Comparing abnormalities of amplitude of low-frequency fluctuations in multiple system atrophy and idiopathic Parkinson's disease measured with resting-state fMRI

Abnormalities of cerebral blood flow and the regional brain function in Parkinson's disease: a systematic review and multimodal neuroimaging meta-analysis

Background

Parkinson's disease (PD) is a neurodegenerative disease with high incidence rate. Resting state functional magnetic resonance imaging (rs-fMRI), as a widely used method for studying neurodegenerative diseases, has not yet been combined with two important indicators, amplitude low-frequency fluctuation (ALFF) and cerebral blood flow (CBF), for standardized analysis of PD.

Methods

In this study, we used seed-based d-mapping and permutation of subject images (SDM-PSI) software to investigate the changes in ALFF and CBF of PD patients. After obtaining the regions of PD with changes in ALFF or CBF, we conducted a multimodal analysis to identify brain regions where ALFF and CBF changed together or could not synchronize.

Results

The final study included 31 eligible trials with 37 data sets. The main analysis results showed that the ALFF of the left striatum and left anterior thalamic projection decreased in PD patients, while the CBF of the right superior frontal gyrus decreased. However, the results of multimodal analysis suggested that there were no statistically significant brain regions. In addition, the decrease of ALFF in the left striatum and the decrease of CBF in the right superior frontal gyrus was correlated with the decrease in clinical cognitive scores.

Conclusion

PD patients had a series of spontaneous brain activity abnormalities, mainly involving brain regions related to the striatum-thalamic-cortex circuit, and related to the clinical manifestations of PD. Among them, the left striatum and right superior frontal gyrus are more closely related to cognition.

Systematic review registration

https://www.crd.york.ac.uk/ PROSPERO (CRD42023390914).

Magnetic Resonance T1w/T2w Ratio in the Putamen and Cerebellum as a Marker of Cognitive Impairment in MSA: a Longitudinal Study

The exact pathophysiology of cognitive impairment in multiple system atrophy (MSA) is unclear. In our longitudinal study, we aimed to analyze (I) the relationships between cognitive functions and some subcortical structures, such as putamen and cerebellum assessed by voxel-based morphometry (VBM) and T1-weighted/T2-weighted (T1w/T2w) ratio, and (II) the neuroimaging predictors of the progression of cognitive deficits. Twenty-six patients with MSA underwent a comprehensive neuropsychological battery, motor examination, and brain MRI at baseline (T0) and 1-year follow-up (T1). Patients were then divided according to cognitive status into MSA with normal cognition (MSA-NC) and MSA with mild cognitive impairment (MCI). At T1, we divided the sample according to worsening/non worsening of cognitive status compared to baseline evaluation. Logistic regression analysis showed that age (β =  - 9.45, p = .02) and T1w/T2w value in the left putamen (β = 230.64, p = .01) were significant predictors of global cognitive status at T0, explaining 65% of the variance. Logistic regression analysis showed that ∆-values of WM density in the cerebellum/brainstem (β = 2188.70, p = .02) significantly predicted cognitive worsening at T1, explaining 64% of the variance. Our results suggest a role for the putamen and cerebellum in the cognitive changes of MSA, probably due to their connections with the cortex. The putaminal T1w/T2w ratio may deserve further studies as a marker of cognitive impairment in MSA.

Association between cortical gyrification and white matter integrity in spinocerebellar ataxia type 3

Gray matter volume and thickness reductions have been reported in patients with spinocerebellar ataxia type 3 (SCA3), whereas cortical gyrification alterations of this disease remain largely unexplored. Using local gyrification index (LGI) and fractional anisotropy (FA) from structural and diffusion MRI data, this study investigated the cortical gyrification alterations as well as their relationship with white matter microstructural abnormalities in patients with SCA3 (n = 61) compared with healthy controls (n = 69). We found widespread reductions in cortical LGI and white matter FA in patients with SCA3 and that changes in these 2 features were also coupled. In the patient group, the LGI of the left middle frontal gyrus, bilateral insula, and superior temporal gyrus was negatively correlated with the severity of depressive symptoms, and the FA of a cluster in the left cerebellum was negatively correlated with the Scale for the Assessment and Rating of Ataxia scores. Our findings suggest that the gyrification abnormalities observed in this study may account for the clinical heterogeneity in SCA3 and are likely to be mediated by the underlying white matter microstructural abnormalities of this disease.

