Disrupted Brain Network Hubs in Subtype-Specific Parkinson's Disease

Reorganization of structural brain networks in Parkinson's disease with postural instability/gait difficulty

The Postural Instability/Gait Difficulty (PIGD) subtype of Parkinson's disease (PD) has a faster disease progression, a higher risk of cognitive and motor decline, yet the alterations of structural topological organization remain unknown. Diffusion Tensor Imaging (DTI) and 3D-TI scanning were conducted on 31 PD patients with PIGD (PD-PIGD), 30 PD patients without PIGD (PD-non-PIGD) and 35 Healthy Controls (HCs). Structural networks were constructed using DTI brain white matter fiber tractography. A graph theory approach was applied to characterize the topological properties of complex structural networks, and the relationships between significantly different network metrics and motor deficits were analyzed within the PD-PIGD group. PD-PIGD patients exhibited increased shortest path length compared with PD-non-PIGD and HCs (P < 0.05, respectively). Additionally, PD-PIGD patients exhibited decreased nodal properties, mainly in the cerebellar vermis, prefrontal cortex, paracentral lobule, and visual regions. Notably, the degree centrality of the cerebellar vermis was negatively correlated with the PIGD score (r = -0.390; P = 0.030) and Unified Parkinson's Disease Rating Scale Part III score (r = -0.436; P = 0.014) in PD-PIGD patients. Furthermore, network-based statistical analysis revealed decreased structural connectivity between the prefrontal lobe, putamen, supplementary motor area, insula, and cingulate gyrus in PD-PIGD patients. Our findings demonstrated that PD-PIGD patients existed abnormal structural connectomes in the cerebellar vermis, frontal-parietal cortex and visual regions. These topological differences can provide a topological perspective for understanding the potential pathophysiological mechanisms of PIGD in PD.

Functional connectivity-based classification of rapid eye movement sleep behavior disorder

BACKGROUND

Isolated rapid eye movement sleep behavior disorder (iRBD) is a clinically important parasomnia syndrome preceding α-synucleinopathies, thereby prompting us to develop methods for evaluating latent brain states in iRBD. Resting-state functional magnetic resonance imaging combined with a machine learning-based classification technology may help us achieve this purpose.

METHODS

We developed a machine learning-based classifier using functional connectivity to classify 55 patients with iRBD and 97 healthy elderly controls (HC). Selecting 55 HCs randomly from the HC dataset 100 times, we conducted a classification of iRBD and HC for each sampling, using functional connectivity. Random forest ranked the importance of functional connectivity, which was subsequently used for classification with logistic regression and a support vector machine. We also conducted correlation analysis of the selected functional connectivity with subclinical variations in motor and non-motor functions in the iRBDs.

RESULTS

Mean classification performance using logistic regression was 0.649 for accuracy, 0.659 for precision, 0.662 for recall, 0.645 for f1 score, and 0.707 for the area under the receiver operating characteristic curve (p < 0.001 for all). The result was similar in the support vector machine. The classifier used functional connectivity information from nine connectivities across the motor and somatosensory areas, parietal cortex, temporal cortex, thalamus, and cerebellum. Inter-individual variations in functional connectivity were correlated with the subclinical motor and non-motor symptoms of iRBD patients.

CONCLUSIONS

Machine learning-based classifiers using functional connectivity may be useful to evaluate latent brain states in iRBD.

