scholarly journals Parkinson's Disease—Related Spatial Covariance Pattern Identified with Resting-State Functional MRI

2015 ◽  
Vol 35 (11) ◽  
pp. 1764-1770 ◽  
Author(s):  
Tao Wu ◽  
Yilong Ma ◽  
Zheng Zheng ◽  
Shichun Peng ◽  
Xiaoli Wu ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Mri ◽  
Neural Activity ◽  
Resting State ◽  
Healthy Controls ◽  
Sample Analysis ◽  
Spatial Covariance ◽  
Control Subjects ◽  
Split Sample

In this study, we sought to identify a disease-related spatial covariance pattern of spontaneous neural activity in Parkinson's disease using resting-state functional magnetic resonance imaging (MRI). Time-series data were acquired in 58 patients with early to moderate stage Parkinson's disease and 54 healthy controls, and analyzed by Scaled Subprofile Model Principal Component Analysis toolbox. A split-sample analysis was also performed in a derivation sample of 28 patients and 28 control subjects and validated in a prospective testing sample of 30 patients and 26 control subjects. The topographic pattern of neural activity in Parkinson's disease was characterized by decreased activity in the striatum, supplementary motor area, middle frontal gyrus, and occipital cortex, and increased activity in the thalamus, cerebellum, precuneus, superior parietal lobule, and temporal cortex. Pattern expression was elevated in the patients compared with the controls, with a high accuracy (90%) to discriminate the patients from the controls. The split-sample analysis produced a similar pattern but with a lower accuracy for group discrimination in both the derivation (80%) and the validation (73%) samples. Our results showed that resting-state functional MRI can be potentially useful for identification of Parkinson's disease–related spatial covariance patterns, and for differentiation of Parkinson's disease patients from healthy controls at an individual level.

scholarly journals Parkinson's disease-related network topographies characterized with resting state functional MRI

2016 ◽  
Vol 38 (2) ◽  
pp. 617-630 ◽  
Author(s):  
An Vo ◽  
Wataru Sako ◽  
Koji Fujita ◽  
Shichun Peng ◽  
Paul J. Mattis ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Mri ◽  
Resting State

scholarly journals The Relationship between Side of Onset and Cerebral Regional Homogeneity in Parkinson’s Disease: A Resting-State fMRI Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Kai Li ◽  
Hong Zhao ◽  
Chun-Mei Li ◽  
Xin-Xin Ma ◽  
Min Chen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Mri ◽  
Resting State ◽  
Brain Activity ◽  
Regional Homogeneity ◽  
Depression And Anxiety ◽  
Significant Difference ◽  
Temporal Pole ◽  
The Right

Objective. Motor symptoms are usually asymmetric in Parkinson’s disease (PD), and asymmetry in PD may involve widespread brain areas. We sought to evaluate the effect of asymmetry on the whole brain spontaneous activity using the measure regional homogeneity (ReHo) through resting-state functional MRI. Methods. We recruited 30 PD patients with left onset (LPD), 27 with right side (RPD), and 32 controls with satisfactory data. Their demographic, clinical, and neuropsychological information were obtained. Resting-state functional MRI was performed, and ReHo was used to determine the brain activity. ANCOVA was utilized to analyze between-group differences in ReHo and the associations between abnormal ReHo, and various clinical and neuropsychological variables were explored by Spearman’s correlation. Results. LPD patients had higher ReHo in the right temporal pole than the controls. RPD patients had increased ReHo in the right temporal pole and decreased ReHo in the primary motor cortex and premotor area, compared with the controls. Directly comparing LPD and RPD patients did not show a significant difference in ReHo. ReHo of the right temporal pole was significantly correlated with depression and anxiety in RPD patients. Conclusions. Both LPD and RPD have increased brain activity synchronization in the right temporal pole, and only RPD has decreased brain activity synchronization in the right frontal motor areas. The changed brain activity in the right temporal pole may play a compensatory role for depression and anxiety in PD, and the altered cerebral function in the right frontal motor area in RPD may represent the reorganization of the motor system in RPD.

scholarly journals Machine-learning identifies Parkinson's disease patients based on resting-state between-network functional connectivity

