Levodopa modulates small-world architecture of functional brain networks in Parkinson's disease

Investigating Dopamine Replacement-Associated Fluctuations in Cognition and Mood in Cognitively Unimpaired Parkinson's Disease

BACKGROUND

Non-motor fluctuations, characterized by variability in mood and cognition, are prevalent in advanced Parkinson's disease (PD), but less is known about these fluctuations in early PD.

OBJECTIVE

The objective was to characterize fluctuations in cognition and mood in early PD without cognitive impairment.

METHODS

Individuals with PD but without cognitive impairment were evaluated "on" and "off" dopaminergic medications for minimal clinically important differences (MCID) in depression, anxiety, and cognition. Multivariable logistic regression evaluated factors associated with medication-related fluctuations in anxiety, depression, and cognition.

RESULTS

Clinically meaningful fluctuations in anxiety were associated with dysautonomia (OR [odds ratio] 7.5) and female sex (OR 3.9). Fluctuations in Symbol Digit Modalities Test (SDMT), a measure of processing speed and executive function, were associated with dysautonomia (OR 2.82). Such an association was not found with depression or Stroop test.

CONCLUSIONS

Dysautonomia may influence fluctuations in anxiety and some aspects of cognition in cognitively unimpaired PD.

Levodopa therapy affects brain functional network dynamics in Parkinson's disease

Levodopa (L-dopa) therapy is the most effective pharmacological treatment for motor symptoms of Parkinson's disease (PD). However, its effect on brain functional network dynamics is still unclear. Here, we recruited 26 PD patients and 24 healthy controls, and acquired their resting-state functional MRI data before (PD-OFF) and after (PD-ON) receiving 400 mg L-dopa. Using the independent component analysis and the sliding-window approach, we estimated the dynamic functional connectivity (dFC) and examined the effect of L-dopa on the temporal properties of dFC states, the variability of dFC and functional network topological organization. We found that PD-ON showed decreased mean dwell time in sparsely connected State 2 than PD-OFF, the transformation of the dFC state is more frequent and the variability of dFC was decreased within the auditory network and sensorimotor network in PD-ON. Our findings provide new insights to understand the dynamic neural activity induced by L-dopa therapy in PD patients.

Utilising activity patterns of a complex biophysical network model to optimise intra-striatal deep brain stimulation

A large-scale biophysical network model for the isolated striatal body is developed to optimise potential intrastriatal deep brain stimulation applied to, e.g. obsessive-compulsive disorder. The model is based on modified Hodgkin-Huxley equations with small-world connectivity, while the spatial information about the positions of the neurons is taken from a detailed human atlas. The model produces neuronal spatiotemporal activity patterns segregating healthy from pathological conditions. Three biomarkers were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the frequency spectrum of the entire network (rhythmicity) and a combination of the above two. By minimising the deviation of the aforementioned biomarkers from the normal state, we compute the optimal deep brain stimulation parameters, regarding position, amplitude and frequency. Our results suggest that in the DBS optimisation process, there is a clear trade-off between frequency synchronisation and overall network activity, which has also been observed during in vivo studies.

Data-driven and equation-free methods for neurological disorders: analysis and control of the striatum network

The striatum as part of the basal ganglia is central to both motor, and cognitive functions. Here, we propose a large-scale biophysical network for this part of the brain, using modified Hodgkin-Huxley dynamics to model neurons, and a connectivity informed by a detailed human atlas. The model shows different spatio-temporal activity patterns corresponding to lower (presumably normal) and increased cortico-striatal activation (as found in, e.g., obsessive-compulsive disorder), depending on the intensity of the cortical inputs. By applying equation-free methods, we are able to perform a macroscopic network analysis directly from microscale simulations. We identify the mean synaptic activity as the macroscopic variable of the system, which shows similarity with local field potentials. The equation-free approach results in a numerical bifurcation and stability analysis of the macroscopic dynamics of the striatal network. The different macroscopic states can be assigned to normal/healthy and pathological conditions, as known from neurological disorders. Finally, guided by the equation-free bifurcation analysis, we propose a therapeutic close loop control scheme for the striatal network.

Aberrant dynamic functional network connectivity in progressive supranuclear palsy

BACKGROUND

The clinical symptoms of progressive supranuclear palsy (PSP) may be mediated by aberrant dynamic functional network connectivity (dFNC). While earlier research has found altered functional network connections in PSP patients, the majority of those studies have concentrated on static functional connectivity. Nevertheless, in this study, we sought to evaluate the modifications in dynamic characteristics and establish the correlation between these disease-related changes and clinical variables.

METHODS

In our study, we conducted a study on 53 PSP patients and 65 normal controls. Initially, we employed a group independent component analysis (ICA) to derive resting-state networks (RSNs), while employing a sliding window correlation approach to produce dFNC matrices. The K-means algorithm was used to cluster these matrices into distinct dynamic states, and then state analysis was subsequently employed to analyze the dFNC and temporal metrics between the two groups. Finally, we made a correlation analysis.

RESULTS

PSP patients showed increased connectivity strength between medulla oblongata (MO) and visual network (VN) /cerebellum network (CBN) and decreased connections were found between default mode network (DMN) and VN/CBN, subcortical cortex network (SCN) and CBN. In addition, PSP patients spend less fraction time and shorter dwell time in a diffused state, especially the MO and SCN. Finally, the fraction time and mean dwell time in the distributed connectivity state (state 2) is negatively correlated with duration, bulbar and oculomotor symptoms.

DISCUSSION

Our findings were that the altered connectivity was mostly concentrated in the CBN and MO. In addition, PSP patients had different temporal dynamics, which were associated with bulbar and oculomotor symptoms in PSPRS. It suggest that variations in dynamic functional network connectivity properties may represent an essential neurological mechanism in PSP.

The functional brain connectome in isolated rapid eye movement sleep behavior disorder and Parkinson's disease

BACKGROUND

Isolated rapid-eye-movement behavior disorder (iRBD) often precedes the development of alpha-synucleinopathies such as Parkinson's disease (PD). Magnetic resonance imaging (MRI) studies have revealed structural brain alterations in iRBD partially resembling those observed in PD. However, relatively little is known about whole-brain functional brain alterations in iRBD. Here, we characterize the functional brain connectome of iRBD compared with PD patients and healthy controls (HC) using resting-state functional MRI (rs-fMRI).

METHODS

Eighteen iRBD subjects (67.3 ± 6.6 years), 18 subjects with PD (65.4 ± 5.8 years), and 39 age- and sex-matched HC (64.4 ± 9.2 years) underwent rs-fMRI at 3 T. We applied a graph theoretical approach to analyze the brain functional connectome at the global and regional levels. Data were analyzed using both frequentist and Bayesian statistics.

RESULTS

Global connectivity was largely preserved in iRBD and PD individuals. In contrast, both disease groups displayed altered local connectivity mainly in the motor network, temporal cortical regions including the limbic system, and the visual system. There were some group specific alterations, and connectivity changes were pronounced in PD individuals. Overall, however, there was a good agreement of the connectome changes observed in both disease groups.

CONCLUSIONS

This study provides evidence for widespread functional brain connectivity alterations in iRBD, including motor circuitry, despite normal motor function. Connectome alterations showed substantial resemblance with those observed in PD, underlining a close pathophysiological relationship of iRBD and PD.

Neuroimaging and plasma evidence of early white matter loss in Parkinson's disease with poor outcomes

Parkinson's disease is a common and debilitating neurodegenerative disorder, with over half of patients progressing to postural instability, dementia or death within 10 years of diagnosis. However, the onset and rate of progression to poor outcomes is highly variable, underpinned by heterogeneity in underlying pathological processes. Quantitative and sensitive measures predicting poor outcomes will be critical for targeted treatment, but most studies to date have been limited to a single modality or assessed patients with established cognitive impairment. Here, we used multimodal neuroimaging and plasma measures in 98 patients with Parkinson's disease and 28 age-matched controls followed up over 3 years. We examined: grey matter (cortical thickness and subcortical volume), white matter (fibre cross-section, a measure of macrostructure; and fibre density, a measure of microstructure) at whole-brain and tract level; structural and functional connectivity; and plasma levels of neurofilament light chain and phosphorylated tau 181. We evaluated relationships with subsequent poor outcomes, defined as development of mild cognitive impairment, dementia, frailty or death at any time during follow-up, in people with Parkinson's disease. We show that extensive white matter macrostructural changes are already evident at baseline assessment in people with Parkinson's disease who progress to poor outcomes (n = 31): with up to 19% reduction in fibre cross-section in multiple tracts, and a subnetwork of reduced structural connectivity strength, particularly involving connections between right frontoparietal and left frontal, right frontoparietal and left parietal and right temporo-occipital and left parietal modules. In contrast, grey matter volumes and functional connectivity were preserved in people with Parkinson's disease with poor outcomes. Neurofilament light chain, but not phosphorylated tau 181 levels were increased in people with Parkinson's disease with poor outcomes, and correlated with white matter loss. These findings suggest that imaging sensitive to white matter macrostructure and plasma neurofilament light chain may be useful early markers of poor outcomes in Parkinson's disease. As new targeted treatments for neurodegenerative disease are emerging, these measures show important potential to aid patient selection for treatment and improve stratification for clinical trials.