Pathomechanisms of depression in multiple system atrophy

Multiple system atrophy (MSA) is a rapidly progressing neurodegenerative disorder of uncertain etiology that is characterized by various combinations of Parkinsonism, autonomic, cerebellar and motor dysfunctions, with poor prognosis. Little is known about modifiable factors, such as depression, that has negative effects on quality of life in MSA. Depression, with an estimated prevalence of about 43%, is among the most common neuropsychiatric disorders in MSA similar to other atypical Parkinsonian disorders, the frequency of which is associated with increased disease progression, disease severity and autonomic dysfunctions. Depression in MSA, like in Parkinson disease, has been related to a variety of pathogenic mechanisms associated with the underlying neurodegenerative process, such as involvement of serotonergic neuron groups in the brainstem, prefrontal cortical dysfunctions, and altered functional fronto-temporal-thalamic connectivities with disturbances of mood related and other essential resting-state brain networks. The pathophysiology and pathogenesis of depression in MSA, as in other degenerative movement disorders, are complex and deserve further elucidation as a basis for adequate treatment to improve the quality of life in this fatal disease.

Alterations of voxel-wise spontaneous activity and corresponding brain functional networks in multiple system atrophy patients with mild cognitive impairment

Emerging evidence has indicated that cognitive impairment is an underrecognized feature of multiple system atrophy (MSA). Mild cognitive impairment (MCI) is related to a high risk of dementia. However, the mechanism underlying MCI in MSA remains controversial. In this study, we conducted the amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC) analyses to detect the characteristics of local neural activity and corresponding network alterations in MSA patients with MCI (MSA-MCI). We enrolled 80 probable MSA patients classified as cognitively normal (MSA-NC, n = 36) and MSA-MCI (n = 44) and 40 healthy controls. Compared with MSA-NC, MSA-MCI exhibited decreased ALFF in the right dorsal lateral prefrontal cortex (RDLPFC) and increased ALFF in the right cerebellar lobule IX and lobule IV-V. In the secondary FC analyses, decreased FC in the left inferior parietal lobe (IPL) was observed when we set the RDLPFC as the seed region. Decreased FC in the bilateral cuneus, left precuneus, and left IPL and increased FC in the right middle temporal gyrus were shown when we set the right cerebellar lobule IX as the seed region. Furthermore, FC of DLPFC-IPL and cerebello-cerebral circuit, as well as ALFF alterations, were significantly correlated with Montreal Cognitive Assessment scores in MSA patients. We also employed whole-brain voxel-based morphometry analysis, but no gray matter atrophy was detected between the patient subgroups. Our findings indicate that altered spontaneous activity in the DLPFC and the cerebellum and disrupted DLPFC-IPL, cerebello-cerebral networks are possible biomarkers of early cognitive decline in MSA patients.

Altered Brain Volume, Microstructure Metrics and Functional Connectivity Features in Multiple System Atrophy

In order to deeply understand the specific patterns of volume, microstructure, and functional changes in Multiple System Atrophy patients with cerebellar ataxia syndrome (MSA-c), we perform the current study by simultaneously applying structural (T1-weighted imaging), Diffusion tensor imaging (DTI), functional (BOLD fMRI) and extended Network-Based Statistics (extended-NBS) analysis. Twenty-nine MSA-c type patients and twenty-seven healthy controls (HCs) were involved in this study. First, we analyzed the whole brain changes of volume, microstructure, and functional connectivity (FC) in MSA-c patients. Then, we explored the correlations between significant multimodal MRI features and the total Unified Multiple System Atrophy Rating Scale (UMSARS) scores. Finally, we searched for sensitive imaging biomarkers for the diagnosis of MSA-c using support vector machine (SVM) classifier. Results showed significant grey matter atrophy in cerebellum and white matter microstructural abnormalities in cerebellum, left fusiform gyrus, right precentral gyrus and lingual gyrus. Extended-NBS analysis found two significant different connected components, featuring altered functional connectivity related to left and right cerebellar sub-regions, respectively. Moreover, the reduced fiber bundle counts at right Cerebellum_3 (Cbe3) and decreased fractional anisotropy (FA) values at bilateral Cbe9 were negatively associated with total UMSARS scores. Finally, the significant features at left Cbe9, Cbe1, and Cbe7b were found to be useful as sensitive biomarkers to differentiate MSA-c from HCs according to the SVM analysis. These findings advanced our understanding of the neural pathophysiological mechanisms of MSA from the perspective of multimodal neuroimaging.

