Dopaminergic basis for impairments in functional connectivity across subdivisions of the striatum in Parkinson's disease

Chemically Synthesized AgNPs and Piriformosporaindica Synergistically Augment Nutritional Quality in Black Rice

The use of biofertilizers has been the spotlight of research aiming to mitigate the food security threat as well as to restore the fertility of agricultural lands, for decades. Several studies are being conducted to unravel the role and mechanisms of plant growth-promoting microbes. In the present research, we evaluated the effect of silver nanoparticles (AgNPs) and Piriformospora indica on the growth and nutritional enhancement of black rice (Oryzae sativa. L.) individually and in combination. Among the different treatment conditions, the AgNPs + P. indica treatment led to a significant (p ≤ 0.05) increase in morphological and agronomic parameters. In comparison to the control, the percentage increase in plant height in AgNPs-treated black rice was 2.47%, while that for the treatment with only P. indica was 13.2% and that for the treatment with both AgNPs + P. indica was 30.9%. For the number of productive tillers, the effect of AgNPs in comparison to the control was non-significant; however, the effect of P. indica and AgNPs + P. indica showed a significant (p ≤ 0.05) increase of 13.2% and 30.9% in both the treatments, respectively. Gas chromatography mass spectrophotometry analysis of grains revealed that the contents of phenylalanine, tryptophan, and histidine (aromatic amino acids) were significantly (p ≤ 0.05) increased by 75%, 11.1%, and 50%, respectively, in P. indica-treated black rice. Nutrient profiling showed that macronutrients such as potassium, calcium, magnesium were found to be increased by 72.8%, 86.4% and 59.2%, respectively, in the treatment with AgNPs + P. indica in comparison to the control plants. Additionally, a significant (p ≤ 0.05) increase of 51.9% in anthocyanin content was observed in AgNPs + P. indica-treated black rice. The P. indica treatment also showed improved growth and augmented nutrient contents. From this study, we were able to understand that AgNPs + P. indica treatment would be a better plant growth-promoting factor and further evaluation would enable us to obtain a clear picture of its mechanisms of action.

Temporal and spatial variability of dynamic microstate brain network in early Parkinson's disease

Changes of brain network dynamics reveal variations in macroscopic neural activity patterns in behavioral and cognitive aspects. Quantification and application of changed dynamics in brain functional connectivity networks may contribute to a better understanding of brain diseases, and ultimately provide better prognostic indicators or auxiliary diagnostic tools. At present, most studies are focused on the properties of brain functional connectivity network constructed by sliding window method. However, few studies have explored evidence-based brain network construction algorithms that reflect disease specificity. In this work, we first proposed a novel approach to characterize the spatiotemporal variability of dynamic functional connectivity networks based on electroencephalography (EEG) microstate, and then developed a classification framework for integrating spatiotemporal variability of brain networks to improve early Parkinson's disease (PD) diagnostic performance. The experimental results indicated that compared with the brain network construction method based on conventional sliding window, the proposed method significantly improved the performance of early PD recognition, demonstrating that the dynamic spatiotemporal variability of microstate-based brain networks can reflect the pathological changes in the early PD brain. Furthermore, we observed that the spatiotemporal variability of early PD brain network has a specific distribution pattern in brain regions, which can be quantified as the degree of motor and cognitive impairment, respectively. Our work offers innovative methodological support for future research on brain network, and provides deeper insights into the spatiotemporal interaction patterns of brain activity and their variabilities in early PD.

Dopaminergic medication normalizes aberrant cognitive control circuit signalling in Parkinson's disease

Dopaminergic medication is widely used to alleviate motor symptoms of Parkinson's disease, but these medications also impact cognition with significant variability across patients. It is hypothesized that dopaminergic medication impacts cognition and working memory in Parkinson's disease by modulating frontoparietal-basal ganglia cognitive control circuits, but little is known about the underlying causal signalling mechanisms and their relation to individual differences in response to dopaminergic medication. Here we use a novel state-space computational model with ultra-fast (490 ms resolution) functional MRI to investigate dynamic causal signalling in frontoparietal-basal ganglia circuits associated with working memory in 44 Parkinson's disease patients ON and OFF dopaminergic medication, as well as matched 36 healthy controls. Our analysis revealed aberrant causal signalling in frontoparietal-basal ganglia circuits in Parkinson's disease patients OFF medication. Importantly, aberrant signalling was normalized by dopaminergic medication and a novel quantitative distance measure predicted individual differences in cognitive change associated with medication in Parkinson's disease patients. These findings were specific to causal signalling measures, as no such effects were detected with conventional non-causal connectivity measures. Our analysis also identified a specific frontoparietal causal signalling pathway from right middle frontal gyrus to right posterior parietal cortex that is impaired in Parkinson's disease. Unlike in healthy controls, the strength of causal interactions in this pathway did not increase with working memory load and the strength of load-dependent causal weights was not related to individual differences in working memory task performance in Parkinson's disease patients OFF medication. However, dopaminergic medication in Parkinson's disease patients reinstated the relation with working memory performance. Our findings provide new insights into aberrant causal brain circuit dynamics during working memory and identify mechanisms by which dopaminergic medication normalizes cognitive control circuits.