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.

Global Alterations of Whole Brain Structural Connectome in Parkinson's Disease: A Meta-analysis

Recent graph-theoretical studies of Parkinson's disease (PD) have examined alterations in the global properties of the brain structural connectome; however, reported alterations are not consistent. The present study aimed to identify the most robust global metric alterations in PD via a meta-analysis. A comprehensive literature search was conducted for all available diffusion MRI structural connectome studies that compared global graph metrics between PD patients and healthy controls (HC). Hedges' g effect sizes were calculated for each study and then pooled using a random-effects model in Comprehensive Meta-Analysis software, and the effects of potential moderator variables were tested. A total of 22 studies met the inclusion criteria for review. Of these, 16 studies reporting 10 global graph metrics (916 PD patients; 560 HC) were included in the meta-analysis. In the structural connectome of PD patients compared with HC, we found a significant decrease in clustering coefficient (g = -0.357, P = 0.005) and global efficiency (g = -0.359, P < 0.001), and a significant increase in characteristic path length (g = 0.250, P = 0.006). Dopaminergic medication, sex and age of patients were potential moderators of global brain network changes in PD. These findings provide evidence of decreased global segregation and integration of the structural connectome in PD, indicating a shift from a balanced small-world network to 'weaker small-worldization', which may provide useful markers of the pathophysiological mechanisms underlying PD.

Pain in Parkinson disease: mechanistic substrates, main classification systems, and how to make sense out of them

ABSTRACT

Parkinson disease (PD) affects up to 2% of the general population older than 65 years and is a major cause of functional loss. Chronic pain is a common nonmotor symptom that affects up to 80% of patients with (Pw) PD both in prodromal phases and during the subsequent stages of the disease, negatively affecting patient's quality of life and function. Pain in PwPD is rather heterogeneous and may occur because of different mechanisms. Targeting motor symptoms by dopamine replacement or with neuromodulatory approaches may only partially control PD-related pain. Pain in general has been classified in PwPD according to the motor signs, pain dimensions, or pain subtypes. Recently, a new classification framework focusing on chronic pain was introduced to group different types of PD pains according to mechanistic descriptors: nociceptive, neuropathic, or neither nociceptive nor neuropathic. This is also in line with the International Classification of Disease-11 , which acknowledges the possibility of chronic secondary musculoskeletal or nociceptive pain due to disease of the CNS. In this narrative review and opinion article, a group of basic and clinical scientists revise the mechanism of pain in PD and the challenges faced when classifying it as a stepping stone to discuss an integrative view of the current classification approaches and how clinical practice can be influenced by them. Knowledge gaps to be tackled by coming classification and therapeutic efforts are presented, as well as a potential framework to address them in a patient-oriented manner.

Altered brain network centrality in Parkinson's disease patients after deep brain stimulation: a functional MRI study using a voxel-wise degree centrality approach

OBJECTIVE

After deep brain stimulation (DBS), patients with Parkinson's disease (PD) show improved motor symptoms and decreased verbal fluency, an effect that occurs before the initiation of DBS in the subthalamic nucleus. However, the underlying mechanism remains unclear. This study aimed to evaluate the effects of DBS on whole-brain degree centrality (DC) and seed-based functional connectivity (FC) in PD patients.

METHODS

The authors obtained resting-state functional MRI data of 28 PD patients before and after DBS surgery. All patients underwent MRI scans in the off-stimulation state. The DC method was used to evaluate the effects of DBS on whole-brain FC at the voxel level. Seed-based FC analysis was used to examine network function changes after DBS.

RESULTS

After DBS surgery, PD patients showed significantly weaker DC values in the left middle temporal gyrus, left supramarginal gyrus, and left middle frontal gyrus, but significantly stronger DC values in the midbrain, left precuneus, and right precentral gyrus. FC analysis revealed decreased FC values within the default mode network (DMN).

CONCLUSIONS

This study demonstrated that the DC of DMN-related brain regions decreased in PD patients after DBS surgery, whereas the DC of the motor cortex increased. These findings provide new evidence for the neural effects of DBS on voxel-based whole-brain networks in PD patients.

The altered spontaneous neural activity in patients with Parkinson's disease and its predictive value for the motor improvement of deep brain stimulation

BACKGROUND

This study aims to investigate the altered spontaneous neural activity in patients with Parkinson's disease (PD) revealed by amplitudes of low-frequency fluctuations (ALFF) of resting-state fMRI, and the feasibility of using ALFF as neuroimaging predictors for motor improvement after bilateral subthalamic nucleus (STN) deep brain stimulation (DBS).

METHODS

Fourty-four patients and 44 healthy controls were included in this study. First, the ALFF of patients with PD was compared with that of controls; then significant clusters were correlated with motor improvement after DBS (unified Parkinson's disease rating scale (UPDRS-III)) and other clinical variables. Second, regression and classification of the machine learning models were conducted to predict motor improvement after DBS. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the classification model.

RESULTS

Compared with healthy controls, patients with PD showed increased ALFF in the bilateral motor area and decreased ALFF in the bilateral temporal cortex and cerebellum. The Hoehn-Yahr stages correlated with ALFF within the bilateral cerebellum (p = 0.021), and UPDRS-III improvement correlated with ALFF in the left (p < 0.001) and right (p = 0.005) motor areas. The regression model showed a significant correlation between the predicted and observed UPDRS-III changes (R = 0.65, p < 0.001). The ROC analysis revealed an area under the curve (AUC) of 0.94 which differentiated moderate and superior DBS responders.

CONCLUSION

The results revealed altered ALFF patterns in patients with PD and their correlations with clinical variables. Both binary and continuous ALFF can potentially serve as predictive biomarkers for DBS response.

Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity

Type 2 diabetes mellitus (T2DM) is closely linked to cognitive decline and alterations in brain structure and function. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to diagnose neurodegenerative diseases, such as cognitive impairment (CI), Alzheimer's disease (AD), and vascular dementia (VaD). However, whether the functional connectivity (FC) of patients with T2DM and mild cognitive impairment (T2DM-MCI) is conducive to early diagnosis remains unclear. To answer this question, we analyzed the rs-fMRI data of 37 patients with T2DM and mild cognitive impairment (T2DM-MCI), 93 patients with T2DM but no cognitive impairment (T2DM-NCI), and 69 normal controls (NC). We achieved an accuracy of 87.91% in T2DM-MCI versus T2DM-NCI classification and 80% in T2DM-NCI versus NC classification using the XGBoost model. The thalamus, angular, caudate nucleus, and paracentral lobule contributed most to the classification outcome. Our findings provide valuable knowledge to classify and predict T2DM-related CI, can help with early clinical diagnosis of T2DM-MCI, and provide a basis for future studies.

Levodopa responsiveness and white matter alterations in Parkinson's disease: A DTI-based study and brain network analysis: A cross-sectional study

BACKGROUND

Patients with Parkinson's disease (PD) present various responsiveness to levodopa, but the cause of such differences in levodopa responsiveness is unclear. Previous studies related the damage of brain white matter (WM) to levodopa responsiveness in PD patients, but no study investigated the relationship between the structural brain network change in PD patients and their levodopa responsiveness.

METHODS

PD patients were recruited and evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS). Each patient received a diffusion tensor imaging (DTI) scan and an acute levodopa challenge test. The improvement rate of UPDRS-III was calculated. PD patients were grouped into irresponsive group (improvement rate < 30%) and responsive group (improvement rate ≥ 30%). Tract-based spatial statistics (TBSS), deterministic tracing (DT), region of interest (ROI) analysis, and automatic fiber identification (AFQ) analyses were performed. The structural brain network was also constructed and the topological parameters were calculated.

