Previous studies have shown greater atrophy in grey and white matter of various brain regions in patients with Parkinson's disease with mild cognitive impairment than in those without. These anatomical differences likely account for the distinct clinical profiles observed between those groups, but do not account for the evolution of regional brain degradation observed as the disease evolves. Although we have shown recently that cortical thinning correlates significantly more with disease duration in Parkinson's patients with mild cognitive impairment than in those without, to the best of our knowledge no study to date has explored this longitudinally. The present study investigated the longitudinal changes of the cortical and subcortical grey matter in patients with Parkinson's disease with and without mild cognitive impairment. Additionally, these two groups were compared with healthy controls. We found a higher rate of cortical thinning in the temporal, occipital, parietal and supplementary motor area, in patients with Parkinson's disease with mild cognitive impairment compared with both cognitively stable patients and healthy controls. On the other hand cognitively stable patients had only one lateral occipital and one fusiform cluster with increased rate of thinning compared with healthy individuals. Correlating the rate of change of cortical thickness with the results of Montreal Cognitive Assessment scores revealed significant thinning associated with cognitive decline in the group of all patients, in similar regions including temporal and medial occipital lobe. Finally, a significant decrease in the volume of the amygdala and nucleus accumbens was observed specifically in patients with Parkinson's disease with mild cognitive impairment. These results indicate that the early presence of mild cognitive impairment in patients with Parkinson's disease is associated with a faster rate of grey matter thinning in various cortical regions as well as a significant diminishment of limbic subcortical structures. This specific pattern of brain degradation associated with the early presence of mild cognitive impairment might serve as a marker of development toward dementia.

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Idiopathic Parkinson's disease (PD) is a neurodegenerative disorder characterized by the dysfunction of dopaminergic dependent cortico-basal ganglia loops and diagnosed on the basis of motor symptoms (tremors and/or rigidity and bradykinesia). Post-mortem studies tend to show that the destruction of dopaminergic neurons in the substantia nigra constitutes an intermediate step in a broader neurodegenerative process rather than a unique feature of Parkinson's disease, as a consistent pattern of progression would exist, originating from the medulla oblongata/pontine tegmentum. To date, neuroimaging techniques have been unable to characterize the pre-symptomatic stages of PD. However, if such a regular neurodegenerative pattern were to exist, consistent damages would be found in the brain stem, even at early stages of the disease. We recruited 23 PD patients at Hoenn and Yahr stages I to II of the disease and 18 healthy controls (HC) matched for age. T1-weighted anatomical scans were acquired (MPRAGE, 1 mm3 resolution) and analyzed using an optimized VBM protocol to detect white and grey matter volume reduction without spatial a priori. When the HC group was compared to the PD group, a single cluster exhibited statistical difference (p<0.05 corrected for false detection rate, 4287 mm3) in the brain stem, between the pons and the medulla oblongata. The present study provides in-vivo evidence that brain stem damage may be the first identifiable stage of PD neuropathology, and that the identification of this consistent damage along with other factors could help with earlier diagnosis in the future. This damage could also explain some non-motor symptoms in PD that often precede diagnosis, such as autonomic dysfunction and sleep disorders.

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Mild cognitive impairment (MCI) can occur early in the course of Parkinson's disease (PD), and its presence increases the risk of developing dementia. Determining the cortical changes associated with MCI in PD, thus, may be useful in predicting the future development of dementia. To address this objective, 37 patients with PD, divided into 2 groups according to the presence or absence MCI (18 with and 19 without) and 16 matched controls, underwent anatomic magnetic resonance imaging. Corticometry analyses were performed to measure the changes in cortical thickness and surface area as well as their correlation with disease duration. Compared with healthy controls, the PD-MCI group exhibited increased atrophy and changes of local surface area in the bilateral occipital, left temporal, and frontal cortices; whereas the PD non-MCI group exhibited only unilateral thinning and decreased surface area in the occipital lobe and in the frontal cortex. In addition, a comparison between the PD-MCI and PD non-MCI groups revealed increased local surface area in the occipital lobe, temporal lobe, and postcentral gyrus for the cognitively impaired patients. It is noteworthy that, in the PD-MCI group, cortical thickness had a significant negative correlation with disease duration in the precentral, supramarginal, occipital, and superior temporal cortices; whereas, in the PD non-MCI group, such a correlation was absent. The findings from this study reveal that, at the same stage of PD evolution, the presence of MCI is associated with a higher level of cortical changes, suggesting that cortical degeneration is increased in patients with PD because of the presence of MCI.

