all 24 interictal periods. During seizure periods, high-frequency networks showed a significant breakdown of their community structure, which was characterized by the emergence of numerous small nodal communities, not limited to seizure foci and encompassing the entire recorded network. Such network disorganization was observed on average 225 s before the electrographic seizure onset and extended on average 190 s after termination of the seizure. Gamma networks were characterized by stable community dynamics during resting and seizure periods. SIGNIFICANCE: Our findings suggest that the modular breakdown of high-frequency cortical networks represents a distinct functional pathology that underlies epileptogenesis and corresponds to a cortical state of highest propensity to generate seizures.
Aberrant sensory processing plays a fundamental role in the pathophysiology of dystonia; however, its underpinning neural mechanisms in relation to dystonia phenotype and genotype remain unclear. We examined temporal and spatial discrimination thresholds in patients with isolated laryngeal form of dystonia (LD), who exhibited different clinical phenotypes (adductor vs. abductor forms) and potentially different genotypes (sporadic vs. familial forms). We correlated our behavioral findings with the brain gray matter volume and functional activity during resting and symptomatic speech production. We found that temporal but not spatial discrimination was significantly altered across all forms of LD, with higher frequency of abnormalities seen in familial than sporadic patients. Common neural correlates of abnormal temporal discrimination across all forms were found with structural and functional changes in the middle frontal and primary somatosensory cortices. In addition, patients with familial LD had greater cerebellar involvement in processing of altered temporal discrimination, whereas sporadic LD patients had greater recruitment of the putamen and sensorimotor cortex. Based on the clinical phenotype, adductor form-specific correlations between abnormal discrimination and brain changes were found in the frontal cortex, whereas abductor form-specific correlations were observed in the cerebellum and putamen. Our behavioral and neuroimaging findings outline the relationship of abnormal sensory discrimination with the phenotype and genotype of isolated LD, suggesting the presence of potentially divergent pathophysiological pathways underlying different manifestations of this disorder.
Speech is one of the most unique features of human communication. Our ability to articulate our thoughts by means of speech production depends critically on the integrity of the motor cortex. Long thought to be a low-order brain region, exciting work in the past years is overturning this notion. Here, we highlight some of major experimental advances in speech motor control research and discuss the emerging findings about the complexity of speech motocortical organization and its large-scale networks. This review summarizes the talks presented at a symposium at the Annual Meeting of the Society of Neuroscience; it does not represent a comprehensive review of contemporary literature in the broader field of speech motor control.
The analysis of the community architecture in functional brain networks has revealed important relations between specific behavioral patterns and characteristic features of the associated functional organization. Numerous studies have assessed changes in functional communities during different states of awareness, learning, information processing, and various behavioral patterns. The robustness of detected communities within a network has been an often-discussed topic in complex systems research. However, our knowledge regarding the intersubject stability of functional communities in the human brain while performing different tasks is still lacking. In this study, we examined the variability of functional communities in weighted undirected graphs based on fMRI recordings of healthy participants across three conditions: the resting state, syllable production as a simple vocal motor task, and meaningful speech production representing a complex behavioral pattern with cognitive involvement. On the basis of the constructed empirical networks, we simulated a large cohort of artificial graphs and performed a leave-one-out stability analysis to assess the sensitivity of communities in the group-averaged networks with respect to perturbations in the averaging cohort. We found that the stability of partitions derived from group-averaged networks depended on task complexity. The determined community architecture in mean networks reflected within-behavior network stability and between-behavior flexibility of the human functional connectome. The sensitivity of functional communities increased from rest to syllable production to speaking, which suggests that the approximation quality of the community structure in the average network to reflect individual per-participant partitions depends on task complexity.