2019 ◽  
Vol 92 (1101) ◽  
pp. 20180886 ◽  
Author(s):  
Christian Rubbert ◽  
Christian Mathys ◽  
Christiane Jockwitz ◽  
Christian J Hartmann ◽  
Simon B Eickhoff ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Resting State ◽  
Good Accuracy ◽  
Network Connectivity ◽  
High Sensitivity ◽  
Data Driven ◽  
Healthy Controls ◽  
Whole Brain ◽  
Model Based

Objective: Evaluation of a data-driven, model-based classification approach to discriminate idiopathic Parkinson’s disease (PD) patients from healthy controls (HC) based on between-network connectivity in whole-brain resting-state functional MRI (rs-fMRI). Methods: Whole-brain rs-fMRI (EPI, TR = 2.2 s, TE = 30 ms, flip angle = 90°. resolution = 3.1 × 3.1 × 3.1 mm, acquisition time ≈ 11 min) was assessed in 42 PD patients (medical OFF) and 47 HC matched for age and gender. Between-network connectivity based on full and L2-regularized partial correlation measures were computed for each subject based on canonical functional network architectures of two cohorts at different levels of granularity (Human Connectome Project: 15/25/50/100/200 networks; 1000BRAINS: 15/25/50/70 networks). A Boosted Logistic Regression model was trained on the correlation matrices using a nested cross-validation (CV) with 10 outer and 10 inner folds for an unbiased performance estimate, treating the canonical functional network architecture and the type of correlation as hyperparameters. The number of boosting iterations was fixed at 100. The model with the highest mean accuracy over the inner folds was trained using an non-nested 10-fold 20-repeats CV over the whole dataset to determine feature importance. Results: Over the outer folds the mean accuracy was found to be 76.2% (median 77.8%, SD 18.2, IQR 69.4 – 87.1%). Mean sensitivity was 81% (median 80%, SD 21.1, IQR 75 – 100%) and mean specificity was 72.7% (median 75%, SD 20.4, IQR 66.7 – 80%). The 1000BRAINS 50-network-parcellation, using full correlations, performed best over the inner folds. The top features predominantly included sensorimotor as well as sensory networks. Conclusion: A rs-fMRI whole-brain-connectivity, data-driven, model-based approach to discriminate PD patients from healthy controls shows a very good accuracy and a high sensitivity. Given the high sensitivity of the approach, it may be of use in a screening setting. Advances in knowledge: Resting-state functional MRI could prove to be a valuable, non-invasive neuroimaging biomarker for neurodegenerative diseases. The current model-based, data-driven approach on whole-brain between-network connectivity to discriminate Parkinson’s disease patients from healthy controls shows promising results with a very good accuracy and a very high sensitivity.

scholarly journals Network degeneration in Parkinson’s disease: multimodal imaging of nigro-striato-cortical dysfunction

Brain ◽  
2020 ◽  
Vol 143 (3) ◽  
pp. 944-959 ◽  
Author(s):  
Marina C Ruppert ◽  
Andrea Greuel ◽  
Masoud Tahmasian ◽  
Frank Schwartz ◽  
Sophie Stürmer ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Connectivity ◽  
Functional Mri ◽  
Resting State ◽  
Fdg Pet ◽  
Multimodal Imaging ◽  
Substantia Nigra Pars Compacta ◽  
Dopamine Depletion ◽  
18F Fdg