Background: Genetic, biologic and clinical data suggest that Parkinson's disease (PD) is an umbrella for multiple disorders with clinical and pathological overlap, yet with different underlying mechanisms. To better understand these and to move towards neuroprotective treatment, we have established the Quebec Parkinson Network (QPN), an open-access patient registry, and data and bio-samples repository. Objective: To present the QPN and to perform preliminary analysis of the QPN data. Methods: A total of 1,070 consecutively recruited PD patients were included in the analysis. Demographic and clinical data were analyzed, including comparisons between males and females, PD patients with and without RBD, and stratified analyses comparing early and late-onset PD and different age groups. Results: QPN patients exhibit a male:female ratio of 1.8:1, an average age-at-onset of 58.6 years, an age-at-diagnosis of 60.4 years, and average disease duration of 8.9 years. REM-sleep behavior disorder (RBD) was more common among men, and RBD was associated with other motor and non-motor symptoms including dyskinesia, fluctuations, postural hypotension and hallucinations. Older patients had significantly higher rates of constipation and cognitive impairment, and longer disease duration was associated with higher rates of dyskinesia, fluctuations, freezing of gait, falls, hallucinations and cognitive impairment. Since QPN's creation, over 60 studies and 30 publications have included patients and data from the QPN. Conclusions: The QPN cohort displays typical PD demographics and clinical features. These data are open-access upon application (http://rpq-qpn.ca/en/), and will soon include genetic, imaging and bio-samples. We encourage clinicians and researchers to perform studies using these resources.

Motor studies of Parkinson's disease (PD) have shown cortical hypo-activity in relation to nigrostriatal dopamine depletion. Cognitive studies also identified increased cortical activity in PD. We have previously suggested that the hypo-activity/hyper-activity patterns observed in PD are related to the striatal contribution. Tasks that recruit the striatum in control participants are associated with cortical hypo-activity in patients with PD, whereas tasks that do not result in cortical hyper-activity. The putamen, a structure affected by the neurodegeneration observed in PD, shows increased activation for externally-triggered (ET) and self-initiated (SI) movements. The first goal of this study was to evaluate the effect of levodopa on the putamen's response to ET and SI movements. Our second goal was to assess the effect of levodopa on the hypo-activity/hyper-activity patterns in cortical areas. Patients with PD on and off levodopa and healthy volunteers performed SI, ET and control finger movements during functional magnetic resonance imaging. Healthy participants displayed significant differences in putamen activity in ET and SI movements. These differences were reduced in patients off medication, with non-task-specific increases in activity after levodopa administration. Furthermore, the ventrolateral prefrontal cortex showed significant increases in activity during SI movements in healthy controls, whereas it was hypo-active in PD. This region showed significantly increased activity during ET movements in patients off medication. Levodopa had no effect on this discrepancy. Our results suggest that dopamine replacement therapy has a non-task-specific effect on motor corticostriatal regions, and support the hypothesis that increases and decreases in cortical activity in PD are related to the mesocortical dopamine pathway imbalance.

Data sharing is becoming more of a requirement as technologies mature and as global research and communications diversify. As a result, researchers are looking for practical solutions, not only to enhance scientific collaborations, but also to acquire larger amounts of data, and to access specialized datasets. In many cases, the realities of data acquisition present a significant burden, therefore gaining access to public datasets allows for more robust analyses and broadly enriched data exploration. To answer this demand, the Montreal Neurological Institute has announced its commitment to Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016a,b). As such, the LORIS and CBRAIN (Das et al., 2016) platforms have been tasked with the technical challenges specific to the institutional-level implementation of open data sharing, including: Comprehensive linking of multimodal data (phenotypic, clinical, neuroimaging, biobanking, and genomics, etc.)Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring subject confidentiality (using multi-tiered identifiers).Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented and de-identified subject data.Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for rapid data processing and sharing of software tools.Robust Workflows and Quality Control mechanisms ensuring transparency and consistency in best practices.Long term storage (and web access) of data, reducing loss of institutional data assets.Enhanced web-based visualization of imaging, genomic, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards.Implementing the vision of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing for the global research community. Our goal is to utilize the years of experience in multi-site collaborative research infrastructure to implement the technical requirements to achieve this level of public data sharing in a practical yet robust manner, in support of accelerating scientific discovery.