Brain connectivity for subtypes of parkinson's disease using structural MRI

Objective. Delineating Parkinson's disease (PD) into distinct subtypes is a major challenge. Most studies use clinical symptoms to label PD subtypes while our work uses an imaging-based data-mining approach to subtype PD. Our study comprises two major objectives - firstly, subtyping Parkinson's patients based on grey matter information from structural magnetic resonance imaging scans of human brains; secondly, comparative structural brain connectivity analysis of PD subtypes derived from the former step.Approach. Source-based-morphometry decomposition was performed on 131 Parkinson's patients and 78 healthy controls from PPMI dataset, to derive at components (regions) with significance in disease and high effect size. The loading coefficients of significant components were thresholded for arriving at subtypes. Further, regional grey matter maps of subtype-specific subjects were separately parcellated and employed for construction of subtype-specific association matrices using Pearson correlation. These association matrices were binarized using sparsity threshold and leveraged for structural brain connectivity analysis using network metrics.Main results. Two distinct Parkinson's subtypes (namely A and B) were detected employing loadings of two components satisfying the selection criteria, and a third subtype (AB) was detected, common to these two components. Subtype A subjects were highly weighted in inferior, middle and superior frontal gyri while subtype B subjects in inferior, middle and superior temporal gyri. Network metrics analyses through permutation test revealed significant inter-subtype differences (p < 0.05) in clustering coefficient, local efficiency, participation coefficient and betweenness centrality. Moreover, hubs were obtained using betweenness centrality and mean network degree.Significance. MRI-based data-driven subtypes show frontal and temporal lobes playing a key role in PD. Graph theory-driven brain network analyses could untangle subtype-specific differences in structural brain connections showing differential network architecture. Replication of these initial results in other Parkinson's datasets may be explored in future. Clinical Relevance- Investigating structural brain connections in Parkinson's disease may provide subtype-specific treatment.

Convergent and divergent intra- and internetwork connectivity in Parkinson's disease with wearing-off

OBJECTIVE

Our study aimed to explore the functional connectivity alterations between cortical nodes of resting-state networks in Parkinson's disease (PD) patients with wearing-off (WO) at different levels.

METHODS

Resting-state functional magnetic resonance imaging was performed on 36 PD patients without wearing-off (PD-nWO), 30 PD patients with wearing-off (PD-WO), and 35 healthy controls (HCs) to extract functional networks. Integrity, network, and edge levels were calculated for comparison between groups. UPDRS-III, MMSE, MOCA, HAMA, and HAMD scores were collected for further regression analysis.

RESULTS

We observed significantly reduced connectivity strength in the dorsal attention network and limbic network in the PD-WO group compared with the HC group. The PD-WO group showed a decreased degree of functional connectivity at 12 nodes, including the bilateral orbital part of the superior frontal gyrus, right olfactory cortex, left medial orbital part of the superior frontal gyrus, bilateral gyrus rectus, right parahippocampal gyrus, right thalamus, left Heschl's gyrus, right superior temporal gyrus part of the temporal pole, left middle temporal gyrus part of the temporal pole, and right inferior temporal gyrus. Furthermore, the PD-WO group showed a significantly lower degree of functional connectivity in the left orbital part of the superior frontal gyrus and right gyrus rectus than the PD-nWO group. Internetwork analysis indicated reduced functional connectivity in five pairs of resting-state networks.

CONCLUSION

Our results demonstrated altered intra- and internetwork connections in PD patients with WO. These findings will facilitate a better understanding of the distinction between the network changes in PD pathophysiology.

Cerebellar functional connectivity change is associated with motor and neuropsychological function in early stage drug-naïve patients with Parkinson's disease

Introduction

Parkinson's Disease (PD) is a progressive neurodegenerative disorder affecting both motor and cognitive function. Previous neuroimaging studies have reported altered functional connectivity (FC) in distributed functional networks. However, most neuroimaging studies focused on patients at an advanced stage and with antiparkinsonian medication. This study aims to conduct a cross-sectional study on cerebellar FC changes in early-stage drug-naïve PD patients and its association with motor and cognitive function.

Methods

Twenty-nine early-stage drug-naïve PD patients and 20 healthy controls (HCs) with resting-state fMRI data and motor UPDRS and neuropsychological cognitive data were extracted from the Parkinson's Progression Markers Initiative (PPMI) archives. We used seed-based resting-state fMRI (rs-fMRI) FC analysis and the cerebellar seeds were defined based on the hierarchical parcellation of the cerebellum (AAL atlas) and its topological function mapping (motor cerebellum and non-motor cerebellum).