Abstract The spreading hypothesis of neurodegeneration assumes an expansion of neural pathologies along existing neural pathways. Multimodal neuroimaging studies have demonstrated distinct topographic patterns of cerebral pathologies in neurodegeneration. For Parkinson’s disease the hypothesis so far rests largely on histopathological evidence of α-synuclein spreading in a characteristic pattern and progressive nigrostriatal dopamine depletion. Functional consequences of nigrostriatal dysfunction on cortical activity remain to be elucidated. Our goal was to investigate multimodal imaging correlates of degenerative processes in Parkinson’s disease by assessing dopamine depletion and its potential effect on striatocortical connectivity networks and cortical metabolism in relation to parkinsonian symptoms. We combined 18F-DOPA-PET, 18F-fluorodeoxyglucose (FDG)-PET and resting state functional MRI to multimodally characterize network alterations in Parkinson’s disease. Forty-two patients with mild-to-moderate stage Parkinson’s disease and 14 age-matched healthy control subjects underwent a multimodal imaging protocol and comprehensive clinical examination. A voxel-wise group comparison of 18F-DOPA uptake identified the exact location and extent of putaminal dopamine depletion in patients. Resulting clusters were defined as seeds for a seed-to-voxel functional connectivity analysis. 18F-FDG metabolism was compared between groups at a whole-brain level and uptake values were extracted from regions with reduced putaminal connectivity. To unravel associations between dopaminergic activity, striatocortical connectivity, glucose metabolism and symptom severity, correlations between normalized uptake values, seed-to-cluster β-values and clinical parameters were tested while controlling for age and dopaminergic medication. Aside from cortical hypometabolism, 18F-FDG-PET data for the first time revealed a hypometabolic midbrain cluster in patients with Parkinson’s disease that comprised caudal parts of the bilateral substantia nigra pars compacta. Putaminal dopamine synthesis capacity was significantly reduced in the bilateral posterior putamen and correlated with ipsilateral nigral 18F-FDG uptake. Resting state functional MRI data indicated significantly reduced functional connectivity between the dopamine depleted putaminal seed and cortical areas primarily belonging to the sensorimotor network in patients with Parkinson’s disease. In the inferior parietal cortex, hypoconnectivity in patients was significantly correlated with lower metabolism (left P = 0.021, right P = 0.018). Of note, unilateral network alterations quantified with different modalities corresponded with contralateral motor impairments. In conclusion, our results support the hypothesis that degeneration of nigrostriatal fibres functionally impairs distinct striatocortical connections, disturbing the efficient interplay between motor processing areas and impairing motor control in patients with Parkinson’s disease. The present study is the first to reveal trimodal evidence for network-dependent degeneration in Parkinson’s disease by outlining the impact of functional nigrostriatal pathway impairment on striatocortical functional connectivity networks and cortical metabolism.

scholarly journals Parkinson's disease-related pattern (PDRP) identified using resting-state functional MRI: Validation study

2021 ◽  
Vol 1 (3) ◽  
pp. 100026
Author(s):  
Andrea Rommal ◽  
An Vo ◽  
Katharina A. Schindlbeck ◽  
Andrea Greuel ◽  
Marina C. Ruppert ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Functional Mri ◽  
Validation Study ◽  
Resting State ◽  
Related Pattern

scholarly journals Pathological Beta Burst Dynamics are Conserved Across Different Movements in Parkinson’s Disease

2020 ◽  
Author(s):  
Raumin S. Neuville ◽  
Ross. W. Anderson ◽  
Matthew N. Petrucci ◽  
Jordan E. Parker ◽  
Kevin B. Wilkins ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Neural Activity ◽  
Resting State ◽  
Closed Loop ◽  
Peak Frequency ◽  
Beta Band ◽  
Beta Power ◽  
Deep Brain

AbstractBackgroundResting state beta band (13 – 30 Hz) oscillations represent pathological neural activity in Parkinson’s disease (PD). It is unknown whether the peak frequency or dynamics of beta oscillations change among rest, fine, limb and axial movements. This will be critical for the development and feasibility of closed loop deep brain stimulation (DBS) algorithms during resting and movement states.MethodsSubthalamic (STN) local field potentials (LFPs) were recorded from a sensing neurostimulator (Activa® PC+S, Medtronic Inc.,) and synchronized to kinematic recordings in twelve PD participants off medication/off STN DBS during thirty seconds of repetitive alternating finger tapping, wrist-flexion extension, stepping in place, and free walking. Beta power peaks and beta burst dynamics were identified by custom algorithms; beta burst dynamics were compared among rest and movement tasks.ResultsResting state burst durations were longer in a PD beta band, which was elevated above the 1/f physiological spectrum compared to an overlapping band (p < 0.001). Beta power peaks were evident during fine, limb, and axial movements in 98% of movement trials; the peak frequencies were similar during movements and at rest. Burst duration, average and peak power were also similar among the four movement tasks across the group but varied within individuals.ConclusionsProlonged burst durations were a feature of PD bands elevated above and not of PD bands overlapping the 1/f spectrum. The conservation of rest/movement band peak frequency and burst dynamics during different activity states supports the feasibility of successful closed loop DBS algorithms driven by beta burst dynamics during different activities and at rest.HighlightsProlonged beta burst durations represent pathological neural activity in Parkinson’s diseaseBeta band peak frequencies are similar across rest, fine, limb and axial movementsBeta burst dynamics are similar among rest and different movement statesConservation of Parkinsonian neural characteristics across different activity states supports the feasibility of closed loop deep brain stimulation systems in daily life

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