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.

Altered Intrinsic Regional Spontaneous Brain Activity in Patients With Severe Obesity and Meibomian Gland Dysfunction: A Resting-State Functional Magnetic Resonance Imaging Study

Purpose

To evaluate potential regional homogeneity (ReHo) cerebrum function lesions in people with severe obesity and meibomian gland dysfunction (SM) and probe the connection between aberrant cerebrum activity and clinical manifestations.

Patients and Methods

An aggregation of 12 patients with SM, and 12 healthy controls (HCs) closely matched in age and gender were enrolled. We applied corneal confocal microscopy and fundus angiography to compare imaging distinctions between the two groups. SMs were required to carefully fill out the Hospital Anxiety Depression Scale (HADS) forms, and a correlation analysis was performed. ReHo was also utilized to appraise partial differences in spontaneous cerebrum function. Receiver operating characteristic (ROC) curves were created to partition ReHo values between patients with SM and the HCs.

Results

ReHo values for the left cerebellum (LC), right fusiform gyrus (RFG), left inferior temporal gyrus (LITG), left rectus gyrus (LRG), right thalamus (RT), right caudate (RC), left insula (LI), and left thalamus (LT) of subjects with SM were notably higher than those of the HCs (P < 0.05). ReHo values of the right middle frontal gyrus (RMFG) in subjects with SM were decreased notably compared to the HCs (P < 0.05). ReHo values for the RMFG showed a negative correlation with the anxiety scores (ASs; r = −0.961, P < 0.001) and ReHo values for the RFG showed a positive correlation with the depression scores (DSs; r = 0.676, P = 0.016). The areas under the ROC curve were 1.000 (P < 0.001) for the RMFG, LC, LITG, LRG, RC, LI, and LT and 0.993 (P < 0.001) for the RFG and RT. The results from the ROC curve analysis indicated that changes in the ReHo values of some brain regions may help diagnose SM.

Conclusion

Our research emphasized that patients with SM had lesions in synchronized neural activity in many encephalic areas. Our discoveries may provide beneficial information for exploring the neuromechanics of SM.

Narrow doorways alter brain connectivity and step patterns in isolated REM sleep behaviour disorder

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iRBD had slower and more variable stepping compared to controls in this VR task.

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iRBD showed exaggerated responses when passing narrow compared to wide doorways iRBD had altered task-related brain connectivity which was correlated to motor deficits.

Background

Motor impairments in those with isolated REM sleep behaviour disorder (iRBD) significantly increases the likelihood of developing Lewy body disease (e.g. Parkinson’s disease and Dementia with Lewy Bodies).

Objective

This study sought to explore the prodromal process of neurodegeneration by examining the neural signature underlying motor deficits in iRBD patients.

Methods

A virtual reality (VR) gait paradigm (which has previously been shown to elicit adaptive changes in gait performance whilst navigating doorways in Parkinson’s Disease - PD) was paired with fMRI to investigate whether iRBD patients demonstrated worsened motor performance and altered connectivity across frontoparietal, motor and basal ganglia networks compared to healthy controls. Forty participants (23 iRBD and 17 healthy controls) completed the virtual reality gait task whilst in the MRI scanner, and an additional cohort of 19 Early PD patients completed the behavioural virtual reality gait task.

Results

As predicted, iRBD patients demonstrated slower and more variable stepping compared to healthy control participants and demonstrated an exaggerated response when navigating narrow compared to wide doorways, a phenomenon characteristically seen in PD. The iRBD patients also demonstrated less BOLD signal change in the left posterior putamen and right mesencephalic locomotor region, as well as reduced functional connectivity between the frontoparietal network and the motor network, when navigating narrow versus wide doorways compared to healthy control participants.

Conclusions

Taken together, this study demonstrates that iRBD patients have altered task-related brain connectivity, which may represent the neural underpinnings of early motor impairments that are evident in iRBD.

Longitudinal clustering analysis and prediction of Parkinson's disease progression using radiomics and hybrid machine learning

BACKGROUND

We employed machine learning approaches to (I) determine distinct progression trajectories in Parkinson's disease (PD) (unsupervised clustering task), and (II) predict progression trajectories (supervised prediction task), from early (years 0 and 1) data, making use of clinical and imaging features.

METHODS

We studied PD-subjects derived from longitudinal datasets (years 0, 1, 2 & 4; Parkinson's Progressive Marker Initiative). We extracted and analyzed 981 features, including motor, non-motor, and radiomics features extracted for each region-of-interest (ROIs: left/right caudate and putamen) using our standardized standardized environment for radiomics analysis (SERA) radiomics software. Segmentation of ROIs on dopamine transposer - single photon emission computed tomography (DAT SPECT) images were performed via magnetic resonance images (MRI). After performing cross-sectional clustering on 885 subjects (original dataset) to identify disease subtypes, we identified optimal longitudinal trajectories using hybrid machine learning systems (HMLS), including principal component analysis (PCA) + K-Means algorithms (KMA) followed by Bayesian information criterion (BIC), Calinski-Harabatz criterion (CHC), and elbow criterion (EC). Subsequently, prediction of the identified trajectories from early year data was performed using multiple HMLSs including 16 Dimension Reduction Algorithms (DRA) and 10 classification algorithms.

