Speech dysprosody but no music ‘dysprosody’ in Parkinson’s disease

AbstractParkinson’s disease is characterized not only by bradykinesia, rigidity, and tremor, but also by impairments of expressive and receptive linguistic prosody. The facilitating effect of music with a salient beat on patients’ gait suggests that it might have a similar effect on vocal behavior, however it is currently unknown whether singing is affected by the disease. In the present study, fifteen Parkinson patients were compared with fifteen healthy controls during the singing of familiar melodies and improvised melodic continuations. While patients’ speech could reliably be distinguished from that of healthy controls matched for age and gender, purely on the basis of aural perception, no significant differences in singing were observed, either in pitch, pitch range, pitch variability, and tempo, or in scale tone distribution, interval size or interval variability. The apparent dissociation of speech and singing in Parkinson’s disease suggests that music could be used to facilitate expressive linguistic prosody

Circuit imaging biomarkers in preclinical and prodromal Parkinson's disease

Abstract Parkinson’s disease (PD) commences several years before the onset of motor features. Pathophysiological understanding of the pre-clinical or early prodromal stages of PD are essential for the development of new therapeutic strategies. Two categories of patients are ideal to study the early disease stages. Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents a well-known prodromal stage of PD in which pathology is presumed to have reached the lower brainstem. The majority of patients with iRBD will develop manifest PD within years to decades. Another category encompasses non-manifest mutation carriers, i.e. subjects without symptoms, but with a known mutation or genetic variant which gives an increased risk of developing PD. The speed of progression from preclinical or prodromal to full clinical stages varies among patients and cannot be reliably predicted on the individual level. Clinical trials will require inclusion of patients with a predictable conversion within a limited time window. Biomarkers are necessary that can confirm pre-motor PD status and can provide information regarding lead time and speed of progression. Neuroimaging changes occur early in the disease process and may provide such a biomarker. Studies have focused on radiotracer imaging of the dopaminergic nigrostriatal system, which can be assessed with dopamine transporter (DAT) single photon emission computed tomography (SPECT). Loss of DAT binding represents an effect of irreversible structural damage to the nigrostriatal system. This marker can be used to monitor disease progression and identify individuals at specific risk for phenoconversion. However, it is known that changes in neuronal activity precede structural changes. Functional neuro-imaging techniques, such as 18F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography (18F-FDG PET) and functional magnetic resonance imaging (fMRI), can be used to model the effects of disease on brain networks when combined with advanced analytical methods. Because these changes occur early in the disease process, functional imaging studies are of particular interest in prodromal PD diagnosis. In addition, fMRI and 18F-FDG PET may be able to predict a specific future phenotype in prodromal cohorts, which is not possible with DAT SPECT. The goal of the current review is to discuss the network-level brain changes in pre-motor PD

Handedness correlates with the dominant parkinson side:A systematic review and meta-analysis

Parkinson's disease (PD) characteristically presents with asymmetrical symptoms, contralateral to the side of the most extensive cerebral affection. This intriguing asymmetry, even included in the definition for diagnosing PD, however, is still part of a mystery. The relation with handedness as a common indicator of cerebral asymmetry might provide a clue in the search for causal factors of asymmetrical symptom onset in PD. This possible relationship, however, is still under debate. The objective of this study was to establish whether a relation between handedness and dominant PD side exists. We searched for cross-sectional or cohort studies that registered handedness and onset side in PD patients in PubMed, EMBASE, and Web of Science from their first record until 14 February 2011. Data about handedness and dominant PD side was extracted. Authors who registered both but not described their relation were contacted for further information. Odds ratios (ORs) were analyzed with a fixed effect Mantel-Haenszel model. Heterogeneity and indications of publication bias were limited. Our electronic search identified 10 studies involving 4405 asymmetric PD patients. Of the right-handed patients, 2413 (59.5%) had right-dominant and 1644 (40.5%) had left-dominant PD symptoms. For the left-handed patients this relation was reversed, with 142 (40.8%) right-dominant and 206 (59.2%) left-dominant PD symptoms. Overall OR was 2.13 (95% confidence interval [CI], 1.712.66). Handedness and symptom dominance in PD are firmly related with each other in such a way that the PD symptoms emerge more often on the dominant hand-side. Possible causal factors are discussed. (C) 2011 Movement Disorder Societ