Automated Differentiation of Atypical Parkinsonian Syndromes Using Brain Iron Patterns in Susceptibility Weighted Imaging

In recent studies, iron overload has been reported in atypical parkinsonian syndromes. The topographic patterns of iron distribution in deep brain nuclei vary by each subtype of parkinsonian syndrome, which is affected by underlying disease pathologies. In this study, we developed a novel framework that automatically analyzes the disease-specific patterns of iron accumulation using susceptibility weighted imaging (SWI). We constructed various machine learning models that can classify diseases using radiomic features extracted from SWI, representing distinctive iron distribution patterns for each disorder. Since radiomic features are sensitive to the region of interest, we used a combination of T1-weighted MRI and SWI to improve the segmentation of deep brain nuclei. Radiomics was applied to SWI from 34 patients with a parkinsonian variant of multiple system atrophy, 21 patients with cerebellar variant multiple system atrophy, 17 patients with progressive supranuclear palsy, and 56 patients with Parkinson’s disease. The machine learning classifiers that learn the radiomic features extracted from iron-reflected segmentation results produced an average area under receiver operating characteristic curve (AUC) of 0.8607 on the training data and 0.8489 on the testing data, which is superior to the conventional classifier with segmentation using only T1-weighted images. Our radiomic model based on the hybrid images is a promising tool for automatically differentiating atypical parkinsonian syndromes.

Depression in multiple system atrophy: Views on pathological, clinical and imaging aspects

Multiple system atrophy (MSA) is a common atypical parkinsonism, characterized by a varying combination of autonomic, cerebellar, and pyramidal systems. It has been noticed that the patients with MSA can be accompanied by some neuropsychiatric disorders, in particular depression. However, there is limited understanding of MSA-related depression. To bridge existing gaps, we summarized research progress on this topic and provided a new perspective regarding pathological, clinical, and imaging aspects. Firstly, we synthesized corresponding studies in order to investigate the relationship between depression and MSA from a pathological perspective. And then, from a clinical perspective, we focused on the prevalence of depression in MS patients and the comparison with other populations. Furthermore, the associations between depression and some clinical characteristics, such as life quality and gender, have been reported. The available neuroimaging studies were too sparse to draw conclusions about the radiological aspect of depression in MSA patients but we still described them in the presence of paper. Finally, we discussed some limitations and shortcomings existing in the included studies, which call for more high-quality basic research and clinical research in this field.

Differentiation of Cerebellum-Type and Parkinson-Type of Multiple System Atrophy by Using Multimodal MRI Parameters

Recent studies have demonstrated the structural and functional changes in patients with multiple system atrophy (MSA). However, little is known about the different parameter changes of the most vulnerable regions in different types of MSA. In this study, we collected resting-state structure, perfusion, and patients with functional magnetic resonance imaging (fMRI) data of cerebellum-type of MSA (MSA-c) and Parkinson-type of MSA (MSA-p). First, by simultaneously using voxel-based morphology (VBM), arterial spin labeling (ASL), and amplitude of low-frequency fluctuation (ALFF), we analyzed the whole brain differences of structure, perfusion, and functional activation between patients with MSA-c and MSA-p. Second, we explored the relationships among structure, perfusion, function, and the clinical variables in patients with MSA. Finally, we extracted the MRI parameters of a specific region to separate the two groups and search for a sensitive imaging biomarker. As a result, compared with patients with MSA-p type, patients with MSA-c type showed decreased structure atrophy in several cerebella and vermis subregions, reduced perfusion in bilateral cerebellum_4_5 and vermis_4_5, and an decreased ALFF values in the right lingual gyrus (LG) and fusiform (FFG). Subsequent analyses revealed the close correlations among structure, perfusion, function, and clinical variables in both MSA-c and MSA-p. Finally, the receiver operating characteristic (ROC) analysis showed that the regional cerebral blood flow (rCBF) of bilateral cerebellum_4_5/vermis_4_5 could differentiate the two groups at a relatively high accuracy, yielding the sensitivity of 100%, specificity of 79.2%, and the area under the curve (AUC) value of 0.936. These findings have important implications for understanding the underlying neurobiology of different types of MSA and added the new evidence for the disrupted rCBF, structure, and function of MSA, which may provide the potential biomarker for accurately detecting different types of patients with MSA and new ideas for the treatment of different types of MSA in the future.

