Disrupted Functional Connectivity of Basal Ganglia across Tremor-Dominant and Akinetic/Rigid-Dominant Parkinson's Disease

Role of the globus pallidus in motor and non-motor symptoms of Parkinson's disease

The globus pallidus plays a pivotal role in the basal ganglia circuit. Parkinson's disease is characterized by degeneration of dopamine-producing cells in the substantia nigra, which leads to dopamine deficiency in the brain that subsequently manifests as various motor and non-motor symptoms. This review aims to summarize the involvement of the globus pallidus in both motor and non-motor manifestations of Parkinson's disease. The firing activities of parvalbumin neurons in the medial globus pallidus, including both the firing rate and pattern, exhibit strong correlations with the bradykinesia and rigidity associated with Parkinson's disease. Increased beta oscillations, which are highly correlated with bradykinesia and rigidity, are regulated by the lateral globus pallidus. Furthermore, bradykinesia and rigidity are strongly linked to the loss of dopaminergic projections within the cortical-basal ganglia-thalamocortical loop. Resting tremors are attributed to the transmission of pathological signals from the basal ganglia through the motor cortex to the cerebellum-ventral intermediate nucleus circuit. The cortico-striato-pallidal loop is responsible for mediating pallidi-associated sleep disorders. Medication and deep brain stimulation are the primary therapeutic strategies addressing the globus pallidus in Parkinson's disease. Medication is the primary treatment for motor symptoms in the early stages of Parkinson's disease, while deep brain stimulation has been clinically proven to be effective in alleviating symptoms in patients with advanced Parkinson's disease, particularly for the movement disorders caused by levodopa. Deep brain stimulation targeting the globus pallidus internus can improve motor function in patients with tremor-dominant and non-tremor-dominant Parkinson's disease, while deep brain stimulation targeting the globus pallidus externus can alter the temporal pattern of neural activity throughout the basal ganglia-thalamus network. Therefore, the composition of the globus pallidus neurons, the neurotransmitters that act on them, their electrical activity, and the neural circuits they form can guide the search for new multi-target drugs to treat Parkinson's disease in clinical practice. Examining the potential intra-nuclear and neural circuit mechanisms of deep brain stimulation associated with the globus pallidus can facilitate the management of both motor and non-motor symptoms while minimizing the side effects caused by deep brain stimulation.

Oscillation-Specific Nodal Differences in Parkinson's Disease Patients with Anxiety

Background

Parkinson's disease (PD) is a common neurodegenerative disorder that is predominantly known for its motor symptoms but is also accompanied by non-motor symptoms, including anxiety.

Objective

The underlying neurobiological substrates and brain network changes associated with comorbid anxiety in PD require further exploration.

Methods

An analysis of oscillation-specific nodal properties in patients with and without anxiety was conducted using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory. We used a band-pass filtering approach to differentiate oscillatory frequency bands for subsequent functional connectivity (FC) and graph analyses.

Results

The study included 68 non-anxiety PD (naPD) patients, 62 anxiety PD (aPD) patients, and 64 healthy controls (NC). Analyses of nodal betweenness centrality (BC), degree centrality (DC), and efficiency were conducted across multiple frequency bands. The findings indicated no significant differences in BC among naPD, aPD, and NC within the 0.01-0.08 Hz frequency range. However, we observed a specific reduction in BC at narrower frequency ranges in aPD patients, as well as differing patterns of change in DC and efficiency, which are believed to reflect the neurophysiological bases of anxiety symptoms in PD.

Conclusions

Differential oscillation-specific nodal characteristics have been identified in PD patients with anxiety, suggesting potential dysregulations in brain network dynamics. These findings emphasize the complexity of brain network alterations in anxiety-associated PD and identify oscillatory frequencies as potential biomarkers. The study highlights the importance of considering oscillatory frequency bands in the analysis of brain network changes.

Linking the cerebellum to Parkinson disease: an update

Parkinson disease (PD) is characterized by heterogeneous motor and non-motor symptoms, resulting from neurodegeneration involving various parts of the central nervous system. Although PD pathology predominantly involves the nigral-striatal system, growing evidence suggests that pathological changes extend beyond the basal ganglia into other parts of the brain, including the cerebellum. In addition to a primary involvement in motor control, the cerebellum is now known to also have an important role in cognitive, sleep and affective processes. Over the past decade, an accumulating body of research has provided clinical, pathological, neurophysiological, structural and functional neuroimaging findings that clearly establish a link between the cerebellum and PD. This Review presents an overview and update on the involvement of the cerebellum in the clinical features and pathogenesis of PD, which could provide a novel framework for a better understanding the heterogeneity of the disease.

Regional white matter hyperintensity volume in Parkinson's disease and associations with the motor signs

OBJECTIVE

To determine whether white matter hyperintensity (WMH) volumes in specific regions are associated with Parkinson's disease (PD) compared to non-PD controls, and to assess their impact on motor signs through cross-sectional and longitudinal analyses.

METHODS

A total of 50 PD participants and 47 age- and gender-matched controls were enrolled. All PD participants were followed up for at least 2 years. To detect regions of greater WMH in the PD, the WMH volume of each region was compared with the corresponding region in the control group. Linear regression and linear mixed effects models were respectively used for cross-sectional and longitudinal analyses of the impact of increases in WMH volume on motor signs.