Sentence Comprehension and Its Association with Executive Functions in Patients with Parkinson's Disease

Coexistent impairments in executive functions and language comprehension in patients with Parkinson's disease (PD) have been repeatedly observed. In this study, the aim was to provide insights into the interaction between linguistic representation and processing and executive functioning. Therefore, sentence comprehension and executive functions were assessed in 28 Dutch-speaking PD patients and 28 healthy control subjects. Three aspects of the sentence materials were varied: (1) phrase structure complexity, (2) sentence length, and (3) picture congruence. PD patients with mild-to-moderate disease severity showed decreased sentence comprehension compared to healthy control subjects. The difficulties encountered by PD patients were not limited to one aspect of the sentence materials. The same pattern of results was present in healthy control subjects. Deficits in set-switching were specifically associated with the comprehension of passive sentences. Generally, our study confirms that there does not appear to be a language faculty encapsulated from the influence of executive functions

Abnormal Parietal Function in Conversion Paresis

The etiology of medically unexplained symptoms such as conversion disorder is poorly understood. This is partly because the interpretation of neuroimaging results in conversion paresis has been complicated by the use of different control groups, tasks and statistical comparisons. The present study includes these different aspects in a single data set. In our study we included both normal controls and feigners to control for conversion paresis. We studied both movement execution and imagery, and we contrasted both within-group and between-group activation. Moreover, to reveal hemisphere-specific effects that have not been reported before, we performed these analyses using both flipped and unflipped data. This approach resulted in the identification of abnormal parietal activation which was specific for conversion paresis patients. Patients also showed reduced activity in the prefrontal cortex, supramarginal gyrus and precuneus, including hemisphere-specific activation that is lateralized in the same hemisphere, regardless of right- or left-sided paresis. We propose that these regions are candidates for an interface between psychological mechanisms and disturbed higher-order motor control. Our study presents an integrative neurophysiological view of the mechanisms that contribute to the etiology of this puzzling psychological disorder, which can be further investigated with other types of conversion symptoms

Occipital hypometabolism is a risk factor for conversion to Parkinson’s disease in isolated REM sleep behaviour disorder

Purpose: Isolated REM sleep behaviour disorder (iRBD) patients are at high risk of developing clinical syndromes of the α-synuclein spectrum. Progression markers are needed to determine the neurodegenerative changes and to predict their conversion. Brain imaging with 18F-FDG PET in iRBD is promising, but longitudinal studies are scarce. We investigated the regional brain changes in iRBD over time, related to phenoconversion.Methods: Twenty iRBD patients underwent two consecutive 18F-FDG PET brain scans and clinical assessments (3.7 ± 0.6 years apart). Seventeen patients also underwent 123I-MIBG and 123I-FP-CIT SPECT scans at baseline. Four subjects phenoconverted to Parkinson’s disease (PD) during follow-up. 18F-FDG PET scans were compared to controls with a voxel-wise single-subject procedure. The relationship between regional brain changes in metabolism and PD-related pattern scores (PDRP) was investigated.Results: Individual hypometabolism t-maps revealed three scenarios: (1) normal 18F-FDG PET scans at baseline and follow-up (N = 10); (2) normal scans at baseline but occipital or occipito-parietal hypometabolism at follow-up (N = 4); (3) occipital hypometabolism at baseline and follow-up (N = 6). All patients in the last group had pathological 123I-MIBG and 123I-FP-CIT SPECT. iRBD converters (N = 4) showed occipital hypometabolism at baseline (third scenario). At the group level, hypometabolism in the frontal and occipito-parietal regions and hypermetabolism in the cerebellum and limbic regions were progressive over time. PDRP z-scores increased over time (0.54 ± 0.36 per year). PDRP expression was driven by occipital hypometabolism and cerebellar hypermetabolism.Conclusions: Our results suggest that occipital hypometabolism at baseline in iRBD implies a short-term conversion to PD. This might help in stratification strategies for disease-modifying trials.</p

Parkinson-Related Changes of Activation in Visuomotor Brain Regions during Perceived Forward Self-Motion