Results

The early stage drug-naïve PD patients had significant differences in cerebellar FC when compared with HCs. Our findings include: (1) Increased intra-cerebellar FC within motor cerebellum, (2) increase motor cerebellar FC in inferior temporal gyrus and lateral occipital gyrus within ventral visual pathway and decreased motor-cerebellar FC in cuneus and dorsal posterior precuneus within dorsal visual pathway, (3) increased non-motor cerebellar FC in attention, language, and visual cortical networks, (4) increased vermal FC in somatomotor cortical network, and (5) decreased non-motor and vermal FC within brainstem, thalamus and hippocampus. Enhanced FC within motor cerebellum is positively associated with the MDS-UPDRS motor score and enhanced non-motor FC and vermal FC is negatively associated with cognitive function test scores of SDM and SFT.

Conclusion

These findings provide support for the involvement of cerebellum at an early stage and prior to clinical presentation of non-motor features of the disease in PD patients.

Cerebellar alterations in Parkinson's disease with postural instability and gait disorders

BACKGROUND

Few studies interrogated the involvement of cerebellum in modulating gait in Parkinson's disease (PD) patients with postural instability and gait disorders (PD-PIGD). This study aimed at assessing cerebellar atrophy and activity alterations during functional MRI (fMRI) gait-simulating motor- and dual-tasks in PD-PIGD.

METHODS

Twenty-one PD-PIGD and 23 healthy controls underwent clinical assessment, structural MRI, and fMRI including a motor-task (foot anti-phase movements) and a dual-task (foot anti-phase movements while counting backwards by threes). Grey matter cerebellar volumes were assessed using SUIT atlas. FMRI activations were extracted from each cerebellar lobule, and we correlated cerebellar and basal ganglia activity.

RESULTS

PD-PIGD patients had reduced volumes of cerebellar motor and non-motor areas relative to controls. During fMRI motor-task, patients showed greater activation of cognitive cerebellar areas (VI and Crus I-II) vs controls. During fMRI dual-task, PD-PIGD patients showed increased activity of cognitive areas (Crus II) and reduced activity of motor areas (I-IV). Cerebellar structural alterations correlated with increased fMRI activity of cerebellar cognitive areas and with lower executive-attentive performance. The increased activity of Crus I during the motor-task correlated with a better motor performance in PD-PIGD. Moreover, the increased activity of cerebellum correlated with a reduced activity of putamen.

CONCLUSIONS

In PD-PIGD, the increased activity of non-motor cerebellar areas during gait-simulating tasks may be a consequence of grey matter atrophy or an attempt to compensate the functional failure of cerebellar motor areas and basal ganglia. Cerebellar MRI metrics are useful to characterize brain correlates of motor and dual-task abilities in PD-PIGD patients.

The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms

The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.

Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI

BACKGROUND

Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive.

OBJECTIVES

Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures.

METHODS

A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes.

RESULTS

Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described.

CONCLUSION

Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.

Cerebro-cerebellar motor networks in clinical subtypes of Parkinson’s disease

Parkinson’s disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD.

Structural Brain Network Abnormalities in Parkinson’s Disease With Freezing of Gait

Objective

Diffusion tensor imaging (DTI) studies have investigated white matter (WM) integrity abnormalities in Parkinson’s disease (PD). However, little is known about the topological changes in the brain network. This study aims to reveal these changes by comparing PD without freezing of gait (FOG) (PD FOG–), PD with FOG (PD FOG+), and healthy control (HC).

Methods

21 PD FOG+, 34 PD FOG-, and 23 HC were recruited, and DTI images were acquired. The graph theoretical analysis and network-based statistical method were used to calculate the topological parameters and assess connections.

Results

PD FOG+ showed a decreased normalized clustering coefficient, small-worldness, clustering coefficient, and increased local network efficiency compared with HCs. PD FOG+ showed decreased centrality, degree centrality, and nodal efficiency in the striatum, frontal gyrus, and supplementary motor area (SMA). PD FOG+ showed decreased connections in the frontal gyrus, cingulate gyrus, and caudate nucleus (CAU). The between centrality of the left SMA and left CAU was negatively correlated with FOG questionnaire scores.

