Cognitive impairment in Parkinson's disease (PD) is related to the reorganization of brain topology. Although drug challenge studies have proven how levodopa treatment can modulate functional connectivity in brain circuits, the role of chronic dopaminergic therapy on cognitive status and functional connectivity has never been investigated. We sought to characterize brain functional topology in mid-stage PD patients under chronic antiparkinson treatment and explore the presence of correlation between reorganization of brain architecture and specific cognitive deficits. We explored networks topology and functional connectivity in 16 patients with PD and 16 matched controls through a graph theoretical analysis of resting state-functional MRI data, and evaluated the relationships between network metrics and cognitive performance. PD patients showed a preserved small-world network topology but a lower clustering coefficient in comparison with healthy controls. Locally, PD patients showed lower degree of connectivity and local efficiency in many hubs corresponding to functionally relevant areas. Four disconnected subnetworks were also identified in regions responsible for executive control, sensory-motor control and planning, motor coordination and visual elaboration. Executive functions and information processing speed were directly correlated with degree of connectivity and local efficiency in frontal, parietal and occipital areas. While functional reorganization appears in both motor and cognitive areas, the clinical expression of network imbalance seems to be partially compensated by the chronic levodopa treatment with regards to the motor but not to the cognitive performance. In a context of reduced network segregation, the presence of higher local efficiency in hubs regions correlates with a better cognitive performance.

Focal dystonias are the most common type of isolated dystonia. Although their causative pathophysiology remains unclear, it is thought to involve abnormal functioning of the basal ganglia-thalamo-cortical circuitry. We used high-resolution research tomography with the radioligand 11C-NNC-112 to examine striatal dopamine D₁ receptor function in two independent groups of patients, writer’s cramp and laryngeal dystonia, compared to healthy controls. We found that availability of dopamine D₁ receptors was significantly increased in bilateral putamen by 19.6–22.5% in writer’s cramp and in right putamen and caudate nucleus by 24.6–26.8% in laryngeal dystonia (all P ≤ 0.009). This suggests hyperactivity of the direct basal ganglia pathway in focal dystonia. Our findings paralleled abnormally decreased dopaminergic function via the indirect basal ganglia pathway and decreased symptom-induced phasic striatal dopamine release in writer’s cramp and laryngeal dystonia. When examining topological distribution of dopamine D₁ and D₂ receptor abnormalities in these forms of dystonia, we found abnormal separation of direct and indirect pathways within the striatum, with negligible, if any, overlap between the two pathways and with the regions of phasic dopamine release. However, despite topological disorganization of dopaminergic function, alterations of dopamine D₁ and D₂ receptors were somatotopically localized within the striatal hand and larynx representations in writer’s cramp and laryngeal dystonia, respectively. This finding points to their direct relevance to disorder-characteristic clinical features. Increased D₁ receptor availability showed significant negative correlations with dystonia duration but not its severity, likely representing a developmental endophenotype of this disorder. In conclusion, a comprehensive pathophysiological mechanism of abnormal basal ganglia function in focal dystonia is built upon upregulated dopamine D₁ receptors that abnormally increase excitation of the direct pathway, downregulated dopamine D₂receptors that abnormally decrease inhibition within the indirect pathway, and weakened nigro-striatal phasic dopamine release during symptomatic task performance. Collectively, these aberrations of striatal dopaminergic function underlie imbalance between direct and indirect basal ganglia pathways and lead to abnormal thalamo-motor-cortical hyperexcitability in dystonia.

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: Up to 12% of patients with laryngeal dystonia report a familial history of dystonia, pointing to involvement of genetic factors. However, its genetic causes remain unknown. METHOD: Using Sanger sequencing, we screened 57 patients with isolated laryngeal dystonia for mutations in known dystonia genes TOR1A (DYT1), THAP1 (DYT6), TUBB4A (DYT4), and GNAL (DYT25). Using functional MRI, we explored the influence of the identified mutation on brain activation during symptomatic task production. RESULTS: We identified 1 patient with laryngeal dystonia who was a GNAL mutation carrier. When compared with 26 patients without known mutations, the GNAL carrier had increased activity in the fronto-parietal cortex and decreased activity in the cerebellum. CONCLUSIONS: Our data show that GNAL mutation may represent one of the rare causative genetic factors of isolated laryngeal dystonia. Exploratory evidence of distinct neural abnormalities in the GNAL carrier may suggest the presence of divergent pathophysiological cascades underlying this disorder. © 2016 International Parkinson and Movement Disorder Society.

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.

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.

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.

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.

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.