RESULTS

Fifty-four PD patients were included. TBSS identified significant differences in fractional anisotropy (FA) values in the corpus callosum and other regions of the brain. DT and ROI analysis of the corpus callosum found a significant difference in FA between the two groups. Graph theory analysis showed statistical differences in global efficiency, local efficiency, and characteristic path length.

CONCLUSION

PD patients with poor responsiveness to levodopa had WM damage in multiple brain areas, especially the corpus callosum, which might cause disruption of information integration of the structural brain network.

Alterations in Large-Scale Intrinsic Connectivity Networks in the Parkinson's Disease-Associated Cognitive Impairment Continuum: A Systematic Review

Introduction

Cognitive impairment is common in the course of Parkinson's disease (PD) and displays a continuum from subjective cognitive impairment to dementia. Illuminating the pathophysiological processes associated with the continuum may help create follow-up and new treatment approaches. In this context, large-scale intrinsic connectivity networks are widely investigated to elucidate the neural processes underlying PD and are promising as non-invasive biomarkers. This systematic review aims to examine the alterations in large-scale intrinsic connectivity networks in the continuum of PD-associated cognitive impairment.

Method

ScienceDirect, Web of Science, and PubMed databases were searched with the specified keywords. The studies obtained as a result of this review were investigated by the PRISMA criteria, which were taken as a basis for the systematic review and writing of meta-analyses.

Results

A total of 974 studies were obtained from three databases. Twenty studies were included in the systematic review based on predetermined eligibility criteria. Among the large-scale connectivity networks examined in these studies, it was found that sensory-motor networks decreased their connectivity in the continuum of PD-associated cognitive impairment, and there were conflicting results in terms of cognitive networks.

Conclusion

Well-designed longitudinal studies are needed to clarify the alterations in the intrinsic connectivity networks in the PD cognitive impairment continuum. In these studies, it is necessary to define the cognitive disorder groups well, to control the connectivity changes that may occur due to dopaminergic treatment, and to evaluate Parkinson's patients with subjective cognitive impairment and dementia within the continuum.

Motor progression marker for newly diagnosed drug-naïve patients with Parkinson's disease: A resting-state functional MRI study

The effective early prediction of clinical outcomes of Parkinson's disease (PD) is of great significance in the implementation of appropriate interventions. We aimed to propose a method based on the use of baseline resting-state functional characteristics (i.e., fractional amplitude of low-frequency fluctuations, fALFF) to predict motor progression in PD patients. Resting-state functional magnetic resonance imaging was performed on 48 newly-diagnosed drug-naïve PD patients and 27 age- and sex- matched healthy controls (HCs). Two PD subgroups were defined with different annual increase of Unified PD Rating Scale Part III motor scores. Least absolute shrinkage and selection operator regression analysis was performed to explore the baseline region-functional indicators for PD discrimination as well as the predictors for future motor deficits. Two significant models composed of baseline fALFF values from cerebral subregions were proposed. The classification model that distinguished PD patients from HCs (area under the curve [AUC] = 0.897) showed the most significant imaging characteristics in the putamen and precentral gyrus. The other prediction model that evaluated the degree of future deterioration of motor symptoms in PD patients (AUC = 0.916) showed the most significant imaging characteristics in the superior occipital gyrus and caudate nucleus. Furthermore, the increased regional function in bilateral caudate nuclei was correlated with the lower annual increase in motor deficits in all PD patients. The caudate nucleus might be the core region responsible for future motor deficits in newly-diagnosed PD patients, which may aid the development of disease progression preventive strategies in clinical practice.

Functional connectivity of the cortico-subcortical sensorimotor loop is modulated by the severity of nigrostriatal dopaminergic denervation in Parkinson’s Disease

To assess if the severity of nigrostriatal innervation loss affects the functional connectivity (FC) of the sensorimotor cortico-striato-thalamic-cortical loop (CSTCL) in Parkinson’s Disease (PD), Resting-State functional MRI and ¹⁸F-DOPA PET data, simultaneously acquired on a hybrid PET/MRI scanner, were retrospectively analyzed in 39 PD and 16 essential tremor patients. Correlations between posterior Putamen DOPA Uptake (pPDU) and the FC of the main CSTCL hubs were assessed separately in the two groups, analyzing the differences between the two groups by a group-by-pPDU interaction analysis of the resulting clusters’ FC. Unlike in essential tremor, in PD patients pPDU correlated inversely with the FC of the thalamus with the sensorimotor cortices, and of the postcentral gyrus with the dorsal cerebellum, and directly with the FC of pre- and post-central gyri with both the superior and middle temporal gyri and the paracentral lobule, and of the caudate with the superior parietal cortex. The interaction analysis confirmed the significance of the difference between the two groups in these correlations. In PD patients, the post-central cortex FC, in the clusters correlating directly with pPDU, negatively correlated with both UPDRS motor examination score and Hoehn and Yahr stage, independent of the pPDU, suggesting that these FC changes contribute to motor impairment. In PD, nigrostriatal innervation loss correlates with a decrease in the FC within the sensorimotor network and between the sensorimotor network and the superior temporal cortices, possibly contributing to motor impairment, and with a strengthening of the thalamo-cortical FC, that may represent ineffective compensatory phenomena.

Subthalamic and pallidal stimulation in Parkinson's disease induce distinct brain topological reconstruction

The subthalamic nucleus (STN) and globus pallidus internus (GPi) are the two most common and effective target brain areas for deep brain stimulation (DBS) treatment of advanced Parkinson's disease. Although DBS has been shown to restore functional neural circuits of this disorder, the changes in topological organization associated with active DBS of each target remain unknown. To investigate this, we acquired resting-state functional magnetic resonance imaging (fMRI) data from 34 medication-free patients with Parkinson's disease that had DBS electrodes implanted in either the subthalamic nucleus or internal globus pallidus (n = 17 each), in both ON and OFF DBS states. Sixteen age-matched healthy individuals were used as a control group. We evaluated the regional information processing capacity and transmission efficiency of brain networks with and without stimulation, and recorded how stimulation restructured the brain network topology of patients with Parkinson's disease. For both targets, the variation of local efficiency in motor brain regions was significantly correlated (p < 0.05) with improvement rate of the Uniform Parkinson's Disease Rating Scale-III scores, with comparable improvements in motor function for the two targets. However, non-motor brain regions showed changes in topological organization during active stimulation that were target-specific. Namely, targeting the STN decreased the information transmission of association, limbic and paralimbic regions, including the inferior frontal gyrus angle, insula, temporal pole, superior occipital gyri, and posterior cingulate, as evidenced by the simultaneous decrease of clustering coefficient and local efficiency. GPi-DBS had a similar effect on the caudate and lenticular nuclei, but enhanced information transmission in the cingulate gyrus. These effects were not present in the DBS-OFF state for GPi-DBS, but persisted for STN-DBS. Our results demonstrate that DBS to the STN and GPi induce distinct brain network topology reconstruction patterns, providing innovative theoretical evidence for deciphering the mechanism through which DBS affects disparate targets in the human brain.

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 Functional Network Connectivity of Precuneus and Executive Control Networks in Type 2 Diabetes Mellitus Without Cognitive Impairment

In epidemiological studies, type 2 diabetes mellitus (T2DM) has been associated with cognitive impairment and dementia, but studies about functional network connectivity in T2DM without cognitive impairment are limited. This study aimed to explore network connectivity alterations that may help enhance our understanding of damage-associated processes in T2DM. MRI data were analyzed from 82 patients with T2DM and 66 normal controls. Clinical, biochemical, and neuropsychological assessments were conducted in parallel with resting-state functional magnetic resonance imaging, and the cognitive status of the patients was assessed using the Montreal Cognitive Assessment-B (MoCA-B) score. Independent component analysis revealed a positive correlation between the salience network and the visual network and a negative connection between the left executive control network and the default mode network in patients with T2DM. The differences in dynamic brain network connectivity were observed in the precuneus, visual, and executive control networks. Internal network connectivity was primarily affected in the thalamus, inferior parietal lobe, and left precuneus. Hemoglobin A1c level, body mass index, MoCA-B score, and grooved pegboard (R) assessments indicated significant differences between the two groups (p < 0.05). Our findings show that key changes in functional connectivity in diabetes occur in the precuneus and executive control networks that evolve before patients develop cognitive deficits. In addition, the current study provides useful information about the role of the thalamus, inferior parietal lobe, and precuneus, which might be potential biomarkers for predicting the clinical progression, assessing the cognitive function, and further understanding the neuropathology of T2DM.