Frequency specific co-activation pattern analysis via sparse nonnegative tensor decomposition

BACKGROUND

Traditionally, the diagnosis of Parkinson's disease (PD) has been made based on symptoms. Extensive studies have demonstrated that PD may lead to variation of brain activity in different frequency bands. However, frequency specific dynamic alterations of PD have not yet been explored.

NEW METHOD

In order to address this gap, a novel sparse nonnegative tensor decomposition (SNTD) method was used to estimate frequency specific co-activation patterns (CAP). The difference between PD and healthy controls (HC) are investigated with the proposed framework.

RESULT

The difference between PD and HC mainly exists at frequency band 0.04-0.1 Hz in basal ganglia. We also found that the average intensity of PD in this frequency band is significantly correlated with the Hoehn and Yahr scale.

COMPARISON WITH EXISTING METHODS

Compared with conventional CAP approach, SNTD estimates frequency specific CAPs that show alterations in PD patients.

CONCLUSION

SNTD provides an alternative to K-means clustering used in conventional CAP analysis. With the proposed framework, frequency specific CAPs are extracted, and alterations in PD patients are also successfully discovered.

Bereitschaftspotential in Multiple System Atrophy

Objective: Multiple system atrophy (MSA) is a neurodegenerative disorder manifesting as parkinsonism, cerebellar ataxia, and autonomic dysfunction. It is categorized into MSA with predominant parkinsonism (MSA-P) and into MSA with predominant cerebellar ataxia (MSA-C). The pathophysiology of motor control circuitry involvement in MSA subtype is unclear. Bereitschaftspotential (BP) is a feasible clinical tool to measure electroencephalographic activity prior to volitional motions. We recorded BP in patients with MSA-P and MSA-C to investigate their motor cortical preparation and activation for volitional movement.

Methods: We included eight patients with MSA-P, eight patients with MSA-C, and eight age-matched healthy controls. BP was recorded during self-paced rapid wrist extension movements. The electroencephalographic epochs were time-locked to the electromyography onset of the voluntary wrist movements. The three groups were compared with respect to the mean amplitudes of early (1,500–500 ms before movement onset) and late (500–0 ms before movement onset) BP.

Results: Mean early BP amplitude was non-significantly different between the three groups. Mean late BP amplitude in the two patient groups was significantly reduced in the parietal area contralateral to the movement side compared with that in the healthy control group. In addition, the late BP of the MSA-C group but not the MSA-P group was significantly reduced at the central parietal area compared with that of the healthy control group.

Conclusions: Our findings suggest that patients with MSA exhibit motor cortical dysfunction in voluntary movement preparation and activation. The dysfunction can be practicably evaluated using late BP, which represents the cerebello-dentato-thalamo-cortical pathway.

Voxel-Based Meta-Analysis of Gray Matter Abnormalities in Multiple System Atrophy

Purpose: This study aimed to identify consistent gray matter volume (GMV) changes in the two subtypes of multiple system atrophy (MSA), including parkinsonism subtype (MSA-P), and cerebellar subtype (MSA-C), by conducting a voxel-wise meta-analysis of whole brain voxel-based morphometry (VBM) studies.

Method: VBM studies comparing MSA-P or MSA-C and healthy controls (HCs) were systematically searched in the PubMed, Embase, and Web of Science published from 1974 to 20 October 2020. A quantitative meta-analysis of VBM studies on MSA-P or MSA-C was performed using the effect size-based signed differential mapping (ES-SDM) method separately. A complementary analysis was conducted using the Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) method, which allows a familywise error rate (FWE) correction for multiple comparisons of the results, for further validation of the results.