Radial expanding optic flow is a visual consequence of forward locomotion. Presented on screen, it generates illusionary forward self-motion, pointing at a close vision-gait interrelation. As particularly parkinsonian gait is vulnerable to external stimuli, effects of optic flow on motor-related cerebral circuitry were explored with functional magnetic resonance imaging in healthy controls (HC) and patients with Parkinson's disease (PD). Fifteen HC and 22 PD patients, of which 7 experienced freezing of gait (FOG), watched wide-field flow, interruptions by narrowing or deceleration and equivalent control conditions with static dots. Statistical parametric mapping revealed that wide-field flow interruption evoked activation of the (pre-)supplementary motor area (SMA) in HC, which was decreased in PD. During wide-field flow, dorsal occipito-parietal activations were reduced in PD relative to HC, with stronger functional connectivity between right visual motion area V5, pre-SMA and cerebellum (in PD without FOG). Non-specific 'changes' in stimulus patterns activated dorsolateral fronto-parietal regions and the fusiform gyrus. This attention-associated network was stronger activated in HC than in PD. PD patients thus appeared compromised in recruiting medial frontal regions facilitating internally generated virtual locomotion when visual motion support falls away. Reduced dorsal visual and parietal activations during wide-field optic flow in PD were explained by impaired feedforward visual and visuomotor processing within a magnocellular (visual motion) functional chain. Compensation of impaired feedforward processing by distant fronto-cerebellar circuitry in PD is consistent with motor responses to visual motion stimuli being either too strong or too weak. The 'change'-related activations pointed at covert (stimulus-driven) attention

Lateral and Medial Ventral Occipitotemporal Regions Interact During the Recognition of Images Revealed from Noise

Several studies suggest different functional roles for the medial and the lateral sections of the ventral visual cortex in object recognition. Texture and surface information is processed in medial sections, while shape information is processed in lateral sections. This begs the question whether and how these functionally specialized sections interact with each other and with early visual cortex to facilitate object recognition. In the current research, we set out to answer this question. In an fMRI study, 13 subjects viewed and recognized images of objects and animals that were gradually revealed from noise while their brains were being scanned. We applied dynamic causal modeling (DCM) a method to characterize network interactions to determine the modulatory effect of object recognition on a network comprising the primary visual cortex (V1), the lingual gyrus (LG) in medial ventral cortex and the lateral occipital cortex (LO). We found that object recognition modulated the bilateral connectivity between LG and LO. Moreover, the feed-forward connectivity from Vito LG and LO was modulated, while there was no evidence for feedback from these regions to V1 during object recognition. In particular, the interaction between medial and lateral areas supports a framework in which visual recognition of objects is achieved by networked regions that integrate information on image statistics, scene content and shape rather than by a single categorically specialized region within the ventral visual cortex

FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder

Background and Objectives 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with principal component analysis (PCA) has been applied to identify disease-related brain patterns in neurodegenerative disorders such as Parkinson’s disease (PD), Dementia with Lewy Bodies (DLB) and Alzheimer’s disease (AD). These patterns are used to quantify functional brain changes at the single subject level. This is especially relevant in determining disease progression in idiopathic REM sleep behavior disorder (iRBD), a prodromal stage of PD and DLB. However, the PCA method is limited in discriminating between neurodegenerative conditions. More advanced machine learning algorithms may provide a solution. In this study, we apply Generalized Matrix Learning Vector Quantization (GMLVQ) to FDG-PET scans of healthy controls, and patients with AD, PD and DLB. Scans of iRBD patients, scanned twice with an approximate 4 year interval, were projected into GMLVQ space to visualize their trajectory. Methods We applied a combination of SSM/PCA and GMLVQ as a classifier on FDG-PET data of healthy controls, AD, DLB, and PD patients. We determined the diagnostic performance by performing a ten times repeated ten fold cross validation. We analyzed the validity of the classification system by inspecting the GMLVQ space. First by the projection of the patients into this space. Second by representing the axis, that span this decision space, into a voxel map. Furthermore, we projected a cohort of RBD patients, whom have been scanned twice (approximately 4 years apart), into the same decision space and visualized their trajectories. Results The GMLVQ prototypes, relevance diagonal, and decision space voxel maps showed metabolic patterns that agree with previously identified disease-related brain patterns. The GMLVQ decision space showed a plausible quantification of FDG-PET data. Distance traveled by iRBD subjects through GMLVQ space per year (i.e. velocity) was correlated with the change in motor symptoms per year (Spearman’s rho =0.62, P=0.004). Conclusion In this proof-of-concept study, we show that GMLVQ provides a classification of patients with neurodegenerative disorders, and may be useful in future studies investigating speed of progression in prodromal disease stages