Linking α-synuclein-induced synaptopathy and neural network dysfunction in early Parkinson's disease

The prodromal phase of Parkinson's disease is characterized by aggregation of the misfolded pathogenic protein α-synuclein in select neural centres, co-occurring with non-motor symptoms including sensory and cognitive loss, and emotional disturbances. It is unclear whether neuronal loss is significant during the prodrome. Underlying these symptoms are synaptic impairments and aberrant neural network activity. However, the relationships between synaptic defects and network-level perturbations are not established. In experimental models, pathological α-synuclein not only impacts neurotransmission at the synaptic level, but also leads to changes in brain network-level oscillatory dynamics-both of which likely contribute to non-motor deficits observed in Parkinson's disease. Here we draw upon research from both human subjects and experimental models to propose a 'synapse to network prodrome cascade' wherein before overt cell death, pathological α-synuclein induces synaptic loss and contributes to aberrant network activity, which then gives rise to prodromal symptomology. As the disease progresses, abnormal patterns of neural activity ultimately lead to neuronal loss and clinical progression of disease. Finally, we outline goals and research needed to unravel the basis of functional impairments in Parkinson's disease and other α-synucleinopathies.

Dynamics of intrinsic whole-brain functional connectivity in abstinent males with methamphetamine use disorder

Background

The global prevalence of methamphetamine use disorder (MUD) and the associated economic burden are increasing, but effective pharmacological treatment is lacking. Therefore, understanding the neurological mechanisms underlying MUD is essential to develop clinical strategies and improve patient care. Individuals with MUD can show static brain network abnormalities during the resting state, but their alterations in dynamic functional network connectivity (dFNC) are unclear.

Methods

In this study, we obtained resting-state functional magnetic resonance imaging from 42 males with MUD and 41 healthy controls. Sliding-window and spatial independent component analyses with a k-means clustering algorithm were used to assess the recurring functional connectivity states. The temporal properties of the dFNC, including fraction and dwelling time of each state and the number of transitions between different states, were compared between the two groups. In addition, the relationships between the temporal properties of the dFNC and clinical characteristics of the MUDs, including their anxiety and depressive symptoms, were further explored.

Results

While the two groups shared many similarities in their dFNC, the occurrence of a highly integrated functional network state and a state featuring balanced integration and segregation in the MUDs significantly correlated with the total drug usage (Spearman's rho = 0.47, P = 0.002) and duration of abstinence (Spearman's rho = 0.38, P = 0.013), respectively.

Conclusions

The observed results in our study demonstrate that methamphetamines can affect dFNC, which may reflect the drug's influence on cognitive abilities. Our study justifies further studies into the effects of MUD on dynamic neural mechanisms.

Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson's Disease: An EEG Study

Dopaminergic medication for Parkinson's disease (PD) modulates neuronal oscillations and functional connectivity (FC) across the basal ganglia-thalamic-cortical circuit. However, the non-oscillatory component of the neuronal activity, potentially indicating a state of excitation/inhibition balance, has not yet been investigated and previous studies have shown inconsistent changes of cortico-cortical connectivity as a response to dopaminergic medication. To further elucidate changes of regional non-oscillatory component of the neuronal power spectra, FC, and to determine which aspects of network organization obtained with graph theory respond to dopaminergic medication, we analyzed a resting-state electroencephalography (EEG) dataset including 15 PD patients during OFF and ON medication conditions. We found that the spectral slope, typically used to quantify the broadband non-oscillatory component of power spectra, steepened particularly in the left central region in the ON compared to OFF condition. In addition, using lagged coherence as a FC measure, we found that the FC in the beta frequency range between centro-parietal and frontal regions was enhanced in the ON compared to the OFF condition. After applying graph theory analysis, we observed that at the lower level of topology the node degree was increased, particularly in the centro-parietal area. Yet, results showed no significant difference in global topological organization between the two conditions: either in global efficiency or clustering coefficient for measuring global and local integration, respectively. Interestingly, we found a close association between local/global spectral slope and functional network global efficiency in the OFF condition, suggesting a crucial role of local non-oscillatory dynamics in forming the functional global integration which characterizes PD. These results provide further evidence and a more complete picture for the engagement of multiple cortical regions at various levels in response to dopaminergic medication in PD.

Network Reconfiguration Among Cerebellar Visual, and Motor Regions Affects Movement Function in Spinocerebellar Ataxia Type 3

Background

Spinocerebellar ataxia type 3 (SCA3) is a rare movement disorder characterized with ataxia. Previous studies on movement disorders show that the whole-brain functional network tends to be more regular, and these reconfigurations correlate with genetic and clinical variables.

Methods

To test whether the brain network in patients with SCA3 follows a similar reconfiguration course to other movement disorders, we recruited 41 patients with SCA3 (mean age = 40.51 ± 12.13 years; 23 male) and 41 age and sex-matched healthy individuals (age = 40.10 ± 11.56 years; 24 male). In both groups, the whole-brain network topology of resting-state functional magnetic resonance imaging (rs-fMRI) was conducted using graph theory, and the relationships among network topologies, cytosine-adenine-guanine (CAG) repeats, clinical symptoms, and functional connectivity were explored in SCA3 patients using partial correlation analysis, controlling for age and sex.

Results

The brain networks tended to be more regular with a higher clustering coefficient, local efficiency, and modularity in patients with SCA3. Hubs in SCA3 patients were reorganized as the number of hubs increased in motor-related areas and decreased in cognitive areas. At the global level, small-worldness and normalized clustering coefficients were significantly positively correlated with clinical motor symptoms. At the nodal level, the clustering coefficient and local efficiency increased significantly in the visual (bilateral cuneus) and sensorimotor (right cerebellar lobules IV, V, VI) networks and decreased in the cognitive areas (right middle frontal gyrus). The clustering coefficient and local efficiency in the bilateral cuneus gyrus were negatively correlated with clinical motor symptoms. The functional connectivity between right caudate nucleus and bilateral calcarine gyrus were negatively correlated with disease duration, while connectivity between right posterior cingulum gyrus and left cerebellar lobule III, left inferior occipital gyrus and right cerebellar lobule IX was positively correlated.

Conclusion

Our results demonstrate that a more regular brain network occurred in SCA3 patients, with motor and visual-related regions, such as, cerebellar lobules and cuneus gyrus, both forayed neighbor nodes as “resource predators” to compensate for normal function, with motor and visual function having the higher priority comparing with other high-order functions. This study provides new information about the neurological mechanisms underlying SCA3 network topology impairments in the resting state, which give a potential guideline for future clinical treatments.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [ChiCTR1800019901].

Locus coeruleus degeneration is associated with disorganized functional topology in Parkinson's disease

Degeneration of the locus coeruleus (LC) is recognized as a critical hallmark of Parkinson's disease (PD). Recent studies have reported that noradrenaline produced from the LC has critical effects on brain functional organization. However, it is unknown if LC degeneration in PD contributes to cognitive/motor manifestations through modulating brain functional organization. This study enrolled 94 PD patients and 68 healthy controls, and LC integrity was measured using the contrast-to-noise ratio of the LC (CNR_LC) calculated from T1-weighted magnetic resonance imaging. We used graph-theory-based network analysis to characterize brain functional organization. The relationships among LC degeneration, network disruption, and cognitive/motor manifestations in PD were assessed. Whether network disruption was a mediator between LC degeneration and cognitive/motor impairments was assessed further. In addition, an independent PD subgroup (n = 35) having functional magnetic resonance scanning before and after levodopa administration was enrolled to evaluate whether LC degeneration-related network deficiencies were independent of dopamine deficiency. We demonstrated that PD patients have significant LC degeneration compared to healthy controls. CNR_LC was positively correlated with Montreal Cognitive Assessment score and the nodal efficiency (NE) of several cognitive-related regions. Lower NE of the superior temporal gyrus was a mediator between LC degeneration and cognitive impairment in PD. However, levodopa treatment could not normalize the reduced NE of the superior temporal gyrus (mediator). In conclusion, we provided evidence for the relationship between LC degeneration and extensive network disruption in PD, and highlight the role of network disorganization in LC degeneration-related cognitive impairment.