Results: Ten studies were included in the meta-analysis of MSA-P subtype, comprising 136 MSA-P patients and 211 HCs. Five studies were included in the meta-analysis of MSA-C subtype, comprising 89 MSA-C patients and 134 HCs. Cerebellum atrophy was detected in both MSA-P and MSA-C, whereas basal ganglia atrophy was only detected in MSA-P. Cerebral cortex atrophy was detected in both subtypes, with predominant impairment of the superior temporal gyrus, inferior frontal gyrus, temporal pole, insula, and amygdala in MSA-P and predominant impairment of the superior temporal gyrus, middle temporal gyrus, fusiform gyrus, and lingual gyrus in MSA-C. Most of these results survived the FWE correction in the complementary analysis, except for the bilateral amygdala and the left caudate nucleus in MSA-P, and the right superior temporal gyrus and the right middle temporal gyrus in MSA-C. These findings remained robust in the jackknife sensitivity analysis, and no significant heterogeneity was detected.

Conclusion: A different pattern of brain atrophy between MSA-P and MSA-C detected in the current study was in line with clinical manifestations and provided the evidence of the pathophysiology of the two subtypes of MSA.

MRI-Based Radiomics of Basal Nuclei in Differentiating Idiopathic Parkinson's Disease From Parkinsonian Variants of Multiple System Atrophy: A Susceptibility-Weighted Imaging Study

Objectives

To investigate the value of MRI-based radiomic model based on the radiomic features of different basal nuclei in differentiating idiopathic Parkinson's disease (IPD) from Parkinsonian variants of multiple system atrophy (MSA-P).

Methods

Radiomics was applied to the 3T susceptibility- weighted imaging (SWI) from 102 MSA-P patients and 83 IPD patients (allocated to a training and a testing cohort, 7:3 ratio). The substantia nigra (SN), caudate nucleus (CN), putamen (PUT), globus pallidus (GP), red nucleus (RN), and subthalamic nucleus (STN) were manually segmented, and 396 features were extracted. After feature selection, support vector machine (SVM) was generated, and its predictive performance was calculated in both the training and testing cohorts using the area under receiver operating characteristic curve (AUC).

Results

Seven radiomic features were selected from the PUT, by which the SVM classifier achieved the best diagnostic performance with an AUC of 0.867 in the training cohort and an AUC of 0.862 in the testing cohort. Furthermore, the combined model, which incorporating part III of the Parkinson's Disease Rating Scale (UPDRSIII) scores into radiomic features of the PUT, further improved the diagnostic performance. However, radiomic features extracted from RN, SN, GP, CN, and STN had moderate to poor diagnostic performance, with AUC values that ranged from 0.610 to 0.788 in the training cohort and 0.583 to 0.766 in the testing cohort.

Conclusion

Radiomic features derived from the PUT had optimal value in differentiating IPD from MSA-P. A combined radiomic model, which contained radiomic features of the PUT and UPDRSIII scores, further improved performance and may represent a promising tool for distinguishing between IPD and MSA-P.

Abnormal static and dynamic functional connectivity of resting-state fMRI in multiple system atrophy

In order to explore the topological alterations in functional brain networks between multiple system atrophy (MSA) patients and healthy controls (HC), a new joint analysis method of static and dynamic functional connectivity (FC) is proposed in this paper. Twenty-four MSA patients and twenty HCs were enrolled in this study. We constructed static and dynamic brain networks from resting-state fMRI data and calculated four graph theory attributes. Statistical comparisons and correlation analysis were carried out for static and dynamic FC separately before combining both cases. We found decreased local efficiency (LE) and weighted degree (WD) in cerebellum from both static and dynamic graph attributes. For static FC alone, we identified increased betweenness centrality (BC) at left dorsolateral prefrontal cortex, left Cerebellum_Crus9 and decreased WD at Vermis_6. For dynamic FC alone, decreased BC, clustering coefficients and LE at several cortical regions and cerebellum were identified. All the features had significant correlation with total UMSARS scores. Receiver operating characteristic analysis showed that dynamic features had the highest area under the curve value. Our work not only added new evidence for the underlying neurobiology and disrupted dynamic disconnection syndrome of MSA, but also proved the possibility of disease diagnosis and progression tracking using rs-fMRI.