RESULTS

The PD group had greater WMH volume in the occipital region compared with the control group. Cross-sectional analyses only detected a significant correlation between occipital WMH volume and motor function in PD. Occipital WMH volume positively correlated with the severity of tremor, and gait and posture impairments, in the PD group. During the follow-up period, the participants' motor signs progressed and the WMH volumes remained stable, no longitudinal association was detected between them. The baseline occipital WMH volume cannot predict the progression of signs after adjustment for baseline disease duration and the presence of vascular risk factors.

INTERPRETATION

PD participants in this study were characterized by greater WMH at the occipital region, and greater occipital WMH volume had cross-sectional associations with worse motor signs, while its longitudinal impact on motor signs progression was limited.

The pollutome-connectome axis: a putative mechanism to explain pollution effects on neurodegeneration

The study of pollutant effects is extremely important to address the epochal challenges we are facing, where world populations are increasingly moving from rural to urban centers, revolutionizing our world into an urban world. These transformations will exacerbate pollution, thus highlighting the necessity to unravel its effect on human health. Epidemiological studies have reported that pollution increases the risk of neurological diseases, with growing evidence on the risk of neurodegenerative disorders. Air pollution and water pollutants are the main chemicals driving this risk. These chemicals can promote inflammation, acting in synergy with genotype vulnerability. However, the biological underpinnings of this association are unknown. In this review, we focus on the link between pollution and brain network connectivity at the macro-scale level. We provide an updated overview of epidemiological findings and studies investigating brain network changes associated with pollution exposure, and discuss the mechanistic insights of pollution-induced brain changes through neural networks. We explain, in detail, the pollutome-connectome axis that might provide the functional substrate for pollution-induced processes leading to cognitive impairment and neurodegeneration. We describe this model within the framework of two pollutants, air pollution, a widely recognized threat, and polyfluoroalkyl substances, a large class of synthetic chemicals which are currently emerging as new neurotoxic source.

Nigral Iron Deposition Influences Disease Severity by Modulating the Effect of Parkinson's Disease on Brain Networks

BACKGROUND

In Parkinson's disease (PD), excessive iron deposition in the substantia nigra may exacerbate α-synuclein aggregation, facilitating the degeneration of dopaminergic neurons and their neural projection.

OBJECTIVE

To investigate the interaction effect between nigral iron deposition and PD status on brain networks.

METHODS

Eighty-five PD patients and 140 normal controls (NC) were included. Network function and nigral iron were measured using multi-modality magnetic resonance imaging. According to the median of nigral magnetic susceptibility of NC (0.095 ppm), PD and NC were respectively divided into high and low nigral iron group. The main and interaction effects were investigated by mixed effect analysis.

RESULTS

The main effect of disease was observed in basal ganglia network (BGN) and visual network (VN). The interaction effect between nigral iron and PD status was observed in left inferior frontal gyrus and left insular lobe in BGN, as well as right middle occipital gyrus, right superior temporal gyrus, and bilateral cuneus in VN. Furthermore, multiple mediation analysis revealed that the functional connectivity of interaction effect clusters in BGN and medial VN partially mediated the relationship between nigral iron and Unified Parkinson's Disease Rating Scale II score.

CONCLUSION

Our study demonstrates an interaction of nigral iron deposition and PD status on brain networks, that is, nigral iron deposition is associated with the change of brain network configuration exclusively when in PD. We identified a potential causal mediation pathway for iron to affect disease severity that was mediated by both BGN dysfunction and VN hyperfunction in PD.

Gray and white matter alterations in different predominant side and type of motor symptom in Parkinson's disease

Background

Parkinson's disease (PD) is highly heterogeneous reflected by different affected side of body and type of motor symptom. We aim to explore clinical characteristics and underlying brain structure alterations in PD with different predominant sides and motor types.

Methods

We recruited 161 PD patients and 50 healthy controls (HC). Patients were classified into four subtypes according to their predominant side and motor type: left akinetic/rigid‐dominant (LAR), left tremor‐dominant (LTD), right akinetic/rigid‐dominant (RAR), and right tremor‐dominant (RTD). All participants assessed motor and cognitive performances, then underwent T1‐weighted and diffusion tensor imaging scanning. A general linear model was used to compare neuroimaging parameters among five groups.

Results

Among four PD subtypes, patients of LAR subtype experienced the worst motor impairment, and only this subtype showed worse cognitive performance compared with HC. Compared with HC and other subtypes, LAR subtype showed a significant reduction in cortical thickness of the right caudal‐anterior‐cingulate gyrus and fractional anisotropy of the right cingulum bundle.

Conclusions

We demonstrated that LAR subtype had the worst clinical performance, which the severer damage in the right cingulate region might be the underlying mechanism. This study underscores the importance of classifying PD subtypes based on both the side and type of motor symptom for clinical intervention and research to optimize behavioral outcomes in the future.

Differential Effects of Subthalamic Nucleus and Globus Pallidus Internus Deep Brain Stimulation on Motor Subtypes in Parkinson's Disease

OBJECTIVE

We investigated the differences in motor symptom change outcomes after bilateral subthalamic nucleus (STN) and globus pallidus internus (GPi) deep brain stimulation (DBS) in well-defined motor subtypes of Parkinson's disease (PD) to improve clinical decision making.