RESULTS

We identified 3 distinct progression trajectories. Hotelling's t squared test (HTST) showed that the identified trajectories were distinct. The trajectories included those with (I, II) disease escalation (2 trajectories, 27% and 38% of patients) and (III) stable disease (1 trajectory, 35% of patients). For trajectory prediction from early year data, HMLSs including the stochastic neighbor embedding algorithm (SNEA, as a DRA) as well as locally linear embedding algorithm (LLEA, as a DRA), linked with the new probabilistic neural network classifier (NPNNC, as a classifier), resulted in accuracies of 78.4% and 79.2% respectively, while other HMLSs such as SNEA + Lib_SVM (library for support vector machines) and t_SNE (t-distributed stochastic neighbor embedding) + NPNNC resulted in 76.5% and 76.1% respectively.

CONCLUSIONS

This study moves beyond cross-sectional PD subtyping to clustering of longitudinal disease trajectories. We conclude that combining medical information with SPECT-based radiomics features, and optimal utilization of HMLSs, can identify distinct disease trajectories in PD patients, and enable effective prediction of disease trajectories from early year data.

Altered resting-state functional connectivity of the frontal-striatal circuit in elderly with apathy

Apathy is defined as reduction of goal-directed behaviors and a common nuisance syndrome of neurodegenerative and psychiatric disease. The underlying mechanism of apathy implicates changes of the front-striatal circuit, but its precise alteration is unclear for apathy in healthy aged people. The aim of our study is to investigate how the frontal-striatal circuit is changed in elderly with apathy using resting-state functional MRI. Eighteen subjects with apathy (7 female, 63.7 ± 3.0 years) and eighteen subjects without apathy (10 female, 64.8 ± 3.0 years) who underwent neuropsychological assessment and MRI measurement were recruited. We compared functional connectivity with/within the striatum between the apathy and non-apathy groups. The seed-to-voxel group analysis for functional connectivity between the striatum and other brain regions showed that the connectivity was decreased between the ventral rostral putamen and the right dorsal anterior cingulate cortex/supplementary motor area in the apathy group compared to the non-apathy group while the connectivity was increased between the dorsal caudate and the left sensorimotor area. Moreover, the ROI-to-ROI analysis within the striatum indicated reduction of functional connectivity between the ventral regions and dorsal regions of the striatum in the apathy group. Our findings suggest that the changes in functional connectivity balance among different frontal-striatum circuits contribute to apathy in elderly.

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

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

More Than Just Static: Dynamic Functional Connectivity Changes of the Thalamic Nuclei to Cortex in Parkinson's Disease With Freezing of Gait

Background: The thalamus is not only a key relay node of the thalamocortical circuit but also a hub in the regulation of gait. Previous studies of resting-state functional magnetic resonance imaging (fMRI) have shown static functional connectivity (FC) between the thalamus and the cortex are disrupted in Parkinson's disease (PD) patients with freezing of gait (FOG). However, temporal dynamic FC between the thalamus and the cortex has not yet been characterized in these patients.

Methods: Fifty PD patients, including 25 PD patients with FOG (PD-FOG) and 25 PD patients without FOG (PD-NFOG), and 25 healthy controls (HC) underwent resting-state fMRI. Seed-voxel-wise static and dynamic FC were calculated between each thalamic nuclei and other voxels across the brain using the 14 thalamic nuclei in both hemispheres as regions of interest. Associations between altered thalamic FC based on significant inter-group differences and severity of FOG symptoms were also examined in PD-FOG.

Results: Both PD-FOG and PD-NFOG showed lower static FC between the right lateral posterior thalamic nuclei and right inferior parietal lobule (IPL) compared with HC. Altered FC dynamics between the thalamic nuclei and several cortical areas were identified in PD-FOG, as shown by temporal dynamic FC analyses. Specifically, relative to PD-NFOG or HC, PD-FOG showed greater fluctuations in FC between the left intralaminar (IL) nuclei and right IPL and between the left medial geniculate and left postcentral gyrus. Furthermore, the dynamics of FC between the left pulvinar anterior nuclei and left inferior frontal gyrus were upregulated in both PD-FOG and PD-NFOG. The dynamics of FC between the right ventral lateral nuclei and left paracentral lobule were elevated in PD-NFOG but were maintained in PD-FOG and HC. The quantitative variability of FC between the left IL nuclei and right IPL was positively correlated with the clinical scales scores in PD-FOG.

Conclusions: Dynamic FC between the thalamic nuclei and relevant associative cortical areas involved in sensorimotor integration or cognitive function was disrupted in PD-FOG, which was reflected by greater temporal fluctuations. Abnormal dynamic FC between the left IL nuclei of the thalamus and right IPL was related to the severity of FOG.