Normalization effect of levodopa on hierarchical brain function in Parkinson’s disease

Hierarchical brain organization, in which the rich club and diverse club situate in core position, is critical for global information integration in the human brain network. Parkinson’s disease (PD), a common movement disorder, has been conceptualized as a network disorder. Levodopa is an effective treatment for PD. Whether there is a functional divergence in the hierarchical brain system under PD pathology, and how this divergence is regulated by immediate levodopa therapy, remains unknown. We constructed a functional network in 61 PD patients and 89 normal controls and applied graph theoretical analyses to examine the neural mechanism of levodopa short response from the perspective of brain hierarchical configuration. The results revealed the following: (a) PD patients exhibited disrupted function within rich-club organization, while the diverse club preserved function, indicating a differentiated brain topological organization in PD. (b) Along the rich-club derivate hierarchical system, PD patients showed impaired network properties within rich-club and feeder subnetworks, and decreased nodal degree centrality in rich-club and feeder nodes, along with increased nodal degree in peripheral nodes, suggesting distinct functional patterns in different types of nodes. And (c) levodopa could normalize the abnormal network architecture of the rich-club system. This study provides evidence for levodopa effects on the hierarchical brain system with divergent functions.

Many studies of brain networks have revealed densely connected regions forming the rich club and diverse club, which occupy the central position of the hierarchical brain system. Here, we explore the hierarchical topology in Parkinson’s disease (PD) and investigate the neural effect of levodopa on it. We show that within the core position of the hierarchical system, the function of the diverse club is preserved while the function of the rich club is impaired. Along the rich-club hierarchical system, the function of biologically costly rich-club and feeder subnetworks is disrupted, together with an increased function of peripheral nodes, which could be normalized by levodopa. Our study provides evidence of a disparity pattern between different levels of brain hierarchical systems under PD pathology.

The amplitude of low-frequency fluctuation predicts levodopa treatment response in patients with Parkinson's disease

INTRODUCTION

Levodopa has become the main therapy for motor symptoms of Parkinson's disease (PD). This study aimed to test whether the amplitude of low-frequency fluctuation (ALFF) computed by fMRI could predict individual patient's response to levodopa treatment.

METHODS

We included 40 patients. Treatment efficacy was defined based on motor symptoms improvement from the state of medication off to medication on, as assessed by the Unified Parkinson's Disease Rating Scale score III. Two machine learning models were constructed to test the prediction ability of ALFF. First, the ensemble method was implemented to predict individual treatment responses. Second, the categorical boosting (CatBoost) classification was used to predict individual levodopa responses in patients classified as moderate and superior responders, according to the 50% threshold of improvement. The age, disease duration and treatment dose were controlled as covariates.

RESULTS

No significant difference in clinical data were observed between moderate and superior responders. Using the ensemble method, the regression model showed a significant correlation between the predicted and the observed motor symptoms improvement (r = 0.61, p < 0.01, mean absolute error = 0.11 ± 0.02), measured as a continuous variable. The use of the Catboost algorithm revealed that ALFF was able to differentiate between moderate and superior responders (area under the curve = 0.90). The mainly contributed regions for both models included the bilateral primary motor cortex, the occipital cortex, the cerebellum, and the basal ganglia.

CONCLUSION

Both continuous and binary ALFF values have the potential to serve as promising predictive markers of dopaminergic therapy response in patients with PD.

Effect of deep brain stimulation on brain network and white matter integrity in Parkinson's disease

Aims

The effects of subthalamic nucleus (STN)‐deep brain stimulation (DBS) on brain topological metrics, functional connectivity (FC), and white matter integrity were studied in levodopa‐treated Parkinson’s disease (PD) patients before and after DBS.

Methods

Clinical assessment, resting‐state functional MRI (rs‐fMRI), and diffusion tensor imaging (DTI) were performed pre‐ and post‐DBS in 15 PD patients, using a within‐subject design. The rs‐fMRI identified brain network topological metric and FC changes using graph‐theory‐ and seed‐based methods. White matter integrity was determined by DTI and tract‐based spatial statistics.

Results

Unified Parkinson's Disease Rating Scale III (UPDRS‐ III) scores were significantly improved by 35.3% (p < 0.01) after DBS in PD patients, compared with pre‐DBS patients without medication. Post‐DBS PD patients showed a significant decrease in the graph‐theory‐based degree and cost in the middle temporal gyrus and temporo‐occipital part‐Right. Changes in FC were seen in four brain regions, and a decrease in white matter integrity was seen in the left anterior corona radiata. The topological metrics changes were correlated with Beck Depression Inventory II (BDI‐II) and the FC changes with UPDRS‐III scores.

Conclusion

STN‐DBS modulated graph‐theoretical metrics, FC, and white matter integrity. Brain connectivity changes observed with multi‐modal imaging were also associated with postoperative clinical improvement. These findings suggest that the effects of STN‐DBS are caused by brain network alterations.

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.

A Longitudinal Randomized Controlled Trial Protocol to Evaluate the Effects of Wuqinxi on Dynamic Functional Connectivity in Parkinson's Disease Patients

Background: Parkinson’s disease (PD) is a neurodegenerative movement disease that includes non-motor symptoms such as cognitive impairment. Long-term mind-body exercise has been shown to improve cognitive ability in PD patients, but the methods of assessment and intervention were inconsistent across studies. Wuqinxi is a mind-body exercise that is easy to learn, has few physical and cognitive demands, and is recommended for PD patients. Dynamic functional connectivity (DFC) has been associated with cognitive alterations in PD patients, but no studies have yet explored the effects of Wuqinxi on this association. The current protocol is designed to measure the effects of long-term Wuqinxi intervention on cognition in PD patients, and explore the underlying neural mechanisms through DFC.

Methods: A long-term single-blind, randomized trial will be conducted. PD patients and age- and gender-matched HC will be recruited; PD patients will be randomly assigned to either Wuqinxi or balance groups, and HC will all receive health education. The Wuqinxi group will receive a 90-min session of Wuqinxi intervention three times a week for 24 weeks, while the balance group will receive balance exercise instruction on the same schedule. Primary outcomes will include assessment of cognitive domains and dynamic temporal characteristics of functional connectivity. Secondary outcomes will include severity of motor symptoms, mobility, balance, and emotional state. Assessments will be conducted at baseline, at the end of 24 weeks of intervention, and 12 weeks after interventions have ended.

Discussion: This study will provide evidence to the effects of Wuqinxi exercise on cognitive improvements in PD patients from the perspective of DFC, and will contribute to the understanding of neural mechanisms underlying cognitive enhancement through Wuqinxi practice.

Clinical Trial Registration:www.chictr.org.cn, identifier ChiCTR2000038517.

Effects of Levodopa Therapy on Cerebral Arteries and Perfusion in Parkinson's Disease Patients

BACKGROUND

Levodopa is the most-commonly used therapy for Parkinson's Disease (PD). Imaging findings show increased cerebral blood flow (CBF) response to levodopa, but the artery morphological change is less studied.

PURPOSE

To investigate the effect of levodopa on cerebral arteries and CBF.

STUDY TYPE

Prospective.

POPULATION

57 PD patients (56 ± 10 years, 26 males) and 17 age-matched healthy controls (AMC, 57 ± 9 years, 9 males) were scanned at baseline (OFF). Patients were rescanned 50 minutes after taking levodopa (ON).

FIELD STRENGTH AND SEQUENCE

3 T; Simultaneous noncontrast angiography intraplaque imaging (SNAP) based on turbo field echo; Pseudo-continuous arterial spin labeling (PCASL) based on echo-planner imaging.

ASSESSMENT

The Unified Parkinson's Disease Rating Scale (UPDRS-III) was used to assess the disease severity. Length and radius of arteries were measured from SNAP images. CBF was calculated from PCASL images globally and regionally.

STATISTICAL TESTS

Mann Whitney U tests were conducted in comparing PD vs. AMC. Wilcoxon matched-pairs signed rank tests were used in comparing OFF vs. ON, and the more-affected vs. the less-affected hemisphere in PD. Linear regressions were performed to test the correlations of neuroimaging findings with behavioral changes. Significance threshold was P < 0.05 with Bonferroni correction.