METHODS

We included 114 patients who had undergone STN-DBS and 65 patients who had undergone GPi-DBS. The patients were classified as having akinetic-rigid type (ART), tremor-dominant type (TDT), and mixed type (MT) using the preoperative Movement Disorder Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) scores in the no-medication state. The outcome measures included the no-medication MDS-UPDRS-III scores and subscore changes at the last follow-up after surgery. The outcomes were compared among the different motor subtypes and between STN-DBS and GPi-DBS.

RESULTS

At the last follow-up (14.92 ± 8.35 months), the TDT patients had had a greater median overall motor improvement in the no-medication MDS-UPDRS-III scores compared with the ART patients (62.90% vs. 46.67%; P < 0.001), regardless of the stimulation target. The ART patients showed greater improvement after STN-DBS than after GPi-DBS (54.44% vs. 37.21%; P < 0.001), with improvements in rigidity, akinesia, and posture and gait disorders accounting for the difference.

CONCLUSIONS

Our results suggest that the different PD motor subtypes will have differential responses to STN-DBS and GPi-DBS, that TDT patients will experience greater improvement than ART patients, and that STN-DBS provides better effects for ART patients than does GPi-DBS. In addition, different motor symptoms among the different motor subtypes might respond differently to STN-DBS than to GPi-DBS. All these factors could reflect the heterogeneity of PD. Longer-term outcomes across the different motor subtypes and stimulation targets should be studied further.

Tremor associated with similar structural networks in Parkinson's disease and essential tremor

INTRODUCTION

Despite substantial clinical and pathophysiological differences, the characteristics of tremor in Parkinson's disease (PD) and essential tremor (ET) patients bear certain similarities. The presented study delineates tremor-related structural networks in these two disorders.

METHODS

42 non-advanced PD patients (18 tremor-dominant, 24 without substantial tremor), 17 ET, and 45 healthy controls underwent high-angular resolution diffusion-weighted imaging acquisition to reconstruct their structural motor connectomes as a proxy of the anatomical interconnections between motor network regions, implementing state-of-the-art globally optimised probabilistic tractography.

RESULTS

When compared to healthy controls, ET patients exhibited higher structural connectivity in the cerebello-thalamo-cortical network. Interestingly, the comparison of tremor-dominant PD patients and PD patients without tremor yielded very similar results - higher structural connectivity in tremor-dominant PD sharing multiple nodes with the tremor network detected in ET, despite the generally lower structural connectivity between basal ganglia and frontal cortex in the whole PD group when compared to healthy controls.

CONCLUSION

The higher structural connectivity of the cerebello-thalamo-cortical network seems to be the dominant tremor driver in both PD and ET. While it appears to be the only tremor-related network in ET, its combination with large scale hypoconnectivity in the frontal cortico-subcortical network in PD may explain different clinical features of tremor in these two disorders.

Stability of AI-Enabled Diagnosis of Parkinson's Disease: A Study Targeting Substantia Nigra in Quantitative Susceptibility Mapping Imaging

Purpose: Parkinson's disease (PD) diagnosis algorithms based on quantitative susceptibility mapping (QSM) and image algorithms rely on substantia nigra (SN) labeling. However, the difference between SN labels from different experts (or segmentation algorithms) will have a negative impact on downstream diagnostic tasks, such as the decrease of the accuracy of the algorithm or different diagnostic results for the same sample. In this article, we quantify the accuracy of the algorithm on different label sets and then improve the convolutional neural network (CNN) model to obtain a high-precision and highly robust diagnosis algorithm. Methods: The logistic regression model and CNN model were first compared for classification between PD patients and healthy controls (HC), given different sets of SN labeling. Then, based on the CNN model with better performance, we further proposed a novel "gated pooling" operation and integrated it with deep learning to attain a joint framework for image segmentation and classification. Results: The experimental results show that, with different sets of SN labeling that mimic different experts, the CNN model can maintain a stable classification accuracy at around 86.4%, while the conventional logistic regression model yields a large fluctuation ranging from 78.9 to 67.9%. Furthermore, the "gated pooling" operation, after being integrated for joint image segmentation and classification, can improve the diagnosis accuracy to 86.9% consistently, which is statistically better than the baseline. Conclusion: The CNN model, compared with the conventional logistic regression model using radiomics features, has better stability in PD diagnosis. Furthermore, the joint end-to-end CNN model is shown to be suitable for PD diagnosis from the perspectives of accuracy, stability, and convenience in actual use.

It Is Time to Study Overlapping Molecular and Circuit Pathophysiologies in Alzheimer's and Lewy Body Disease Spectra