Feature selection and machine learning methods for optimal identification and prediction of subtypes in Parkinson's disease

OBJECTIVES

The present work focuses on assessment of Parkinson's disease (PD), including both PD subtype identification (unsupervised task) and prediction (supervised task). We specifically investigate optimal feature selection and machine learning algorithms for these tasks.

METHODS

We selected 885 PD subjects as derived from longitudinal datasets (years 0-4; Parkinson's Progressive Marker Initiative), and investigated 981 features including motor, non-motor, and imaging features (SPECT-based radiomics features extracted using our standardized SERA software). Two different hybrid machine learning systems (HMLS) were constructed and applied to the data in order to select optimal combinations in both tasks: (i) identification of subtypes in PD (unsupervised-clustering), and (ii) prediction of these subtypes in year 4 (supervised-classification). From the original data based on years 0 (baseline) and 1, we created new datasets as inputs to the prediction task: (i,ii) CSD0 and CSD01: cross-sectional datasets from year 0 only and both years 0 & 1, respectively; (iii) TD01: timeless dataset from both years 0 & 1. In addition, PD subtype in year 4 was considered as outcome. Finally, high score features were derived via ensemble voting based on their prioritizations from feature selector algorithms (FSAs).

RESULTS

In clustering task, the most optimal combinations (out of 981) were selected by individual FSAs to enable high correlation compared to using all features (arriving at 547). In prediction task, we were able to select optimal combinations, resulting in an accuracy >90% only for timeless dataset (TD01); there, we were able to select the most optimal combination using 77 features, directly selected by FSAs. In both tasks, however, using combination of only high score features from ensemble voting did not enable acceptable performances, showing optimal feature selection via individual FSAs to be more effective.

CONCLUSION

Combining non-imaging information with SPECT-based radiomics features, and optimal utilization of HMLSs, can enable robust identification of subtypes as well as appropriate prediction of these subtypes in PD patients. Moreover, use of timeless dataset, beyond cross-sectional datasets, enabled predictive accuracies over 90%. Overall, we showed that radiomics features extracted from SPECT images are important in clustering as well as prediction of PD subtypes.

Structural and functional neuroimaging changes associated with cognitive impairment and dementia in Parkinson's disease

This study seeks a better understanding of possible pathophysiological mechanisms associated with cognitive impairment and dementia in Parkinson's disease using structural and functional MRI. We investigated resting-state functional connectivity of important subdivisions of the caudate nucleus, putamen and thalamus, and also how the morphology of these structures are impacted in the disorder. We found cognitively unimpaired Parkinson's disease subjects (n = 33), compared to controls (n = 26), display increased functional connectivity of the dorsal caudate, anterior putamen and mediodorsal thalamic subdivisions with areas across the frontal lobe, as well as reduced functional connectivity of the dorsal caudate with posterior cortical and cerebellar regions. Compared to cognitively unimpaired subjects, those with mild cognitive impairment (n = 22) demonstrated reduced functional connectivity of the mediodorsal thalamus with the paracingulate cortex, while also demonstrating increased functional connectivity of the mediodorsal thalamus with the posterior cingulate cortex, compared to subjects with dementia (n = 17). Extensive volumetric and surface-based deflation was found in subjects with dementia compared to cognitively unimpaired Parkinson's disease participants and controls. Our research suggests that structures within basal ganglia-thalamocortical circuits are implicated in cognitive impairment and dementia in Parkinson's disease, with cognitive impairment and dementia associated with a breakdown in functional connectivity of the mediodorsal thalamus with para- and posterior cingulate regions of the brain respectively.

Motor Symptom Lateralization Influences Cortico-Striatal Functional Connectivity in Parkinson's Disease

Objective: The striatum is unevenly impaired bilaterally in Parkinson's disease (PD). Because the striatum plays a key role in cortico-striatal circuits, we assume that lateralization affects cortico-striatal functional connectivity in PD. The present study sought to evaluate the effect of lateralization on various cortico-striatal circuits through resting-state functional magnetic resonance imaging (fMRI). Methods: Thirty left-onset Parkinson's disease (LPD) patients, 27 right-onset Parkinson's disease (RPD) patients, and 32 normal controls with satisfactory data were recruited. Their demographic, clinical, and neuropsychological information was collected. Resting-state fMRI was performed, and functional connectivity changes of seven subdivisions of the striatum were explored in the two PD groups. In addition, the associations between altered functional connectivity and various clinical and neuropsychological characteristics were analyzed by Pearson's or Spearman's correlation. Results: Directly comparing the LPD and RPD patients demonstrated that the LPD patients had lower FC between the left dorsal rostral putamen and the left orbitofrontal cortex than the RPD patients. In addition, the LPD patients showed aberrant functional connectivity involving several striatal subdivisions in the right hemisphere. The right dorsal caudate, ventral rostral putamen, and superior ventral striatum had decreased functional connectivity with the cerebellum and parietal and occipital lobes relative to the normal control group. The comparison between RPD patients and the controls did not obtain significant difference in functional connectivity. The functional connectivity between the left dorsal rostral putamen and the left orbitofrontal cortex was associated with contralateral motor symptom severity in PD patients. Conclusions: Our findings provide new insights into the distinct characteristics of cortico-striatal circuits in LPD and RPD patients. Lateralization of motor symptoms is associated with lateralized striatal functional connectivity.