Conclusion

This study demonstrates that PD FOG+ exhibits disruption of global and local topological organization in structural brain networks, and the disrupted topological organization can be potential biomarkers in PD FOG+. These new findings may provide increasing insight into the pathophysiological mechanism of PD FOG+.

Altered Intra- and Inter-Network Connectivity in Drug-Naïve Patients With Early Parkinson’s Disease

The aim of our study was to investigate differences in whole brain connectivity at different levels between drug-naïve individuals with early Parkinson’s disease (PD) and healthy controls (HCs). Resting-state functional magnetic resonance imaging data were collected from 47 patients with early-stage, drug-naïve PD and 50 HCs. Functional brain connectivity was analyzed at the integrity, network, and edge levels; UPDRS-III, MMSE, MOCA, HAMA, and HAMD scores, reflecting the symptoms of PD, were collected for further regression analysis. Compared with age-matched HCs, reduced functional connectivity were mainly observed in the visual (VSN), somatomotor (SMN), limbic (LBN), and deep gray matter networks (DGN) at integrity level [p < 0.05, false discovery rate (FDR) corrected]. Intra-network analysis indicated decreased functional connectivity in DGN, SMN, LBN, and ventral attention networks (VAN). Inter-network analysis indicated reduced functional connectivity in nine pairs of resting-state networks. At the edge level, the LBN was the center of abnormal functional connectivity (p < 0.05, FDR corrected). MOCA score was associated with the intra-network functional connectivity strength (FC) of the DGN, and inter-network FC of the DGN-VAN. HAMA and HAMD scores were associated with the FC of the SMN and DGN, and either the LBN or VAN, respectively. We demonstrated variations in whole brain connections of drug-naïve patients with early PD. Major changes involved the SMN, DGN, LBN, and VSN, which may be relevant to symptoms of early PD. Additionally, our results support PD as a disconnection syndrome.

Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.

Dynamic Network Connectivity Reveals Markers of Response to Deep Brain Stimulation in Parkinson's Disease

Background: Neuronal loss in Parkinson's Disease (PD) leads to widespread neural network dysfunction. While graph theory allows for analysis of whole brain networks, patterns of functional connectivity (FC) associated with motor response to deep brain stimulation of the subthalamic nucleus (STN-DBS) have yet to be explored. Objective/Hypothesis: To investigate the distributed network properties associated with STN-DBS in patients with advanced PD. Methods: Eighteen patients underwent 3-Tesla resting state functional MRI (rs-fMRI) prior to STN-DBS. Improvement in UPDRS-III scores following STN-DBS were assessed 1 year after implantation. Independent component analysis (ICA) was applied to extract spatially independent components (ICs) from the rs-fMRI. FC between ICs was calculated across the entire time series and for dynamic brain states. Graph theory analysis was performed to investigate whole brain network topography in static and dynamic states. Results: Dynamic analysis identified two unique brain states: a relative hypoconnected state and a relative hyperconnected state. Time spent in a state, dwell time, and number of transitions were not correlated with DBS response. There were no significant FC findings, but graph theory analysis demonstrated significant relationships with STN-DBS response only during the hypoconnected state - STN-DBS was negatively correlated with network assortativity. Conclusion: Given the widespread effects of dopamine depletion in PD, analysis of whole brain networks is critical to our understanding of the pathophysiology of this disease. Only by leveraging graph theoretical analysis of dynamic FC were we able to isolate a hypoconnected brain state that contained distinct network properties associated with the clinical effects of STN-DBS.