Alzheimer's disease (AD) is the leading cause of dementia due to neurodegeneration and is characterized by extracellular senile plaques composed of amyloid β1 - 42 (Aβ) as well as intracellular neurofibrillary tangles consisting of phosphorylated tau (p-tau). Dementia with Lewy bodies constitutes a continuous spectrum with Parkinson's disease, collectively termed Lewy body disease (LBD). LBD is characterized by intracellular Lewy bodies containing α-synuclein (α-syn). The core clinical features of AD and LBD spectra are distinct, but the two spectra share common cognitive and behavioral symptoms. The accumulation of pathological proteins, which acquire pathogenicity through conformational changes, has long been investigated on a protein-by-protein basis. However, recent evidence suggests that interactions among these molecules may be critical to pathogenesis. For example, Aβ/tau promotes α-syn pathology, and α-syn modulates p-tau pathology. Furthermore, clinical evidence suggests that these interactions may explain the overlapping pathology between AD and LBD in molecular imaging and post-mortem studies. Additionally, a recent hypothesis points to a common mechanism of prion-like progression of these pathological proteins, via neural circuits, in both AD and LBD. This suggests a need for understanding connectomics and their alterations in AD and LBD from both pathological and functional perspectives. In AD, reduced connectivity in the default mode network is considered a hallmark of the disease. In LBD, previous studies have emphasized abnormalities in the basal ganglia and sensorimotor networks; however, these account for movement disorders only. Knowledge about network abnormalities common to AD and LBD is scarce because few previous neuroimaging studies investigated AD and LBD as a comprehensive cohort. In this paper, we review research on the distribution and interactions of pathological proteins in the brain in AD and LBD, after briefly summarizing their clinical and neuropsychological manifestations. We also describe the brain functional and connectivity changes following abnormal protein accumulation in AD and LBD. Finally, we argue for the necessity of neuroimaging studies that examine AD and LBD cases as a continuous spectrum especially from the proteinopathy and neurocircuitopathy viewpoints. The findings from such a unified AD and Parkinson's disease (PD) cohort study should provide a new comprehensive perspective and key data for guiding disease modification therapies targeting the pathological proteins in AD and LBD.

Altered Brain Functional Network in Subtypes of Parkinson's Disease: A Dynamic Perspective

Background: Parkinson's disease (PD) is a highly heterogeneous disease, especially in the clinical characteristics and prognosis. The PD is divided into two subgroups: tremor-dominant phenotype and non-tremor-dominant phenotype. Previous studies reported abnormal changes between the two PD phenotypes by using the static functional connectivity analysis. However, the dynamic properties of brain networks between the two PD phenotypes are not yet clear. Therefore, we aimed to uncover the dynamic functional network connectivity (dFNC) between the two PD phenotypes at the subnetwork level, focusing on the temporal properties of dFNC and the variability of network efficiency.

Methods: We investigated the resting-state functional MRI (fMRI) data from 29 tremor-dominant PD patients (PDTD), 25 non-tremor-dominant PD patients (PDNTD), and 20 healthy controls (HCs). Sliding window approach, k-means clustering, independent component analysis (ICA), and graph theory analysis were applied to analyze the dFNC. Furthermore, the relationship between alterations in the dynamic properties and clinical features was assessed.

Results: The dFNC analyses identified four reoccurring states, one of them showing sparse connections (state I). PDTD patients stayed longer time in state I and showed increased FNC between BG and vSMN in state IV. Both PD phenotypes exhibited higher FNC between dSMN and FPN in state II and state III compared with the controls. PDNTD patients showed decreased FNC between BG and FPN but increased FNC in the bilateral FPN compared with both PDTD patients and controls. In addition, PDNTD patients exhibited greater variability in global network efficiency. Tremor scores were positively correlated with dwell time in state I along with increased FNC between BG and vSMN in state IV.

Conclusions: This study explores the dFNC between the PDTD and PDNTD patients, which offers new evidence on the abnormal time-varying brain functional connectivity and their network destruction of the two PD phenotypes, and may help better understand the neural substrates underlying different types of PD.

Consistency and Stability of Motor Subtype Classifications in Patients With de novo Parkinson's Disease

Objective

Patients with Parkinson’s disease (PD) are commonly classified into subtypes based on motor symptoms. The aims of the present study were to determine the consistency between PD motor subtypes, to assess the stability of PD motor subtypes over time, and to explore the variables influencing PD motor subtype stability.

Methods

This study was part of a longitudinal study of de novo PD patients at a single center. Based on three different motor subtype classification systems proposed by Jankovic, Schiess, and Kang, patients were respectively categorized as tremor-dominant/indeterminate/postural instability and gait difficulty (TD/indeterminate/PIGD), TD_S/mixed_S/akinetic-rigid_S (ARS), or TD_K/mixed_K/AR_K at baseline evaluation and then re-assessed 1 month later. Demographic and clinical characteristics were recorded at each evaluation. The consistency between subtypes at baseline evaluation was assessed using Cohen’s kappa coefficient (κ). Additional variables were compared between PD subtype groups using the two-sample t-test, Mann–Whitney U-test or Chi-squared test.

Results

Of 283 newly diagnosed, untreated PD patients, 79 were followed up at 1 month. There was fair agreement between the Jankovic, Schiess, and Kang classification systems (κ_S = 0.383 ± 0.044, κ_K = 0.360 ± 0.042, κ_SK = 0.368 ± 0.038). Among the three classification systems, the Schiess classification was the most stable and the Jankovic classification was the most unstable. The non-motor symptoms questionnaire (NMSQuest) scores differed significantly between PD patients with stable and unstable subtypes based on the Jankovic classification (p = 0.008), and patients with a consistent subtype had more severe NMSQuest scores than patients with an inconsistent subtype.

Conclusion

Fair consistency was observed between the Jankovic, Schiess, and Kang classification systems. For the first time, non-motor symptoms (NMSs) scores were found to influence the stability of the TD/indeterminate/PIGD classification. Our findings support combining NMSs with motor symptoms to increase the effectiveness of PD subtypes.