Cortical Activity Underlying Gait Improvements Achieved With Dopaminergic Medication During Usual Walking and Obstacle Avoidance in Parkinson Disease

BACKGROUND

Dopaminergic medication improves gait in people with Parkinson disease (PD). However, it remains unclear if dopaminergic medication modulates cortical activity while walking.

OBJECTIVE

We investigated the effects of dopaminergic medication on cortical activity during unobstructed walking and obstacle avoidance in people with PD.

METHODS

A total of 23 individuals with PD, in both off (PD_OFF) and on (PD_ON) medication states, and 30 healthy older adults (control group [CG]) performed unobstructed walking and obstacle avoidance conditions. Cortical activity was acquired through a combined functional near-infrared spectroscopy electroencephalography (EEG) system, along with gait parameters, through an electronic carpet. Prefrontal cortex (PFC) oxygenated hemoglobin (HbO₂) and EEG absolute power from FCz, Cz, and CPz channels were calculated.

RESULTS

HbO₂ concentration reduced for people with PD_OFF during obstacle avoidance compared with unobstructed walking. In contrast, both people with PD_ON and the CG had increased HbO₂ concentration when avoiding obstacles compared with unobstructed walking. Dopaminergic medication increased step length, step velocity, and β and γ power in the CPz channel, regardless of walking condition. Moreover, dopaminergic-related changes (ie, on-off) in FCz/CPz γ power were associated with dopaminergic-related changes in step length for both walking conditions.

CONCLUSIONS

PD compromises the activation of the PFC during obstacle avoidance, and dopaminergic medication facilitates its recruitment. In addition, PD medication increases sensorimotor integration during walking by increasing posterior parietal cortex (CPz) activity. Increased γ power in the CPz and FCz channels is correlated with step length improvements achieved with dopaminergic medication during unobstructed walking and obstacle avoidance in PD.

Modulation of glutamatergic functional connectivity by a prototypical antipsychotic: Translational inference from a postsynaptic density immediate-early gene-based network analysis

BACKGROUND

Although extensively studied, the effect of antipsychotics is not completely understood at a network level. We tested the hypothesis that acute administration of haloperidol would modulate functional connectivity of brain regions relevant to schizophrenia pathophysiology. To assess putative changes in brain network properties and regional interactivity, we studied the expression of Homer1a, an Immediate Early Gene (IEG) demonstrated to be induced by antipsychotic administration and coding for a protein involved in glutamatergic synapses remodeling.

METHODS

Sprague-Dawley rats (n = 26) assigned to vehicle (VEH; NaCl 0.9%) or haloperidol (HAL; 0.8 mg/kg) were included in the network analysis. Homer1a mRNA induction was evaluated by in situ hybridization. Signal intensity analysis was performed in 33 Regions of Interest (ROIs) in the cortex, the caudate putamen, and the nucleus accumbens. A signal correlation analysis was performed, computing all possible pairwise Pearson correlations among ROIs in the two groups. Two networks were generated for HAL and VEH groups, and their properties and topography were explored.

RESULTS

VEH and HAL networks showed qualitative differences in global efficiency and clustering coefficient. The HAL network showed enhanced interactivity between cortical and striatal regions, and within caudate putamen subdivisions. On the other hand, it exhibited reduced inter-correlations between cingulate cortex and anterior insula and caudate putamen and nucleus accumbens. Moreover, haloperidol was able to modulate centrality of crucial functional hubs. These preclinical results corroborate and expand the clinical evidence that antipsychotics may modulate specific brain network properties and disease-related circuits' interactivity.

G-protein coupled receptor 88 knockdown in the associative striatum reduces psychiatric symptoms in a translational male rat model of Parkinson disease

BACKGROUND

In addition to motor disability, another characteristic feature of Parkinson disease is the early appearance of psychiatric symptoms, including apathy, depression, anxiety and cognitive deficits; treatments for these symptoms are limited by the development of adverse effects such as impulse-control disorders. In this context, we investigated the orphan G protein-coupled receptor 88 (GPR88) as a novel therapeutic target.

METHODS

We used lentiviral-mediated expression of specifically designed microRNA to knock down Gpr88 in a translational male rat model of early Parkinson disease obtained by dopamine loss in the dorsolateral striatum as a result of 6-hydroxydopamine lesions. We evaluated the impact of Gpr88 knockdown on the Parkinson disease model using behavioural, immunohistochemical and in situ hybridization studies.

RESULTS

Knockdown of Gpr88 in associative territories of the dorsal striatum efficiently reduced alterations in mood, motivation and cognition through modulation of the regulator of the G-protein signalling 4 and of the truncated splice variant of the FosB transcription factor. Knockdown of Gpr88 also reduced allostatic changes in striatal activity markers that may be related to patterns observed in patients and that provide support for an "overload" hypothesis for the etiology of the psychiatric symptoms of Parkinson disease.