RESULTS

PD patients were identified with significantly lower CBF (PD OFF Mean = 40.15 ± 5.99, AMC Mean = 43.48 ± 6.21 mL/100 g/min) and shortened total artery length (PD OFF Mean = 5851.07 ± 1393.45, AMC Mean = 7479.16 ± 1335.93 mm). Levodopa elevated CBF of PD brains (PD ON Mean = 41.48 ± 6.32 mL/100 g/min) and expanded radius of proximal arteries. Artery radius change significantly correlated with CBF change in corresponding territories (r = 0.559 for Internal Carotid Arteries, r = 0.448 for Basilar Artery, and r = 0.464 for Middle Cerebral Artery M1). Global CBF significantly related to UPDRS-III (r = -0.391) post-levodopa.

DATA CONCLUSION

Levodopa can increase CBF by dilating proximal arteries.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 4.

Abnormal Topological Network in Parkinson's Disease With Impulse Control Disorders: A Resting-State Functional Magnetic Resonance Imaging Study

In recent years, neuroimaging evidence shows that the brains of Parkinson disease (PD) with impulse control disorders (ICDs) patients have functional disconnection changes. However, so far, it is still unclear whether the topological organization is damaged in PD patients with ICD. In this study, we aimed to explore the functional brain network in 18 patients with PD with ICDs (PD-ICD) and 18 patients with PD without ICDs (PD-nICD) by using functional magnetic resonance imaging and graph theory approach. We found that the PD-ICD patients had increased clustering coefficient and characteristic path length, while decreased small-world index compared with PD-nICD patients. Furthermore, we explored the hypothesis whether the abnormality of the small-world network parameters of PD-ICD patients is accompanied by the change of nodal centrality. As we hypothesized, the nodal centralities of the default mode network, control network, and dorsal attention network were found to be significantly damaged in the PD-ICD group compared with the PD-nICD group. Our study provides more evidence for PD-ICD patients' brain network abnormalities from the perspective of information exchange, which may be the underlying pathophysiological basis of brain abnormalities in PD-ICD patients.

Global efficiency of the motor network is decreased in Parkinson's disease in comparison with essential tremor and healthy controls

BACKGROUND

Graph theory (GT) is a mathematical field that analyses complex networks that can be applied to neuroimaging to quantify brain's functional systems in Parkinson's disease (PD) and essential tremor (ET).

OBJECTIVES

To evaluate the functional connectivity (FC) measured by the global efficiency (GE) of the motor network in PD and compare it to ET and healthy controls (HC), and correlate it to clinical parameters.

METHODS

103 subjects (54PD, 18ET, 31HC) were submitted to structural and functional MRI. A network was designed with regions of interest (ROIs) involved in motor function, and GT was applied to determine its GE. Clinical parameters were analyzed as covariates to estimate the impact of disease severity and medication on GE.

RESULTS

GE of the motor circuit was reduced in PD in comparison with HC (p .042). Areas that most contributed to it were left supplementary motor area (SMA) and bilateral postcentral gyrus. Tremor scores correlated positively with GE of the motor network in PD subgroups. For ET, there was an increase in the connectivity of the anterior cerebellar network to the other ROIs of the motor circuit in comparison with PD.

CONCLUSIONS

FC measured by the GE of the motor network is diminished in PD in comparison with HC, especially due to decreased connectivity of left SMA and bilateral postcentral gyrus. This finding supports the theory that there is a global impairment of the motor network in PD, and it does not affect just the basal ganglia, but also areas associated with movement modulation. The ET group presented an increased connectivity of the anterior cerebellar network to the other ROIs of the motor circuit when compared to PD, which reinforces what it is known about its role in this pathology.

The Anterior Attentional-Intentional System in Patients with Parkinson's Disease-A Pilot and Feasibility Study

(1) Background: This study compared anterior attentional–intentional system performance between three groups: Parkinson’s disease (PD) patients with normal cognition (PD-NC), with mild cognitive impairment (PD-MCI), and a comparison group (CG). It also evaluated the feasibility of the recruitment and study procedures; (2) Methods: From 45 participants recruited, 39 were allocated (mean age 65.31; 43.59% men) to PD-NC, PD-MCI and CG (13 per group). To assess attention, we used three tasks from the ROtman–Baycrest Battery for Investigating Attention: Simple Reaction time (RT), Choice RT, and Prepare RT. We conducted a mixed-model analysis of variance with a 3 (groups) × 4 (tasks) design to compare reaction times; (3) Results: PD-MCI had slower reaction times than PD-NC (p = 0.028) and the CG (p = 0.052); there was no difference between PD-NC and CG. PD-MCI might perform worse on monitoring tasks than PD-NC, Z = −1.68, p = 0.092. Nearly half the volunteers from the CG and 87% of all eligible patients were enrolled in the study and completed all neuropsychological procedures; (4) Conclusions: General cognitive decline appears related to partial deficits in energization and tends to impair attentional monitoring. Furthermore, PD-NC exhibited similar reaction times to the CG. Results from the feasibility study contributed to the definitive study.

Disrupted functional brain network topology in Parkinson's disease patients with freezing of gait

BACKGROUND

Freezing of gait (FOG) is a common and debilitating gait disturbance in patients with Parkinson's disease (PD), but the potential mechanisms are still unclear. This study aimed to explore alterations in the topological organization of whole-brain functional networks in PD patients with FOG.

METHODS

We recruited 75 patients with PD, 37 patients with FOG and 38 patients without FOG, to undergo resting-state functional magnetic resonance imaging (fMRI). The whole-brain functional networks were constructed, and the topological properties at three (global, nodal, and connectional) levels were analyzed using graph theory approaches.

RESULTS

Compared with patients without FOG, patients with FOG exhibited altered global topological properties (a significant decrease in the normalized clustering coefficient and small-worldness), implying a shift toward randomization in their functional brain networks. At the node and connectional levels, patients with FOG showed increased nodal centralities and functional connectivity in the sensorimotor network, frontoparietal network, visual network, subcortical and limbic regions, and decreased nodal centralities in the frontoparietal network and the cerebellum. Furthermore, the altered nodal centralities in the right hippocampus (HIP) were positively correlated with FOG severity.

CONCLUSIONS

This study suggests that FOG in PD is associated with disrupted topological organization of whole-brain functional networks, involving dysfunction of the multiple networks.

Dynamic functional connectivity changes in Parkinson's disease patients with REM sleep behavior disorder

BACKGROUND

Rapid eye movement (REM) sleep behavior disorder (RBD) is one of the common nonmotor symptoms of Parkinson's disease (PD), characterized by frequently occurring REM sleep without muscle atonia. Our aim was to explore dynamic network connection changes in PD patients with RBD.

METHOD

On the basis of RBD screening questionnaire (RBDSQ), 126 PD patients were classified into those with probable RBD symptoms (PD-pRBD) and without probable RBD (PD-npRBD). We applied independent component analysis, sliding window approach and k-means clustering methods to clarify dynamic functional connectivity alterations.

RESULTS

In contrast to PD-npRBD, PD-pRBD patients were liable to engage in a brain pattern mainly marked by weaker positive couplings between visual network (VIS) and default mode network (DMN), DMN and basal ganglia network (BG), and within DMN (State IV). In addition, we discovered that both PD patients with or without pRBD had shorter dwell time and fewer occurrences in State III, characterized by positive correlations between VIS and DMN, BG and DMN, and positive within-network coupling of sensorimotor network (SMN), relative to healthy controls.

CONCLUSIONS

Our study suggested that the weaker positive couplings between VIS and DMN, DMN and BG, and within DMN in State IV could be involved in the pathogenesis of PD patients with probable RBD on an overall level.

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.

Functional Connectome in Parkinson's Disease and Parkinsonism

PURPOSE OF REVIEW

There has been an exponential growth in functional connectomics research in neurodegenerative disorders. This review summarizes the recent findings and limitations of the field in Parkinson's disease (PD) and atypical parkinsonian syndromes.

RECENT FINDINGS

Increasingly more sophisticated methods ranging from seed-based to network and whole-brain dynamic functional connectivity have been used. Results regarding the disruption in the functional connectome vary considerably based on disease severity and phenotypes, and treatment status in PD. Non-motor symptoms of PD also link to the dysfunction in heterogeneous networks. Studies in atypical parkinsonian syndromes are relatively scarce. An important clinical goal of functional connectomics in neurodegenerative disorders is to establish the presence of pathology, track disease progression, predict outcomes, and monitor treatment response. The obstacles of reliability and reproducibility in the field need to be addressed to improve the potential of the functional connectome as a biomarker for these purposes in PD and atypical parkinsonian syndromes.