Disrupted interhemispheric coordination with unaffected lateralization of global eigenvector centrality characterizes hemiparkinsonism

OBJECTIVE

The motor dysfunctions always affect hemi-body first in Parkinson's disease (PD). However, the interhemispheric relationships in patients with only unilateral motor impairment were barely known to date. We aimed to investigate the interhemispheric functions using resting-state functional Magnetic resonance imaging (RS-fMRI) for further understanding the pathogenesis of PD.

METHODS

Forty-three unilateral-symptomatic PD patients (UPD, Hoehn-Yahr staging scale, H-Y: 1-1.5), and 54 age-, gender-, education-matched normal controls (NC) were recruited. All subjects underwent MRI scanning and clinical evaluations. The interhemispheric coordination (Voxel-Mirrored Homotopic Connectivity, VMHC) and hemispheric dominance pattern (laterality index of eigenvector centrality mapping, LI-ECM) were calculated. Afterwards, correlation analyses and receiver operating characteristic (ROC) curve analysis were employed.

RESULTS

Compared with NC, UPD group showed significantly decreased VMHC in bilateral sensorimotor regions which was negatively correlated with the motor score. Furthermore, at the cut-off homotopic connectivity of 0.604, statistically significant ability of VMHC to discriminate UPD from NC with area under ROC curve (AUC) = 0.759, p < 0.001; specificity = 74.4%; sensitivity = 68.5% was observed. No difference was detected in UPD patients as for ECM and LI-ECM.

CONCLUSIONS

The disrupted interhemispheric coordination in bilateral sensorimotor regions may have significant implications for elucidating the mechanisms underlying the hemiparkinsonism and enabling the uncovering of complex mechanisms of PD.

Use of Functional Magnetic Resonance Imaging to Assess How Motor Phenotypes of Parkinson's Disease Respond to Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) is a well-accepted treatment of Parkinson's disease (PD). Motor phenotypes include tremor-dominant (TD), akinesia-rigidity (AR), and postural instability gait disorder (PIGD). The mechanism of action in how DBS modulates motor symptom relief remains unknown.

OBJECTIVE

Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) was used to determine whether the functional activity varies in response to DBS depending on PD phenotypes.

MATERIALS AND METHODS

Subjects underwent an fMRI scan with DBS cycling ON and OFF. The effects of DBS cycling on BOLD activation in each phenotype were documented through voxel-wise analysis. For each region of interest, ANOVAs were performed using T-values and covariate analyses were conducted. Further, a correlation analysis was performed comparing stimulation settings to T-values. Lastly, T-values of subjects with motor improvement were compared to those who worsened.

RESULTS

As a group, BOLD activation with DBS-ON resulted in activation in the motor thalamus (p < 0.01) and globus pallidus externa (p < 0.01). AR patients had more activation in the supplementary motor area (SMA) compared to PIGD (p < 0.01) and TD cohorts (p < 0.01). Further, the AR cohort had more activation in primary motor cortex (MI) compared to the TD cohort (p = 0.02). Implanted nuclei (p = 0.01) and phenotype (p = <0.01) affected activity in MI and phenotype alone affected SMA activity (p = <0.01). A positive correlation was seen between thalamic activation and pulse-width (p = 0.03) and between caudate and total electrical energy delivered (p = 0.04).

CONCLUSIONS

These data suggest that DBS modulates network activity differently based on patient motor phenotype. Improved understanding of these differences may further our knowledge about the mechanisms of DBS action on PD motor symptoms and to optimize treatment.

Is Parkinson's disease an unique clinical entity? Rigid or tremor dominant PD: Two faces of the same coin

Parkinson's disease is one of the most described neurodegenerative pathologies; though it is one of the most complex pathologies, is not fully understood, correctly identified, with its different types of presentation, its clinical course and the neural networks involved. We report on a series consisting of 432 de novo PD diagnosed patients, and 457 control cases. We identify a possible independent relationship between two clinical PD presentation, akinetic-rigid and tremor-dominant, and cognitive and behavioral changes. A 24-months follow-up allows to identify new information still not fully explored.

Oscillation-specific nodal alterations in early to middle stages Parkinson's disease

BACKGROUND

Different oscillations of brain networks could carry different dimensions of brain integration. We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson's disease (PD) across early stage to middle stage by using graph theory-based analysis.

METHODS

Eighty-eight PD patients including 39 PD patients in the early stage (EPD) and 49 patients in the middle stage (MPD) and 36 controls were recruited in the present study. Graph theory-based network analyses from three oscillation frequencies (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; slow-3: 0.073-0.198 Hz) were analyzed. Nodal metrics (e.g. nodal degree centrality, betweenness centrality and nodal efficiency) were calculated.

RESULTS

Our results showed that (1) a divergent effect of oscillation frequencies on nodal metrics, especially on nodal degree centrality and nodal efficiency, that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed, which visually showed that network was perturbed in PD; (2) PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities, which was consistently detected within all three oscillation frequencies; (3) the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients; (4) logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level; (5) occipital disruption within high frequency (slow-3) made a significant influence on motor impairment which was dominated by akinesia and rigidity.

CONCLUSIONS

Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages.