Changes in Metabolic Activity and Gait Function by Dual-Task Cognitive Game-Based Treadmill System in Parkinson's Disease: Protocol of a Randomized Controlled Trial

Balance and gait impairments, and consequently, mobility restrictions and falls are common in Parkinson’s disease (PD). Various cognitive deficits are also common in PD and are associated with increased fall risk. These mobility and cognitive deficits are limiting factors in a person’s health, ability to perform activities of daily living, and overall quality of life. Community ambulation involves many dual-task (DT) conditions that require processing of several cognitive tasks while managing or reacting to sudden or unexpected balance challenges. DT training programs that can simultaneously target balance, gait, visuomotor, and cognitive functions are important to consider in rehabilitation and promotion of healthy active lives. In the proposed multi-center, randomized controlled trial (RCT), novel behavioral positron emission tomography (PET) brain imaging methods are used to evaluate the molecular basis and neural underpinnings of: (a) the decline of mobility function in PD, specifically, balance, gait, visuomotor, and cognitive function, and (b) the effects of an engaging, game-based DT treadmill walking program on mobility and cognitive functions. Both the interactive cognitive game tasks and treadmill walking require continuous visual attention, and share spatial processing functions, notably to minimize any balance disturbance or gait deviation/stumble. The ability to “walk and talk” normally includes activation of specific regions of the prefrontal cortex (PFC) and the basal ganglia (site of degeneration in PD). The PET imaging analysis and comparison with healthy age-matched controls will allow us to identify areas of abnormal, reduced activity levels, as well as areas of excessive activity (increased attentional resources) during DT-walking. We will then be able to identify areas of brain plasticity associated with improvements in mobility functions (balance, gait, and cognition) after intervention. We expect the gait-cognitive training effect to involve re-organization of PFC activity among other, yet to be identified brain regions. The DT mobility-training platform and behavioral PET brain imaging methods are directly applicable to other diseases that affect gait and cognition, e.g., cognitive vascular impairment, Alzheimer’s disease, as well as in aging.

Disrupted morphological grey matter networks in early-stage Parkinson's disease

While previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis.

Neuroimaging Detectable Differences between Parkinson's Disease Motor Subtypes: A Systematic Review

BACKGROUND

The neuroanatomical substrates of Parkinson's disease (PD) with tremor-dominance (TD) and those with non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not fully differentiated. A better understanding of symptom specific pathoanatomical markers of PD subtypes may result in earlier diagnosis and more tailored treatment. Here, we aim to give an overview of the neuroimaging literature that compared PD motor subtypes.

METHODS

A systematic literature review on neuroimaging studies of PD subtypes was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Search terms submitted to the PubMed database included: "Parkinson's disease", "MRI" and "motor subtypes" (TD, nTD, PIGD, AR). The results are first discussed from macro to micro level of organization (i.e., (1) structural; (2) functional; and (3) molecular) and then by applied imaging methodology.

FINDINGS

Several neuroimaging methods including diffusion imaging and positron emission tomography (PET) distinguish specific PD motor subtypes well, although findings are mixed. Furthermore, our review demonstrates that nTD-PD patients have more severe neuroalterations compared to TD-PD patients. More specifically, nTD-PD patients have deficits within striato-thalamo-cortical (STC) circuitry and other thalamocortical projections related to cognitive and sensorimotor function, while TD-PD patients tend to have greater cerebello-thalamo-cortical (CTC) circuitry dysfunction.

CONCLUSIONS

Based on the literature, STC and CTC circuitry deficits seem to be the key features of PD and the subtypes. Future research should make greater use of multimodal neuroimaging and techniques that have higher sensitivity in delineating subcortical structures involved in motor diseases.

Brain networks associated with anticipatory postural adjustments in Parkinson's disease patients with freezing of gait

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High hemodynamic response in the AI and SMA in the FoG when an APA was required.

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Connectivity between the right and left insulae was correlated with severity of FoG.

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Both groups showed different brain network organizations between SMA and bilateral AI.

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SMA was found to be a hub in patients with FoG when an APA was required.