Functional Connectomics and Disease Progression in Drug-Naïve Parkinson's Disease Patients

BACKGROUND

Functional brain connectivity alterations may be detectable even before the occurrence of brain atrophy, indicating their potential as early markers of pathological processes.

OBJECTIVE

We aimed to determine the whole-brain network topologic organization of the functional connectome in a large cohort of drug-naïve Parkinson's disease (PD) patients using resting-state functional magnetic resonance imaging and to explore whether baseline connectivity changes may predict clinical progression.

METHODS

One hundred and forty-seven drug-naïve, cognitively unimpaired PD patients were enrolled in the study at baseline and compared to 38 age- and gender-matched controls. Non-hierarchical cluster analysis using motor and non-motor data was applied to stratify PD patients into two subtypes: 77 early/mild and 70 early/severe. Graph theory analysis and connectomics were used to assess global and local topological network properties and regional functional connectivity at baseline. Stepwise multivariate regression analysis investigated whether baseline functional imaging data were predictors of clinical progression over 2 years.

RESULTS

At baseline, widespread functional connectivity abnormalities were detected in the basal ganglia, sensorimotor, frontal, and occipital networks in PD patients compared to controls. Decreased regional functional connectivity involving mostly striato-frontal, temporal, occipital, and limbic connections differentiated early/mild from early/severe PD patients. Connectivity changes were found to be independent predictors of cognitive progression at 2-year follow-up.

CONCLUSIONS

Our findings revealed that functional reorganization of the brain connectome occurs early in PD and underlies crucial involvement of striatal projections. Connectomic measures may be helpful to identify a specific PD patient subtype, characterized by severe motor and non-motor clinical burden as well as widespread functional connectivity abnormalities. © 2021 International Parkinson and Movement Disorder Society.

A new era for executive function research: On the transition from centralized to distributed executive functioning

"Executive functions" (EFs) is an umbrella term for higher cognitive control functions such as working memory, inhibition, and cognitive flexibility. One of the most challenging problems in this field of research has been to explain how the wide range of cognitive processes subsumed as EFs are controlled without an all-powerful but ill-defined central executive in the brain. Efforts to localize control mechanisms in circumscribed brain regions have not led to a breakthrough in understanding how the brain controls and regulates itself. We propose to re-conceptualize EFs as emergent consequences of highly distributed brain processes that communicate with a pool of highly connected hub regions, thus precluding the need for a central executive. We further discuss how graph-theory driven analysis of brain networks offers a unique lens on this problem by providing a reference frame to study brain connectivity in EFs in a holistic way and helps to refine our understanding of the mechanisms underlying EFs by providing new, testable hypotheses and resolves empirical and theoretical inconsistencies in the EF literature.

Topological Abnormalities of Functional Brain Network in Early-Stage Parkinson's Disease Patients With Mild Cognitive Impairment

Recent studies have demonstrated structural and functional alterations in Parkinson's disease (PD) with mild cognitive impairment (MCI). However, the topological patterns of functional brain networks in newly diagnosed PD patients with MCI are unclear so far. In this study, we used functional magnetic resonance imaging (fMRI) and graph theory approaches to explore the functional brain network in 45 PD patients with MCI (PD-MCI), 22 PD patients without MCI (PD-nMCI), and 18 healthy controls (HC). We found that the PD-MCI, PD-nMCI, and HC groups exhibited a small-world architecture in the functional brain network. However, early-stage PD-MCI patients had decreased clustering coefficient, increased characteristic path length, and changed nodal centrality in the default mode network (DMN), control network (CN), somatomotor network (SMN), and visual network (VN), which might contribute to factors for MCI symptoms in PD patients. Our results demonstrated that PD-MCI patients were associated with disrupted topological organization in the functional network, thus providing a topological network insight into the role of information exchange in the underlying development of MCI symptoms in PD patients.

Synergic control of action in levodopa-naïve Parkinson's disease patients: II. Multi-muscle synergies stabilizing vertical posture

Postural instability is a major disabling feature in Parkinson's disease (PD). We quantified the organization of leg and trunk muscles into synergies stabilizing the center of pressure (COP) coordinate within the uncontrolled manifold hypothesis in levodopa-naïve patients with PD and age-matched control subjects. The main hypothesis was that changes in the synergic control of posture are present early in the PD process even before levodopa exposure. Eleven levodopa-naïve patients with PD and 11 healthy controls performed whole-body cyclical voluntary sway tasks and a self-initiated load-release task during standing on a force plate. Surface electromyographic activity in 13 muscles on the right side of the body was analyzed to identify muscle groups with parallel scaling of activation levels (M-modes). Data were collected both before ("off-drug") and approximately 60 min after the first dose of 25/100 carbidopa/levodopa ("on-drug"). COP-stabilizing synergies were quantified for the load-release task. Levodopa-naïve patients with PD showed no COP-stabilizing synergy "off-drug", whereas controls showed posture-stabilizing multi-M-mode synergy. "On-drug", patients with PD demonstrated a significant increase in the synergy index. There were no significant drug effects on the M-mode composition, anticipatory postural adjustments, indices of motor equivalence, or indices of COP variability. The results suggest that levodopa-naïve patients with PD already show impaired posture-stabilizing multi-muscle synergies that may be used as promising behavioral biomarkers for emerging postural disorders in PD. Moreover, levodopa modified synergy metrics differently in these levodopa-naïve patients compared to a previous study of patients on chronic antiparkinsonian medications (Falaki et al. in J Electromyogr Kinesiol 33:20-26, 2017a), suggesting different neurocircuitry involvement.

Dysfunction in superior frontal gyrus associated with diphasic dyskinesia in Parkinson's disease

Alterations in brain function in Parkinson's disease (PD) patients with diphasic dyskinesia have not been investigated. We aimed to explore the alterations in regional brain function. Each of 53 levodopa (LD)-treated PD patients had two resting-state functional magnetic resonance imaging (rs-fMRI) scans in the same morning, before and after taking LD. The regional homogeneity (ReHo) approach was used to reveal local synchronization changes. Two-way factorial repeated measures analysis of covariance, with group as a between-subject factor and LD effect as a within-subject factor, was performed to explore the two main effects and interaction. Interactive analysis was used to show outcomes that combined disease status and LD effect. Spearman's correlations were used to detect associations between interactive brain regions and severity of dyskinetic symptoms, assessed by the Unified Dyskinesia Rating Scale (UDyRS) scores, along with moderation analyses. There was no significant difference in the main group effect analysis. Significantly different clusters obtained from main LD effect analysis were in left caudate nucleus and putamen. ReHo values decreased in the caudate nucleus and increased in the putamen during the ON state after taking LD. Interaction between group and LD effect was found in left medial superior frontal gyrus (mSFG), where there were the lowest ReHo values, and was negatively correlated with UDyRS scores in the diphasic dyskinetic group during the ON state. The relationship was independent of LD dose. Abnormal local synchronization in the mSFG is closely associated with the development of diphasic dyskinesia in PD patients.

Alterations in intrinsic functional networks in Parkinson's disease patients with depression: A resting-state functional magnetic resonance imaging study

Aims

The aim of this research was to investigate the alterations in functional brain networks and to assess the relationship between depressive impairment and topological network changes in Parkinson's disease (PD) patients with depression (DPD).

Methods

Twenty‐two DPD patients, 23 PD patients without depression (NDPD), and 25 matched healthy controls (HCs) were enrolled. All participants were examined by resting‐state functional magnetic resonance imaging scans. Graph theoretical analysis and network‐based statistic methods were used to analyze brain network topological properties and abnormal subnetworks, respectively.

Results

The DPD group showed significantly decreased local efficiency compared with the HC group (P = .008, FDR corrected). In nodal metrics analyses, the degree of the right inferior occipital gyrus (P = .0001, FDR corrected) was positively correlated with the Hamilton Depression Rating Scale scores in the DPD group. Meanwhile, the temporal visual cortex, including the bilateral middle temporal gyri and right inferior temporal gyrus in the HC and NDPD groups and the left posterior cingulate gyrus in the NDPD group, was defined as hub region, but not in the DPD group. Compared with the HC group, the DPD group had extensive weakening of connections between the temporal‐occipital visual cortex and the prefrontal‐limbic network.

Conclusions

These results suggest that PD depression is associated with disruptions in the topological organization of functional brain networks, mainly involved the temporal‐occipital visual cortex and the posterior cingulate gyrus and may advance our current understanding of the pathophysiological mechanisms underlying DPD.