Aberrant brain network connectivity in presymptomatic and manifest Huntington's disease: A systematic review

Resting‐state functional magnetic resonance imaging (rs‐fMRI) has the potential to shed light on the pathophysiological mechanisms of Huntington's disease (HD), paving the way to new therapeutic interventions. A systematic literature review was conducted in three online databases according to PRISMA guidelines, using keywords for HD, functional connectivity, and rs‐fMRI. We included studies investigating connectivity in presymptomatic (pre‐HD) and manifest HD gene carriers compared to healthy controls, implementing seed‐based connectivity, independent component analysis, regional property, and graph analysis approaches. Visual network showed reduced connectivity in manifest HD, while network/areas underpinning motor functions were consistently altered in both manifest HD and pre‐HD, showing disease stage‐dependent changes. Cognitive networks underlying executive and attentional functions showed divergent anterior–posterior alterations, possibly reflecting compensatory mechanisms. The involvement of these networks in pre‐HD is still unclear. In conclusion, aberrant connectivity of the sensory‐motor network is observed in the early stage of HD while, as pathology spreads, other networks might be affected, such as the visual and executive/attentional networks. Moreover, sensory‐motor and executive networks exhibit hyper‐ and hypo‐connectivity patterns following different spatiotemporal trajectories. These findings could potentially help to implement future huntingtin‐lowering interventions.

Increased functional connectivity of thalamic subdivisions in patients with Parkinson's disease

Parkinson’s disease (PD) affects 2–3% of the population over the age of 65 with loss of dopaminergic neurons in the substantia nigra impacting the functioning of basal ganglia-thalamocortical circuits. The precise role played by the thalamus is unknown, despite its critical role in the functioning of the cerebral cortex, and the abnormal neuronal activity of the structure in PD. Our objective was to more clearly elucidate how functional connectivity and morphology of the thalamus are impacted in PD (n = 32) compared to Controls (n = 20). To investigate functional connectivity of the thalamus we subdivided the structure into two important regions-of-interest, the first with putative connections to the motor cortices and the second with putative connections to prefrontal cortices. We then investigated potential differences in the size and shape of the thalamus in PD, and how morphology and functional connectivity relate to clinical variables. Our data demonstrate that PD is associated with increases in functional connectivity between motor subdivisions of the thalamus and the supplementary motor area, and between prefrontal thalamic subdivisions and nuclei of the basal ganglia, anterior and dorsolateral prefrontal cortices, as well as the anterior and paracingulate gyri. These results suggest that PD is associated with increased functional connectivity of subdivisions of the thalamus which may be indicative alterations to basal ganglia-thalamocortical circuitry.

Use of Magnetic Resonance Imaging and Artificial Intelligence in Studies of Diagnosis of Parkinson's Disease

Parkinson's disease (PD) is a common neurodegenerative disorder. It has a delitescent onset and a slow progress. The clinical manifestations of PD in patients are highly heterogeneous. Thus, PD diagnosis process is complex and mainly depends on the professional knowledge and experience of the physician. Magnetic resonance imaging (MRI) could detect the small changes in the brain of PD patients, and quantitative analysis of brain MRI may improve the clinical diagnosis efficiency. However, due to the complexity of clinical courses in PD and the high dimensionality in multimodal MRI data, traditional mathematical analysis could not effectively extract the huge information in them. Up to now, the accuracy of PD diagnosis in large sample size is still unsatisfying. As artificial intelligence (AI) is becoming more mature, varieties of statistical models and machine learning (ML) algorithms have been used for quantitative imaging data analysis to explore a diagnostic result. This review aims to state an overview of existing research recently that used statistical ML/AI methods to perform quantitative analysis of MR image data for the study of PD diagnosis. First we review the recent research in three subareas: diagnosis, differential diagnosis, and subtyping of PD. Then we described the overall workflow from MR image to classification result. Finally, we summarized a critical assessment of the current research and provide some recommendations for likely future research developments and trends.

Modulatory Effects of Levodopa on Cerebellar Connectivity in Parkinson's Disease

Levodopa has been the mainstay of symptomatic therapy for Parkinson's disease (PD) for the last five decades. However, it is associated with the development of motor fluctuations and dyskinesia, in particular after several years of treatment. The aim of this study was to shed light on the acute brain functional reorganization in response to a single levodopa dose. Functional magnetic resonance imaging (fMRI) was performed after an overnight withdrawal of dopaminergic treatment and 1 h after a single dose of 250 mg levodopa in a group of 24 PD patients. Eigenvector centrality was calculated in both treatment states using resting-state fMRI. This offers a new data-driven and parameter-free approach, similar to Google's PageRank algorithm, revealing brain connectivity alterations due to the effect of levodopa treatment. In all PD patients, levodopa treatment led to an improvement of clinical symptoms as measured with the Unified Parkinson's Disease Rating Scale motor score (UPDRS-III). This therapeutic effect was accompanied with a major connectivity increase between cerebellar brain regions and subcortical areas of the motor system such as the thalamus, putamen, globus pallidus, and brainstem. The degree of interconnectedness of cerebellar regions correlated with the improvement of clinical symptoms due to the administration of levodopa. We observed significant functional cerebellar connectivity reorganization immediately after a single levodopa dose in PD patients. Enhanced general connectivity (eigenvector centrality) was associated with better motor performance as assessed by UPDRS-III score. This underlines the importance of considering cerebellar networks as therapeutic targets in PD.