LIMITATIONS

Behavioural tests assessing specific cognitive and motivational parameters are needed to further characterize the effects of the lesion and of Gpr88 knockdown in early-stage and advanced Parkinson disease models, presenting more extensive dopamine loss. Additional studies focusing on the direct and indirect striatal output pathways are also required, because little is known about the signalling pathways regulated by GPR88 in different striatal cell types.

CONCLUSION

GPR88 may constitute a highly relevant target for the treatment of the psychiatric symptoms of Parkinson disease.

Theta and gamma connectivity is linked with affective and cognitive symptoms in Parkinson's disease

BACKGROUND

The progression of Parkinson's disease (PD) can often exacerbate symptoms of depression, anxiety, and/or cognitive impairment. In this study, we explore the possibility that multiple brain network responses are associated with symptoms of depression, anxiety and cognitive impairment in PD. This association is likely to provide insights into a single multivariate relationship, where common affective symptoms occurring in PD cohorts are related with alterations to electrophysiological response.

METHODS

70 PD patients and 21 healthy age-matched controls (HC) participated in a high-density electroencephalography (EEG) study. Functional connectivity differences between PD and HC groups of oscillatory activity at rest and during completion of an emotion-cognition task were examined to identify key brain oscillatory activities. A canonical correlation analysis (CCA) was applied to identify a putative multivariate relationship between connectivity patterns and affective symptoms in PD groups.

RESULTS

A CCA analysis identified a single mode of co-variation linking theta and gamma connectivity with affective symptoms in PD groups. Increases in frontotemporal gamma, frontal and parietal theta connectivity were related with increased anxiety and cognitive impairment. Decreases in temporal region theta and frontoparietal gamma connectivity were associated with higher depression ratings and PD patient age.

LIMITATIONS

This study only reports on optimal dosage of dopaminergic treatment ('on' state) in PD and did not investigate at "off" medication".

CONCLUSIONS

Theta and gamma connectivity during rest and task-states are linked to affective and cognitive symptoms within fronto-temporo-parietal networks, suggesting a potential assessment avenue for understanding brain-behaviour associations in PD with electrophysiological task paradigms.

Robust identification of Parkinson's disease subtypes using radiomics and hybrid machine learning

OBJECTIVES

It is important to subdivide Parkinson's disease (PD) into subtypes, enabling potentially earlier disease recognition and tailored treatment strategies. We aimed to identify reproducible PD subtypes robust to variations in the number of patients and features.

METHODS

We applied multiple feature-reduction and cluster-analysis methods to cross-sectional and timeless data, extracted from longitudinal datasets (years 0, 1, 2 & 4; Parkinson's Progressive Marker Initiative; 885 PD/163 healthy-control visits; 35 datasets with combinations of non-imaging, conventional-imaging, and radiomics features from DAT-SPECT images). Hybrid machine-learning systems were constructed invoking 16 feature-reduction algorithms, 8 clustering algorithms, and 16 classifiers (C-index clustering evaluation used on each trajectory). We subsequently performed: i) identification of optimal subtypes, ii) multiple independent tests to assess reproducibility, iii) further confirmation by a statistical approach, iv) test of reproducibility to the size of the samples.

RESULTS

When using no radiomics features, the clusters were not robust to variations in features, whereas, utilizing radiomics information enabled consistent generation of clusters through ensemble analysis of trajectories. We arrived at 3 distinct subtypes, confirmed using the training and testing process of k-means, as well as Hotelling's T2 test. The 3 identified PD subtypes were 1) mild; 2) intermediate; and 3) severe, especially in terms of dopaminergic deficit (imaging), with some escalating motor and non-motor manifestations.

CONCLUSION

Appropriate hybrid systems and independent statistical tests enable robust identification of 3 distinct PD subtypes. This was assisted by utilizing radiomics features from SPECT images (segmented using MRI). The PD subtypes provided were robust to the number of the subjects, and features.

Elevated caudate connectivity in cognitively normal Parkinson's disease patients

Mild cognitive impairment (MCI) is common in Parkinson’s disease patients. However, its underlying mechanism is not well understood, which has hindered new treatment discoveries specific to MCI. The aim of this study was to investigate functional connectivity changes of the caudate nucleus in cognitively impaired Parkinson’s patients. We recruited 18 Parkinson’s disease patients—10 PDNC [normal cognition Parkinson’s disease; Montreal Cognitive Assessment (MoCA) ≥ 26], 8 PDLC (low cognition Parkinson’s disease; MoCA < 26) —and 10 age-matched healthy controls. All subjects were scanned with resting-state functional magnetic resonance imaging (MRI) and perfusion MRI. We analyzed these data for graph theory metrics and Alzheimer’s disease-like pattern score, respectively. A strong positive correlation was found between the functional connectivity of the right caudate nucleus and MoCA scores in Parkinson’s patient groups, but not in healthy control subjects. Interestingly, PDNC’s functional connectivity of the right caudate was significantly higher than both PDLC and healthy controls, while PDLC and healthy controls were not significantly different from each other. We found that Alzheimer’s disease-like metabolic/perfusion pattern score correlated with MoCA scores in healthy controls, but not in Parkinson’s disease. Increased caudate connectivity may be related to a compensatory mechanism found in cognitively normal patients with Parkinson’s disease. Our findings support and complement the dual syndrome hypothesis.