Hippocampal connectivity in the aftermath of acute social stress

The hippocampus is a core brain region that responds to stress. Previous studies have found a dysconnectivity between hippocampus and other brain regions under acute and chronic stress. However, whether and how acute social stress influences the directed connectivity patterns from and to the hippocampus remains unclear. In this study, using a within-subject design and Granger causal analysis (GCA), we investigated the alterations of resting state effective connectivity from and to hippocampal subregions after an acute social stressor (the Trier Social Stress Test). Participants were engaged in stress and control conditions spaced approximately one month apart. Our findings showed that stress altered the information flows in the thalamus-hippocampus-insula/midbrain circuit. The changes in this circuit could also predict with high accuracy the stress and control conditions at the subject level. These hippocampus-related brain networks have been documented to be involved in emotional information processing and storage, as well as habitual responses. We speculate that alterations of the effective connectivity between these brain regions may be associated with the registering and encoding of threatening stimuli under stress. Our investigation of hippocampal functional connectivity at a subregional level may help elucidate the functional neurobiology of stress-related psychiatric disorders.

Spatial Patterns of Decreased Cerebral Blood Flow and Functional Connectivity in Multiple System Atrophy (Cerebellar-Type): A Combined Arterial Spin Labeling Perfusion and Resting State Functional Magnetic Resonance Imaging Study

Multiple system atrophy (MSA) is a progressive neurodegenerative disease. However, little is known about the regional cerebral blood flow (rCBF) and functional connectivity changes in the disease. In this study, the magnetic resonance imaging (MRI) data including 24MSA-c-type patients and 20 healthy controls were collected by using voxel wise arterial spin labeling (ASL) perfusion analysis, several regions of the altered rCBF were identified in the MSA c-type patients. And then, the changes of the functional connectivities of identified rCBF regions were analyzed by using functional MRI (fMRI). Finally, rCBF value of cerebellum was extracted to differentiate the MSA c-type patients and controls. Compared with the controls, the MSA c-type patients showed distinct disruption of rCBF in the cerebellum. The disconnection of the identified cerebellar regions was revealed in several regions in the MSAc-type patients, including right middle frontal gyrus (MFG), right precuneus, left superior temporal gyrus (STG), right lingual gyrus, left postcentral gyrus (PoCG), right cerebellum 7b, right cerebellum 8, and left cerebellum 4,5. These regions were involved in the default mode network (DMN), sensorimotor network, visual associated cortices, and cerebellum. Using the rCBF value of vermis as biomarker, the two groups can be differentiated and reached a sensitivity of 95.8% and specificity of 100%. This is the first study to demonstrate the MSA-specific rCBF abnormalities using the ASL method, which are closely associated with several functional networks on resting state fMRI. The rCBF of vermis might be used as the potential imaging biomarker for the early diagnosis of MSA c-type.

Cerebellar atrophy and its contribution to motor and cognitive performance in multiple system atrophy

Objective

Neuroanatomical differences in the cerebellum are among the most consistent findings in multiple system atrophy (MSA) patients. This study performed a detailed cerebellar morphology in MSA patients and its two subtypes: MSA-P (parkinson's symptoms predominate) and MSA-C (cerebellar symptoms predominant), and their relations to profiles of motor and cognitive deficits.

Materials and methods

Structure MRI data were acquired from 63 healthy controls and 61 MSA patients; voxel-based morphometry and the Spatially Unbiased Infratentorial Toolbox cerebellar atlas were performed to identify the cerebellar gray volume changes in MSA and its subtypes. Further, the gray matter changes were correlated with the clinical motor/cognitive scores.

Results

Patients with MSA exhibited widespread loss of cerebellar volume bilaterally, relative to healthy controls. In those with MSA-C, gray matter loss was detected from anterior (bilateral lobule IV-V) to posterior (bilateral crus I/II, bilateral lobule IX, left lobule VIII) cerebellar lobes. Lower anterior cerebellar volume negatively correlated with disease duration and motor performance, whereas posterior lobe integrity positively correlated with cognitive assessment. In patients with MSA-P, atrophy of anterior lobe (bilateral lobules IV-V) and posterior lobe in part (left lobule VI, bilateral IX) was evident; and in left cerebellar lobule IX, gray matter loss negatively correlated with motor scores. Direct comparison of MSA-P and MSA-C group outcomes showed divergence in right cerebellar crus II only.