Specific impairments of anticipatory postural adjustment (APA) during step initiation have been reported in patients with Parkinson’s disease (PD) and freezing of gait (FoG). Although APA disruption has been associated with FoG, there is scarce knowledge about its neural correlates. We sought to better understand the neural networks involved with APA in patients with FoG by assessing the level of hemodynamic response of specific brain regions and the functional connectivity during the leg lifting task. In the current investigation, APAs of patients with PD, with and without (nFoG) freezing were assessed during a leg lifting task in an event-related, functional magnetic resonance imaging (er-fMRI) protocol. Results identified a high hemodynamic response in the right anterior insula (AI) and supplementary motor area (SMA) in the FoG group when an APA was required. The nFoG had stronger connectivity between the right and left insulae than the FoG group. The strength of this connectivity was negatively correlated with the severity of FoG. Both groups showed different brain network organizations comprising the SMA and the bilateral AI. The SMA was found to be a hub in patients with FoG when an APA was required for the task. Our findings suggest that both groups used compensatory mechanism comprising the insulae during APA. Neither group used the entire network comprised of the insulae and SMA to accomplish the task. The FoG group relied more on SMA as a hub than as part of a broader network to exchange information during the APA.

An investigation of thalamic nuclei volumes and the intrinsic thalamic structural network based on motor subtype in drug naïve patients with Parkinson's disease

INTRODUCTION

This study aimed to investigate the alterations in thalamic nuclei volumes and the intrinsic thalamic structural network in patients with de novo Parkinson's disease (PD) based on their predominant symptoms.

METHODS

We enrolled 65 patients with de novo PD (44 patients with tremor-dominant [TD] subtype and 21 patients with postural instability and gait disturbance [PIGD] subtype) and 20 healthy controls. All subjects underwent three-dimensional T1-weighted magnetic resonance imaging. The thalamic nuclei were segmented using the FreeSurfer program.

RESULTS

We obtained volumetric differences in the thalamic nuclei of each subtype of PD in comparison of healthy control. Volumes of the right and left suprageniculate nuclei were significantly increased, whereas that of the left parafascicular nucleus was decreased in patients with the TD subtype. Volumes of the right and left suprageniculate nuclei and right ventromedial nucleus were significantly increased, whereas those of the right and left parafascicular nuclei volumes were decreased in patients with the PIGD subtype. The measures of the intrinsic thalamic global network were not different between patients with TD PD and healthy controls. However, in patients with the PIGD subtype, the global and local efficiencies were significantly increased compared to healthy controls. Moreover, although there were no differences in thalamic volume and intrinsic thalamic global network between patients with the TD and PIGD variants, we identified significant differences in the intrinsic thalamic local network between the two groups.

CONCLUSIONS

Alterations in thalamic nuclei volumes and the intrinsic thalamic network in patients with PD differed based on their predominant symptoms. These findings might be related to the underlying pathogenesis and suggest that PD is a heterogeneous syndrome.

Multimodal Evaluation of Neurovascular Functionality in Early Parkinson's Disease

Parkinson's disease (PD) is a multisystem neurological condition affecting different neurotransmitter pathways characterized by aberrant functional connectivity (FC) and perfusion alteration. Since the FC, measuring neuronal activity, and cerebral blood flow (CBF) are closely related through the neurovascular coupling (NVC) mechanism, we aim to assess whether FC changes found in PD mirror perfusion ones. A multimodal MRI study was implemented by acquiring resting state functional MRI (rsfMRI) and arterial spin labeling (ASL) datasets on a group of 26 early PD (66.8 ± 8 years, 22 males, median [interquartile range] Hoehn and Yahr = 1.5 [1]) and 18 age- and sex-matched healthy controls (HCs). In addition, a T1-weighted MPRAGE was also acquired in the same scan session. After a standard preprocessing, resting state networks (RSNs) and CBF maps were extracted from rsfMRI and ASL dataset, respectively. Then, by means of a dual regression algorithm performed on RSNs, a cluster of FC differences between groups was obtained and used to mask CBF maps in the subsequent voxel-wise group comparison. Furthermore, a gray matter (GM) volumetric assessment was performed within the FC cluster in order to exclude tissue atrophy as a source of functional changes. Reduced FC for a PD patient with respect to HC group was found within a sensory-motor network (SMN, p_FWE = 0.01) and visual networks (VNs, primary p_FWE = 0.022 and lateral p_FWE = 0.01). The latter was accompanied by a decreased CBF (primary p_FWE = 0.037, lateral p_FWE = 0.014 VNs), while no GM atrophy was detected instead. The FC alteration found in the SMN of PD might be likely due to a dopaminergic denervation of the striatal pathways causing a functional disconnection. On the other hand, the changes in connectivity depicted in VNs might be related to an altered non-dopaminergic system, since perfusion was also reduced, revealing a compromised NVC. Finally, the absence of GM volume loss might imply that functional changes may potentially anticipate neurodegeneration. In this framework, FC and CBF might be proposed as early functional biomarkers providing meaningful insights in evaluating both disease progression and therapeutic/rehabilitation treatment outcome.