UNLABELLED: The laryngeal motor cortex (LMC) is essential for the production of learned vocal behaviors because bilateral damage to this area renders humans unable to speak but has no apparent effect on innate vocalizations such as human laughing and crying or monkey calls. Several hypotheses have been put forward attempting to explain the evolutionary changes from monkeys to humans that potentially led to enhanced LMC functionality for finer motor control of speech production. These views, however, remain limited to the position of the larynx area within the motor cortex, as well as its connections with the phonatory brainstem regions responsible for the direct control of laryngeal muscles. Using probabilistic diffusion tractography in healthy humans and rhesus monkeys, we show that, whereas the LMC structural network is largely comparable in both species, the LMC establishes nearly 7-fold stronger connectivity with the somatosensory and inferior parietal cortices in humans than in macaques. These findings suggest that important "hard-wired" components of the human LMC network controlling the laryngeal component of speech motor output evolved from an already existing, similar network in nonhuman primates. However, the evolution of enhanced LMC-parietal connections likely allowed for more complex synchrony of higher-order sensorimotor coordination, proprioceptive and tactile feedback, and modulation of learned voice for speech production. SIGNIFICANCE STATEMENT: The role of the primary motor cortex in the formation of a comprehensive network controlling speech and language has been long underestimated and poorly studied. Here, we provide comparative and quantitative evidence for the significance of this region in the control of a highly learned and uniquely human behavior: speech production. From the viewpoint of structural network organization, we discuss potential evolutionary advances of enhanced temporoparietal cortical connections with the laryngeal motor cortex in humans compared with nonhuman primates that may have contributed to the development of finer vocal motor control necessary for speech production.
Laryngeal dystonia (LD) is a task-specific focal dystonia of unknown pathophysiology affecting speech production. We examined the demographics of anecdotally reported alcohol use and its effects on LD symptoms using an online survey based on Research Electronic Data Capture (REDCap™) and National Spasmodic Dysphonia Association's patient registry. From 641 participants, 531 were selected for data analysis, and 110 were excluded because of unconfirmed diagnosis. A total of 406 patients (76.5 %) had LD and 125 (23.5 %) had LD and voice tremor (LD/VT). The consumption of alcohol was reported by 374 LD (92.1 %) and 109 LD/VT (87.2 %) patients. Improvement of voice symptoms after alcohol ingestion was noted by 227 LD (55.9 % of all patients) and 73 LD/VT (58.4 %), which paralleled the improvement observed by patient's family and/or friends in 214 LD (57.2 %) and 69 LD/VT (63.3 %) patients. The benefits lasted 1-3 h in both groups with the maximum effect after 2 drinks in LD patients (p = 0.002), whereas LD/VT symptoms improved independent of the consumed amount (p = 0.48). Our data suggest that isolated dystonic symptoms, such as in LD, are responsive to alcohol intake and this responsiveness is not attributed to the presence of VT, which is known to have significant benefits from alcohol ingestion. Alcohol may modulate the pathophysiological mechanisms underlying abnormal neurotransmission of γ-aminobutyric acid (GABA) in dystonia and as such provide new avenues for novel therapeutic options in these patients.
In the past few years, several studies have been directed to understanding the complexity of functional interactions between different brain regions during various human behaviors. Among these, neuroimaging research installed the notion that speech and language require an orchestration of brain regions for comprehension, planning, and integration of a heard sound with a spoken word. However, these studies have been largely limited to mapping the neural correlates of separate speech elements and examining distinct cortical or subcortical circuits involved in different aspects of speech control. As a result, the complexity of the brain network machinery controlling speech and language remained largely unknown. Using graph theoretical analysis of functional MRI (fMRI) data in healthy subjects, we quantified the large-scale speech network topology by constructing functional brain networks of increasing hierarchy from the resting state to motor output of meaningless syllables to complex production of real-life speech as well as compared to non-speech-related sequential finger tapping and pure tone discrimination networks. We identified a segregated network of highly connected local neural communities (hubs) in the primary sensorimotor and parietal regions, which formed a commonly shared core hub network across the examined conditions, with the left area 4p playing an important role in speech network organization. These sensorimotor core hubs exhibited features of flexible hubs based on their participation in several functional domains across different networks and ability to adaptively switch long-range functional connectivity depending on task content, resulting in a distinct community structure of each examined network. Specifically, compared to other tasks, speech production was characterized by the formation of six distinct neural communities with specialized recruitment of the prefrontal cortex, insula, putamen, and thalamus, which collectively forged the formation of the functional speech connectome. In addition, the observed capacity of the primary sensorimotor cortex to exhibit operational heterogeneity challenged the established concept of unimodality of this region.