Longitudinal functional connectivity changes related to dopaminergic decline in Parkinson's disease

BACKGROUND

Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated that basal ganglia functional connectivity is altered in Parkinson's disease (PD) as compared to healthy controls. However, such functional connectivity alterations have not been related to the dopaminergic deficits that occurs in PD over time.

OBJECTIVES

To examine whether functional connectivity impairments are correlated with dopaminergic deficits across basal ganglia subdivisions in patients with PD both cross-sectionally and longitudinally.

METHODS

We assessed resting-state functional connectivity of basal ganglia subdivisions and dopamine transporter density using 11C-PE2I PET in thirty-four PD patients at baseline. Of these, twenty PD patients were rescanned after 19.9 ± 3.8 months. A seed-based approach was used to analyze resting-state fMRI data. 11C-PE2I binding potential (BPND) was calculated for each participant. PD patients were assessed for disease severity.

RESULTS

At baseline, PD patients with greater dopaminergic deficits, as measured with 11C-PE2I PET, showed larger decreases in posterior putamen functional connectivity with the midbrain and pallidum. Reduced functional connectivity of the posterior putamen with the thalamus, midbrain, supplementary motor area and sensorimotor cortex over time were significantly associated with changes in DAT density over the same period. Furthermore, increased motor disability was associated with lower intraregional functional connectivity of the posterior putamen.

CONCLUSIONS

Our findings suggest that basal ganglia functional connectivity is related to integrity of dopaminergic system in patients with PD. Application of resting-state fMRI in a large cohort and longitudinal scanning may be a powerful tool for assessing underlying PD pathology and its progression.

Common and unique connectivity at the interface of motor, neuropsychiatric, and cognitive symptoms in Parkinson's disease: A commonality analysis

Parkinson's disease (PD) is characterized by overlapping motor, neuropsychiatric, and cognitive symptoms. Worse performance in one domain is associated with worse performance in the other domains. Commonality analysis (CA) is a method of variance partitioning in multiple regression, used to separate the specific and common influence of collinear predictors. We apply, for the first time, CA to the functional connectome to investigate the unique and common neural connectivity underlying the interface of the symptom domains in 74 non-demented PD subjects. Edges were modeled as a function of global motor, cognitive, and neuropsychiatric scores. CA was performed, yielding measures of the unique and common contribution of the symptom domains. Bootstrap confidence intervals were used to determine the precision of the estimates and to directly compare each commonality coefficient. The overall model identified a network with the caudate nucleus as a hub. Neuropsychiatric impairment accounted for connectivity in the caudate-dorsal anterior cingulate and caudate-right dorsolateral prefrontal-right inferior parietal circuits, while caudate-medial prefrontal connectivity reflected a unique effect of both neuropsychiatric and cognitive impairment. Caudate-precuneus connectivity was explained by both unique and shared influence of neuropsychiatric and cognitive symptoms. Lastly, posterior cortical connectivity reflected an interplay of the unique and common effects of each symptom domain. We show that CA can determine the amount of variance in the connectome that is unique and shared amongst motor, neuropsychiatric, and cognitive symptoms in PD, thereby improving our ability to interpret the data while gaining novel insight into networks at the interface of these symptom domains.

Abnormal distraction and load-specific connectivity during working memory in cognitively normal Parkinson's disease

Visuospatial working memory impairments are common in Parkinson's disease (PD), yet the underlying neural mechanisms are poorly understood. The present study investigated abnormalities in context‐dependent functional connectivity of working memory hubs in PD. Cognitively normal PD and control participants underwent fMRI while performing a visuospatial working memory task. To identify sources of dysfunction, distraction, and load‐modulated connectivity were disentangled for encoding and retrieval phases of the task. Despite normal working memory performance in PD, two features of abnormal connectivity were observed, one due to a loss in normal context‐related connectivity and another related to upregulated connectivity of hubs for which the controls did not exhibit context‐dependent connectivity. During encoding, striatal‐prefrontal coupling was lost in PD, both during distraction and high memory loads. However, long‐range connectivity of prefrontal, medial temporal and occipital hubs was upregulated in a context‐specific manner. Memory retrieval was characterized by different aberrant connectivity patterns, wherein precuneus connectivity was upregulated during distraction, whereas prefrontal couplings were lost as memory load approached capacity limits. Features of abnormal functional connectivity in PD had pathological and compensatory influences as they correlated with poorer working memory or better visuospatial skills. The results offer new insights into working memory‐related signatures of aberrant cortico–cortical and corticostriatal functional connections, which may portend future declines in different facets of working memory.