Functional Connectivity Signatures of Parkinson's Disease

 Resting-state functional magnetic resonance imaging (RS-fMRI) studies have been extensively applied to analyze the pathophysiology of neurodegenerative disorders such as Parkinson’s disease (PD). In the present narrative review, we attempt to summarize the most recent RS-fMRI findings highlighting the role of brain networks re-organization and adaptation in the course of PD. We also discuss limitations and potential definition of early functional connectivity signatures to track and predict future PD progression. Understanding the neural correlates and potential predisposing factors of clinical progression and complication will be crucial to guide novel clinical trials and to foster preventive strategies.

Music Therapy and Music-Based Interventions for Movement Disorders

PURPOSE OF REVIEW

There is emerging evidence that music therapy and other methods using music and rhythm may meaningfully improve a broad range of symptoms in neurological and non-neurological disorders. This review highlights the findings of recent studies utilizing music and rhythm-based interventions for gait impairment, other motor symptoms, and non-motor symptoms in Parkinson disease (PD) and other movement disorders. Limitations of current studies as well as future research directions are discussed.

RECENT FINDINGS

Multiple studies have demonstrated short-term benefits of rhythmic auditory stimulation on gait parameters including gait freezing in PD, with recent studies indicating that it may reduce falls. Demonstration of benefits for gait in both dopaminergic "on" and "off" states suggests that this intervention can be a valuable addition to the current armamentarium of PD therapies. There is also emerging evidence of motor and non-motor benefits from group dancing, singing, and instrumental music performance in PD. Preliminary evidence for music therapy and music-based interventions in movement disorders other than PD (such as Huntington disease, Tourette syndrome, and progressive supranuclear palsy) is limited but promising. Music therapy and other music and rhythm-based interventions may offer a range of symptomatic benefits to patients with PD and other movement disorders. Studies investigating the potential mechanisms of music's effects and well-controlled multicenter trials of these interventions are urgently needed.

Emergent Functional Network Effects in Parkinson Disease

The hallmark pathology underlying Parkinson disease (PD) is progressive synucleinopathy, beginning in caudal brainstem that later spreads rostrally. However, the primarily subcortical pathology fails to account for the wide spectrum of clinical manifestations in PD. To reconcile these observations, resting-state functional connectivity (FC) can be used to examine dysfunction across distributed brain networks. We measured FC in a large, single-site study of nondemented PD (N = 107; OFF medications) and healthy controls (N = 46) incorporating rigorous quality control measures and comprehensive sampling of cortical, subcortical and cerebellar regions. We employed novel statistical approaches to determine group differences across the entire connectome, at the network-level, and for select brain regions. Group differences respected well-characterized network delineations producing a striking "block-wise" pattern of network-to-network effects. Surprisingly, these results demonstrate that the greatest FC differences involve sensorimotor, thalamic, and cerebellar networks, with notably smaller striatal effects. Split-half replication demonstrates the robustness of these results. Finally, block-wise FC correlations with behavior suggest that FC disruptions may contribute to clinical manifestations in PD. Overall, these results indicate a concerted breakdown of functional network interactions, remote from primary pathophysiology, and suggest that FC deficits in PD are related to emergent network-level phenomena rather than focal pathology.