Exploring the association between Cerebral small-vessel diseases and motor symptoms in Parkinson's disease

OBJECTIVES

to explore the association between cerebral small-vessel diseases (CSVDs) and motor symptoms in Parkinson's disease (PD).

METHODS

137 PD patients were recruited into the study. Detailed motor symptoms, including tremor, rigidity, bradykinesia, and axial impairment, were evaluated using Unified Parkinson's disease Rating Scale (UPDRS). Non-motor symptoms, including cognition, anxiety, and depression, were evaluated using Montreal Cognitive Assessment (MoCA), Hamilton anxiety scale (HAMA), and Hamilton depression scale (HAMD). Brain MRI was used to assess the subtypes of CSVDs, including lacunes, enlarged perivascular spaces (EPVS), and white matter hyperintensities (WMH). WMH were furtherly divided into deep WMH (DWMH) and periventricular hyperintensities (PVH). The association between CSVDs and motor symptoms was analyzed. Patients were divided into the postural instability and gait disability (PIGD) group and non-PIGD group. Demographic, clinical and CSVDs variables were compared between the two groups.

RESULTS

CSVDs subtypes were all detected in the participants with different prevalence rates and severity degrees. We found a close association between EPVS in basal ganglia and the tremor score (p = 0.032), and between DWMH in the frontal and occipital lobes and the axial motor score (p < 0.05) through the spearman and multivariate liner regression analysis. Compared with the non-PIGD group, the PIGD group demonstrated more serious cognitive impairment and DWMH in the frontal and occipital lobes (p < 0.05). The demographic characteristics and vascular risk factors of the PIGD group were not different from those of the non-PIGD group. Cognitive impairment and DWMH in the frontal lobe were identified to be independent risk factors of PIGD motor phenotype.

CONCLUSIONS

We identified a close association between the CSVDs and motor symptoms in PD and DWMH in the frontal lobe was a risk factor of PIGD motor phenotype, which supports the contribution of vascular pathology in PD.

The Ventral Intermediate Nucleus Differently Modulates Subtype-Related Networks in Parkinson's Disease

Background: Posture instability gait difficulty-dominant (PIGD) and tremor-dominant (TD) are two subtypes of Parkinson's disease (PD). The thalamus is involved in the neural circuits of both subtypes. However, which subregion of the thalamus has an influence on the PD subtypes remains unclear. Objective: To explore the core subregion of the thalamus showing a significant influence on the PD subtypes and its directional interaction between the PD subtypes. Methods: A total of 79 PD patients (43 TD and 36 PIGD) and 31 normal controls (NC) were enrolled, and the gray matter volume and perfusion characteristics in the thalamus were compared between the three groups. The subregion of the thalamus with significantly different perfusion and volume among three groups was used as the seed of a Granger causality analysis (GCA) to compare the causal connectivity between different subtypes. Results: Perfusion with an increased gradient among the three groups (TD > PIGD > NC) in the bilateral ventral intermediate nucleus (Vim) was observed, which was positively correlated with the clinical tremor scores. The GCA revealed that TD patients had enhanced causal connectivity from the bilateral Vim to the bilateral paracentral gyrus, M1 and the cerebellum compared with the NC group, while the PIGD subtype revealed an increased causal connectivity from the bilateral Vim to the bilateral premotor cortex (preM) and putamen. Additionally, there were positive correlations between the tremor scores and a causal connectivity from the Vim to the cerebellum. The connectivity from the right Vim to the right preM and the right putamen was positively correlated with the PIGD scores. Conclusion: This multilevel analysis showed that the Vim had a significant influence on the PD subtypes and that it differentially mediated the TD and PIGD-related causal connectivity pattern in PD.

Iron-related nigral degeneration influences functional topology mediated by striatal dysfunction in Parkinson's disease

In Parkinson's disease (PD), iron accumulation in the substantia nigra (SN) exacerbates oxidative stress and α-synuclein aggregation, leading to neuronal death. However, the influence of iron-related nigral degeneration on the subcortical function and global network configuration in PD remains unknown. Ninety PD patients and 38 normal controls underwent clinical assessments and multimodality magnetic resonance imaging scans. Iron accumulation in the inferior SN and disrupted functional connectivity between the bilateral striatums were observed in PD, and negative correlation between them was found in the whole population. The binarized functional network exhibited enhanced global efficiency and reduced local efficiency while the weighted functional network exhibited reduction in both, and both changes were correlated with nigral iron accumulation in PD. Mediation analysis demonstrated that the functional connectivity between bilateral striatums was a mediator between the nigral iron accumulation and weighted functional network alterations. In conclusion, our findings reveal that iron-related nigral degeneration possibly influences the functional topology mediated by striatal dysfunction, which extends the scientific understanding of PD pathogenesis.