OBJECTIVE: To present the first documented series of patients with negative dystonia (ND) of the palate, including clinical symptoms, functional MRI findings, and management options. STUDY DESIGN: Case series ascertained from clinical research centers that evaluated patients with both hyperkinetic and hypokinetic movement disorders. METHODS: Between July 1983 and March 2013, data was collected on patient demographics, disease characteristics, functional MRI findings, long-term management options, and outcomes. We sought patients whose clinical examination demonstrated absent palatal movement on speaking, despite normal palatal activity on other activities. RESULTS: Five patients (2 males, 3 females) met clinical criteria. All patients presented with hypernasal speech without associated dysphagia. Clinical examination revealed absent palatal movement on speaking despite intact gag reflexes, normal palate elevation on swallowing, and normal cranial nerve examinations. Other cranial and/or limb dystonias were present in four patients (80.0%). Three patients (60.0%) had previously failed oral pharmacologic therapy. Two patients underwent functional magnetic resonance imaging (fMRI) studies, which demonstrated an overall decrease of cortical and subcortical activation during production of symptomatic syllables and asymptomatic coughing. Management included speech therapy (all patients) and palatal lift (2 patients) with limited improvement. Calcium hydroxyapatite injection (1 patient) into the soft palate and Passavants' ridge was beneficial. CONCLUSIONS: This is the first report of ND of the palate. Characteristic findings were task-specific absent palatal movement with speech, despite normal movement on swallowing, coughing, and an intact gag reflex, as well as disorder-specific decreased brain activation on functional MRI. A diagnosis of ND of the palate should be considered for patients who present with hypernasal speech. LEVEL OF EVIDENCE: 4.
Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network.
Our ability to learn and control the motor aspects of complex laryngeal behaviors, such as speech and song, is modulated by the laryngeal motor cortex (LMC), which is situated in the area 4 of the primary motor cortex and establishes both direct and indirect connections with laryngeal motoneurons. In contrast, the LMC in monkeys is located in the area 6 of the premotor cortex, projects only indirectly to laryngeal motoneurons and its destruction has essentially no effect on production of species-specific calls. These differences in cytoarchitectonic location and connectivity may be a result of hominid evolution that led to the LMC shift from the phylogenetically 'old' to 'new' motor cortex in order to fulfill its paramount function, that is, voluntary motor control of human speech and song production.
Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number of extensions of the proposed methodology building upon the current model.
Numerous brain imaging studies have demonstrated structural changes in the basal ganglia, thalamus, sensorimotor cortex, and cerebellum across different forms of primary dystonia. However, our understanding of brain abnormalities contributing to the clinically well-described phenomenon of task specificity in dystonia remained limited. We used high-resolution magnetic resonance imaging (MRI) with voxel-based morphometry and diffusion weighted imaging with tract-based spatial statistics of fractional anisotropy to examine gray and white matter organization in two task-specific dystonia forms, writer's cramp and laryngeal dystonia, and two non-task-specific dystonia forms, cervical dystonia and blepharospasm. A direct comparison between both dystonia forms indicated that characteristic gray matter volumetric changes in task-specific dystonia involve the brain regions responsible for sensorimotor control during writing and speaking, such as primary somatosensory cortex, middle frontal gyrus, superior/inferior temporal gyrus, middle/posterior cingulate cortex, and occipital cortex as well as the striatum and cerebellum (lobules VI-VIIa). These gray matter changes were accompanied by white matter abnormalities in the premotor cortex, middle/inferior frontal gyrus, genu of the corpus callosum, anterior limb/genu of the internal capsule, and putamen. Conversely, gray matter volumetric changes in the non-task-specific group were limited to the left cerebellum (lobule VIIa) only, whereas white matter alterations were found to underlie the primary sensorimotor cortex, inferior parietal lobule, and middle cingulate gyrus. Distinct microstructural patterns in task-specific and non-task-specific dystonias may represent neuroimaging markers and provide evidence that these two dystonia subclasses likely follow divergent pathophysiological mechanisms precipitated by different triggers.