Network imaging biomarkers: insights and clinical applications in Parkinson's disease

Parkinson's disease presents several practical challenges: it can be difficult to distinguish from atypical parkinsonian syndromes, clinical ratings can be insensitive as markers of disease progression, and its non-motor manifestations are not readily assessed in animal models. These challenges, along with others, are beginning to be addressed by innovative imaging methods to characterise Parkinson's disease-specific functional networks across the whole brain and measure their expression in each patient. These signatures can help improve differential diagnosis, guide selection of patients for clinical trials, and quantify treatment responses and placebo effects in individual patients. The primary Parkinson's disease-related metabolic pattern has been replicated in multiple patient populations and used as an outcome measure in clinical trials. It can also be used as a predictor of near-term phenoconversion in prodromal syndromes, such as rapid eye movement sleep behaviour disorder. Functional network imaging holds great promise for future clinical use in the management of neurodegenerative disorders.

Brain imaging of locomotion in neurological conditions

Impaired locomotion is a frequent and major source of disability in patients with neurological conditions. Different neuroimaging methods have been used to understand the brain substrates of locomotion in various neurological diseases (mainly in Parkinson's disease) during actual walking, and while resting (using mental imagery of gait, or brain-behavior correlation analyses). These studies, using structural (i.e., MRI) or functional (i.e., functional MRI or functional near infra-red spectroscopy) brain imaging, electrophysiology (i.e., EEG), non-invasive brain stimulation (i.e., transcranial magnetic stimulation, or transcranial direct current stimulation) or molecular imaging methods (i.e., PET, or SPECT) reveal extended brain networks involving both grey and white matters in key cortical (i.e., prefrontal cortex) and subcortical (basal ganglia and cerebellum) regions associated with locomotion. However, the specific roles of the various pathophysiological mechanisms encountered in each neurological condition on the phenotype of gait disorders still remains unclear. After reviewing the results of individual brain imaging techniques across the common neurological conditions, such as Parkinson's disease, dementia, stroke, or multiple sclerosis, we will discuss how the development of new imaging techniques and computational analyses that integrate multivariate correlations in "large enough datasets" might help to understand how individual pathophysiological mechanisms express clinically as an abnormal gait. Finally, we will explore how these new analytic methods could drive our rehabilitative strategies.

Patterns of striatal and cerebellar functional connectivity in early-stage drug-naïve patients with Parkinson's disease subtypes

PURPOSE

Both the striatal-thalamo-cortical (STC) circuit and cerebello-thalamo-cortical (CTC) circuit play a critical role in Parkinson's disease (PD).

METHODS

Resting-state functional MRI was used to assess functional connectivity (FC) focusing on the basal ganglia (BG) and cerebellum among early-stage drug-naïve PD patients with tremor-dominant (TD) PD patients with postural instability and gait dysfunction (PIGD) and healthy controls (HCs).

RESULTS

Compared to HCs, both PD subgroups had higher FC between the cerebellum and paracentral lobule, sensorimotor areas; lower FC between the BG and superior frontal gyrus, and within the BG circuit; PD-TD patients showed higher FC between the BG and fusiform, paracentral lobule, cerebellum Lobule VI, and between the cerebellum and supplementary motor areas (SMA), insula; lower FC between the BG and rectus, sensorimotor areas, and within the cerebellum circuit; PD-PIGD patients showed higher FC between the cerebellum and middle frontal gyrus, precuneus; lower FC between the BG and cerebellum Crus II. Besides, compared to PD-PIGD patients and HCs, PD-TD patients had higher FC between the BG and calcarine region. In all PD patients, FC in paracentral lobule, SMA, and cerebellum Lobule VI positively correlated with tremor scores, and FC in calcarine area positively correlated with tremor scores, but negatively correlated with PIGD scores.

CONCLUSION

Our findings mainly suggested that the BG and cerebellum had hyper-connectivity with the cortical motor cortex, and the BG had prominent hyper-connectivity with the visual cortex in early-stage PD-TD patients. These findings may be helpful for facilitating the further understanding of potential mechanisms in the early-stage PD-TD. However, our results are preliminary, and further investigations are needed.