Conclusions

Our data suggest that volumetric abnormalities of cerebellum contribute substantially to motor and cognitive performance in patients with MSA. In patients with MSA-P and MSA-C, affected regions of cerebellum differed.

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Cerebellum atrophy contributed substantially to motor and cognitive behavior in MSA.

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Lower cerebellum IV-V volume was correlated with MSA-C disease duration and severity

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Cerebellum atrophy in one side may imply symptoms onset on contralateral

Altered Functional Connectivity of Cerebello-Cortical Circuit in Multiple System Atrophy (Cerebellar-Type)

Multiple system atrophy (MSA) is regarded as a progressive neurodegenerative disease mainly divided into MSA-p type with Parkinsonism and MSA-c type with cerebellar ataxia as the main symptom. However, its neural mechanism is still unclear. In this study, we only focus on the MSA-c type. The purpose of this study is to explore the functional connectivity changes of the cerebello-cortical circuit in MSA-c type by using resting state functional magnetic resonance imaging (rs-fMRI). Thirty-six subjects (18 MSA and 18 normal controls) participated in this study and the rs-fMRI data were collected by applying resting state amplitude of low-frequency fluctuations (ALFF), we found the significant decreased ALFF in the MSA patients relative to controls, which included left cerebellum 8 area, 9 area, 7b area and Cru1 as well as vermis 7. Then we select the brain region of cerebellum 8 area as seed to investigate whole brain functional connectivity alteration in the MSA patients. When comparing to controls, several regions showed decreased connectivity in the MSA patients including bilateral cerebellum anterior lobe, left cerebellum posterior lobe, left dentate, bilateral pons, inferior parietal lobule (IPL), lingual gyrus (LG), parahippocampus (PHG), and middle temporal gyrus (MTG). In addition, there were closely correlation between functional connectivities and clinical performances in the MSA patients. The current study confirmed that the disrupted functional connectivity of specific cerebello-cortical circuit in the MSA patients, which is responsible for the clinical performances.

Functional MRI in Atypical Parkinsonisms

The present chapter reports the current knowledge on the use of functional MRI (fMRI) in patients with atypical parkinsonisms, including Multiple System Atrophy, Corticobasal Syndrome and Progressive Supranuclear Palsy syndrome. Both resting state functional connectivity and task-based brain activity abnormalities are reported in atypical parkinsonisms relative to healthy controls and Parkinson's disease patients. Functional alterations were observed earlier than structural damage and may help to make early diagnosis. The chapter also examines the few longitudinal evidence on fMRI changes in patients with these conditions. The potential use of fMRI techniques in aiding the differential diagnosis, accurately measuring disease progression and assessing the effectiveness of therapeutic interventions is discussed.

Disrupted amplitude of low-frequency fluctuations and causal connectivity in Parkinson's disease with apathy

Apathy is a common non-motor symptom in Parkinson's disease (PD). We aimed to explore its associated neural substrates changes via amplitude of low-frequency fluctuations (ALFF) and granger causality analysis (GCA). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were performed in 20 PD patients with apathy (PD-A), 22 PD patients without apathy (PD-NA) and 19 healthy volunteers. GCA, a new method exploring direction from one brain region to another, was based on brain regions showing alterations of neural activity as seeds, which were examined utilizing ALFF approach. The relationships between ALFF or GCA and apathetic symptoms were also assessed. Relative to PD-NA group, PD-A group indicated decreased ALFF in left orbital middle frontal gyrus and bilateral superior frontal gyrus (SFG). Only ALFF values in right SFG were negatively correlated with Apathy Scale (AS) scores. Then GCA with the seed of right SFG showed a positive feedback from right thalamus to ipsilateral SFG, which was positively correlated with AS scores. In conclusion, dysfunction in SFG and a positive feedback from thalamus to ipsilateral SFG contributed to presence of PD-related apathy, providing a new perspective for future studies on apathy in PD.