Functional imaging correlates of akinesia in Parkinson's disease: Still open issues

Akinesia is a major manifestation of Parkinson's disease (PD) related to difficulties or failures of willed movement to occur. Akinesia is still poorly understood and is not fully alleviated by standard therapeutic strategies. One reason is that the area of the clinical concept has blurred boundaries referring to confounded motor symptoms. Here, we review neuroimaging studies which, by providing access to finer-grained mechanisms, have the potential to reveal the dysfunctional brain processes that account for akinesia. It comes out that no clear common denominator could be identified across studies that are too heterogeneous with respect to the clinical/theoretical concepts and methods used. Results reveal, however, that various abnormalities within but also outside the motor and dopaminergic pathways might be associated with akinesia in PD patients. Notably, numerous yet poorly reproducible neural correlates were found in different brain regions supporting executive control by means of resting-state or task-based studies. This includes for instance the dorsolateral prefrontal cortex, the inferior frontal cortex, the supplementary motor area, the medial prefrontal cortex, the anterior cingulate cortex or the precuneus. This observation raises the issue of the multidimensional nature of akinesia. Yet, other open issues should be considered conjointly to drive future investigations. Above all, a unified terminology is needed to allow appropriate association of behavioral symptoms with brain mechanisms across studies. We adhere to a use of the term akinesia restricted to dysfunctions of movement initiation, ranging from delayed response to freezing or even total abolition of movement. We also call for targeting more specific neural mechanisms of movement preparation and action triggering with more sophisticated behavioral designs/event-related neurofunctional analyses. More work is needed to provide reliable evidence, but answering these still open issues might open up new prospects, beyond dopaminergic therapy, for managing this disabling symptom.

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No clear picture of the neural bases of PD akinesia can be drawn from the literature.

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Akinesia should be disentangled from bradykinesia and hypokinesia.

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Movement initiation dysfunctions may arise from both motor and executive disorders.

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Future neuroimaging studies should probe more specific neurocognitive processes.

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Future studies should look beyond the dopaminergic basal-ganglia circuitry.

Brain Functional Connectivity Plasticity Within and Beyond the Sensorimotor Network in Lower-Limb Amputees

Cerebral neuroplasticity after amputation has been elucidated by functional neuroimaging. However, little is known concerning how brain network-level functional reorganization of the sensorimotor system evolves following lower-limb amputation. We studied 32 unilateral lower-limb amputees (LLAs) and 32 matched healthy controls (HCs) using resting-state functional magnetic resonance imaging (rs-fMRI). A regions of interest (ROI)-wise connectivity analysis was performed with ROIs in eight brain regions in the sensorimotor network to investigate intra-network changes, and seed-based whole-brain functional connectivity (FC) with a seed in the contralateral primary sensorimotor cortex (S1M1) was used to study the FC reorganization between the sensorimotor region (S1M1) and other parts of the brain in the LLAs. The ROI-wise connectivity analysis showed that the LLAs had decreased FC, mainly between the subcortical nuclei and the contralateral S1M1 (p < 0.05, FDR corrected). Seed-based whole-brain FC analysis revealed that brain regions with decreased FC with the contralateral S1M1 extended beyond the sensorimotor network to the prefrontal and visual cortices (p < 0.05, FDR corrected). Moreover, correlation analysis showed that decreased FC between the subcortical and the cortical regions in the sensorimotor network progressively increased in relation to the time since amputation. These findings indicated a cascade of cortical reorganization at a more extensive network level following lower-limb amputation, and also showed promise for the development of a possible neurobiological marker of changes in FC related to motor function recovery in LLAs.

Brain Atrophy and Reorganization of Structural Network in Parkinson's Disease With Hemiparkinsonism

Hemiparkinsonism duration in patients with Parkinson's disease (PD) is a key time window to study early pathology of PD. We aimed to comprehensively explore the alterations of deformation and structural network in PD patients with hemiparkinsonism, which could potentially disclose the early biomarker for PD. Thirty-one PD patients with hemiparkinsonism and 37 age- and gender- matched normal controls were included in the present study. First of all, we normalized the left hemisphere of structural images as the contralateral side to the affected limbs. Deformation-based morphometry (DBM) was conducted to evaluate the brain atrophy and/or enlargement. structural networks were constructed by thresholding gray matter volume correlation matrices of 116 regions and analyzed using graph theoretical approaches (e.g., small-worldness, global, and nodal measures). Significantly decreased deformation values were observed in the temporoparietal regions like bilateral middle temporal gyri, ipsilateral precuneus and contralateral Rolandic operculum extending to supramarginal and postcentral gyri. Lower deformation values in contralateral middle temporal gyrus were negatively correlated with higher motor impairment which was dominated by akinesia/rigidity. Moreover, nodal reorganization of structural network mainly located in frontal, temporal, subcortex and cerebellum was bilaterally explored in PD patients with hemiparkinsonism. Increased nodal properties could be commonly observed in frontal lobes. Disruption of subcortex including basal ganglia and amygdala was detected by nodal local efficiency and nodal clustering coefficient. Twelve hubs, mainly from paralimbic-limbic and heteromodal networks, were disrupted and, alternatively, 14 hubs, most of which were located in frontal lobes, were additionally detected in PD patients with hemiparkinsonism. In conclusion, during hemiparkinsonism period, mild brain atrophy in the temporoparietal regions and widespread reorganization of structural network, e.g., enhanced frontal function and disruption of basal ganglia nodes, occurred in both hemispheres. With our data, we can also argue that MTG contralateral to the affected limbs (expressing clinically verified brain atrophy) might be a potential living biomarker to monitor disease progression. Therefore, the combination of DBM and structural network analyses can provide a comprehensive and sensitive evaluation for potential pathogenesis of early PD patients with hemiparkinsonism.