Neuroanatomical and Microglial Alterations in the Striatum of Levodopa-Treated, Dyskinetic Hemi-Parkinsonian Rats

Dyskinesia associated with chronic levodopa treatment in Parkinson’s disease is associated with maladaptive striatal plasticity. The objective of this study was to examine whether macroscale structural changes, as captured by magnetic resonance imaging (MRI) accompany this plasticity and to identify plausible cellular contributors in a rodent model of levodopa-induced dyskinesia. Adult male Sprague-Dawley rats were rendered hemi-parkinsonian by stereotaxic injection of 6-hydroxydopamine into the left medial forebrain bundle prior to chronic treatment with saline (control) or levodopa to induce abnormal involuntary movements (AIMs), reflective of dyskinesia. Perfusion-fixed brains underwent ex vivo structural MRI before sectioning and staining for cellular markers. Chronic treatment with levodopa induced significant AIMs (p < 0.0001 versus saline). The absolute volume of the ipsilateral, lesioned striatum was increased in levodopa-treated rats resulting in a significant difference in percentage volume change when compared to saline-treated rats (p < 0.01). Moreover, a significant positive correlation was found between this volume change and AIMs scores for individual levodopa-treated rats (r = 0.96; p < 0.01). The density of Iba1+ cells was increased within the lesioned versus intact striatum (p < 0.01) with no difference between treatment groups. Conversely, Iba1+ microglia soma size was significantly increased (p < 0.01) in the lesioned striatum of levodopa-treated but not saline-treated rats. Soma size was not, however, significantly correlated with either AIMs or MRI volume change. Although GFAP+ astrocytes were elevated in the lesioned versus intact striatum (p < 0.001), there was no difference between treatment groups. No statistically significant effects of either lesion or treatment on RECA1, a marker for blood vessels, were observed. Collectively, these data suggest chronic levodopa treatment in 6-hydroxydopamine lesioned rats is associated with increased striatal volume that correlates with the development of AIMs. The accompanying increase in number and size of microglia, however, cannot alone explain this volume expansion. Further multi-modal studies are warranted to establish the brain-wide effects of chronic levodopa treatment.

Structural Network Analysis Using Diffusion MRI Tractography in Parkinson's Disease and Correlations With Motor Impairment

Functional impairment of spatially distributed brain regions in Parkinson's disease (PD) suggests changes in integrative and segregative network characteristics, for which novel analysis methods are available. To assess underlying structural network differences between PD patients and controls, we employed MRI T1 gray matter segmentation and diffusion MRI tractography to construct connectivity matrices to compare patients and controls with data originating from two different centers. In the Dutch dataset (Data-NL), 14 PD patients, and 15 healthy controls were analyzed, while 19 patients and 18 controls were included in the Canadian dataset (Data-CA). All subjects underwent T1 and diffusion-weighted MRI. Patients were assessed with Part 3 of the Unified Parkinson's Disease Rating Scale (UPDRS). T1 images were segmented using FreeSurfer, while tractography was performed using ExploreDTI. The regions of interest from the FreeSurfer segmentation were combined with the white matter streamline sets resulting from the tractography, to construct connectivity matrices. From these matrices, both global and local efficiencies were calculated, which were compared between the PD and control groups and related to the UPDRS motor scores. The connectivity matrices showed consistent patterns among the four groups, without significant differences between PD patients and control subjects, either in Data-NL or in Data-CA. In Data-NL, however, global and local efficiencies correlated negatively with UPDRS scores at both the whole-brain and the nodal levels [false discovery rate (FDR) 0.05]. At the nodal level, particularly, the posterior parietal cortex showed a negative correlation between UPDRS and local efficiency, while global efficiency correlated negatively with the UPDRS in the sensorimotor cortex. The spatial patterns of negative correlations between UPDRS and parameters for network efficiency seen in Data-NL suggest subtle structural differences in PD that were below sensitivity thresholds in Data-CA. These correlations are in line with previously described functional differences. The methodological approaches to detect such differences are discussed.

Abnormal Spontaneous Neural Activity in Parkinson's Disease With "pure" Apathy

Background

Apathy is one of the most common non-motor symptoms of Parkinson’s disease (PD). However, its pathophysiology remains unclear.

Methods

We analyzed resting-state functional magnetic resonance imaging (MRI) data acquired at a 3.0T MRI scanner using the amplitude of low-frequency fluctuation (ALFF) metric in 20 de novo, drug-naïve, non-demented PD patients with apathy (PD-A), 26 PD patients without apathy (PD-NA) without comorbidity of depressive or anxious symptoms, and 23 matched healthy control (HC) subjects.

Results

We found that the ALFF decreased significantly in the bilateral nucleus accumbens, dorsal anterior cingulate cortex (ACC), and left dorsolateral prefrontal cortex in patients with PD-A compared to patients with PD-NA and HC subjects. Furthermore, apathy severity was negatively correlated with the ALFF in the bilateral nucleus accumbens and dorsal ACC in the pooled patients with PD.

Conclusion

The present study characterized the functional pattern of changes in spontaneous neural activity in patients with PD-A. With the aim to better elucidate the pathophysiological mechanisms responsible for these changes, this study controlled for the potentially confounding effects of dopaminergic medication, depression, anxiety, and global cognitive impairment. The findings of the current study add to the literature by highlighting potential abnormalities in mesocorticolimbic pathways involved in the development of apathy in PD.

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.

Altered white matter microarchitecture in Parkinson's disease: a voxel-based meta-analysis of diffusion tensor imaging studies

This study aimed to define the most consistent white matter microarchitecture pattern in Parkinson's disease (PD) reflected by fractional anisotropy (FA), addressing clinical profiles and methodology-related heterogeneity. Web-based publication databases were searched to conduct a meta-analysis of whole-brain diffusion tensor imaging studies comparing PD with healthy controls (HC) using the anisotropic effect size-signed differential mapping. A total of 808 patients with PD and 760 HC coming from 27 databases were finally included. Subgroup analyses were conducted considering heterogeneity with respect to medication status, disease stage, analysis methods, and the number of diffusion directions in acquisition. Compared with HC, patients with PD had decreased FA in the left middle cerebellar peduncle, corpus callosum (CC), left inferior fronto-occipital fasciculus, and right inferior longitudinal fasciculus. Most of the main results remained unchanged in subgroup meta-analyses of medicated patients, early stage patients, voxel-based analysis, and acquisition with 30 diffusion directions. The subgroup meta-analysis of medication-free patients showed FA decrease in the right olfactory cortex. The cerebellum and CC, associated with typical motor impairment, showed the most consistent FA decreases in PD. Medication status, analysis approaches, and the number of diffusion directions have an important impact on the findings, needing careful evaluation in future meta-analyses.

Dynamic functional connectivity changes associated with dementia in Parkinson's disease

Dynamic functional connectivity captures temporal variations of functional connectivity during MRI acquisition and it may be a suitable method to detect cognitive changes in Parkinson's disease. In this study, we evaluated 118 patients with Parkinson's disease matched for age, sex and education with 35 healthy control subjects. Patients with Parkinson's disease were classified with normal cognition (n = 52), mild cognitive impairment (n = 46), and dementia (n = 20) based on an extensive neuropsychological evaluation. Resting state functional MRI and a sliding-window approach were used to study the dynamic functional connectivity. Dynamic analysis suggested two distinct connectivity 'States' across the entire group: a more frequent, segregated brain state characterized by the predominance of within-network connections, State I, and a less frequent, integrated state with strongly connected functional internetwork components, State II. In Parkinson's disease, State I occurred 13.89% more often than in healthy control subjects, paralleled by a proportional reduction of State II. Parkinson's disease subgroups analyses showed the segregated state occurred more frequently in Parkinson's disease dementia than in mild cognitive impairment and normal cognition groups. Further, patients with Parkinson's disease dementia dwelled significantly longer in the segregated State I, and showed a significant lower number of transitions to the strongly interconnected State II compared to the other subgroups. Our study indicates that dementia in Parkinson's disease is characterized by altered temporal properties in dynamic connectivity. In addition, our results show that increased dwell time in the segregated state and reduced number of transitions between states are associated with presence of dementia in Parkinson's disease. Further studies on dynamic functional connectivity changes could help to better understand the progressive dysfunction of networks between Parkinson's disease cognitive states.