Chronic psychosocial stressors are associated with alterations in salience processing and corticostriatal connectivity

Psychosocial stressors including childhood adversity, migration, and living in an urban environment, have been associated with several psychiatric disorders, including psychotic disorders. The neural and psychological mechanisms mediating this relationship remain unclear. In parallel, alterations in corticostriatal connectivity and abnormalities in the processing of salience, are seen in psychotic disorders. Aberrant functioning of these mechanisms secondary to chronic stress exposure, could help explain how common environmental exposures are associated with a diverse range of symptoms. In the current study, we recruited two groups of adults, one with a high degree of exposure to chronic psychosocial stressors (the exposed group, n = 20), and one with minimal exposure (the unexposed group, n = 22). All participants underwent a resting state MRI scan, completed the Aberrant Salience Inventory, and performed a behavioural task - the Salience Attribution Test (SAT). The exposed group showed reduced explicit adaptive salience scores (cohen's d = 0.69, p = 0.03) and increased aberrant salience inventory scores (d = 0.65, p = 0.04). The exposed group also showed increased corticostriatal connectivity between the ventral striatum and brain regions previously implicated in salience processing. Corticostriatal connectivity in these regions negatively correlated with SAT explicit adaptive salience (r = -0.48, p = 0.001), and positively correlated with aberrant salience inventory scores (r = 0.42, p = 0.006). Furthermore, in a mediation analysis there was tentative evidence that differences in striato-cortical connectivity mediated the group differences in salience scores.

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

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

Effect of Dopaminergic Medications on Blood Oxygen Level-Dependent Variability and Functional Connectivity in Parkinson's Disease and Healthy Aging

Both functional connectivity (FC) and blood oxygen level-dependent (BOLD) signal variability (SDBOLD) are methods that are used for examining the physiological state of the brain. Although they are derived from signal changes and are related, a few studies have explored their relationship. Here, we examined the relationship between SDBOLD and FC within the default mode network (DMN) in healthy aging participants and those with Parkinson's disease (PD) ON and OFF dopaminergic medications. Dopaminergic medications had profound effects on both DMN FC and SDBOLD measured separately in PD. Analyzing DMN FC and SDBOLD in a joint independent component analysis, we identified joint components of DMN FC and SDBOLD that were separately associated with measurements of motor and cognitive impairment in PD and qualitatively similar to those in healthy aging. Dopaminergic medications had a differential effect on these components depending on these measures of disease severity, "normalizing" the relationships. Importantly, we show that dopaminergic medication status matters in imaging PD, and it can affect both connectivity and SDBOLD. Imaging PD ON may lead to inflated estimates of SDBOLD and diminish the ability to measure changes associated with declining motor and cognitive capacities.

Quantitative Susceptibility Mapping and Resting State Network Analyses in Parkinsonian Phenotypes-A Systematic Review of the Literature

An imbalance of iron metabolism with consecutive aggregation of α-synuclein and axonal degeneration of neurons has been postulated as the main pathological feature in the development of Parkinson’s disease (PD). Quantitative susceptibility mapping (QSM) is a new imaging technique, which enables to measure structural changes caused by defective iron deposition in parkinsonian brains. Due to its novelty, its potential as a new imaging technique remains elusive for disease-specific characterization of motor and non-motor symptoms (characterizing the individual parkinsonian phenotype). Functional network changes associated with these symptoms are however frequently described for both magnetoencephalography (MEG) and resting state functional magnetic imaging (rs-fMRI). Here, we performed a systematic review of the current literature about QSM imaging, MEG and rs-fMRI in order to collect existing data about structural and functional changes caused by motor and non-motor symptoms in PD. Whereas all three techniques provide an effect in the motor domain, the understanding of network changes caused by non-motor symptoms is much more lacking for MEG and rs-fMRI, and does not yet really exist for QSM imaging. In order to better understand the influence of pathological iron distribution onto the functional outcome, whole-brain QSM analyses should be integrated in functional analyses (especially for the non-motor domain), to enable a proper pathophysiological interpretation of MEG and rs-fMRI network changes in PD. Herewith, a better understanding of the relationship between neuropathological changes, functional network changes and clinical phenotype might become possible.

The functional network signature of heterogeneity in freezing of gait

Freezing of gait is a complex, heterogeneous, and highly variable phenomenon whose pathophysiology and neural signature remains enigmatic. Evidence suggests that freezing is associated with impairments across cognitive, motor and affective domains; however, most research to date has focused on investigating one axis of freezing of gait in isolation. This has led to inconsistent findings and a range of different pathophysiological models of freezing of gait, due in large part to the tendency for studies to investigate freezing of gait as a homogeneous entity. To investigate the neural mechanisms of this heterogeneity, we used an established virtual reality paradigm to elicit freezing behaviour in 41 Parkinson's disease patients with freezing of gait and examined individual differences in the component processes (i.e. cognitive, motor and affective function) that underlie freezing of gait in conjunction with task-based functional MRI. First, we combined three unique components of the freezing phenotype: impaired set-shifting ability, step time variability, and self-reported anxiety and depression in a principal components analysis to estimate the severity of freezing behaviour with a multivariate approach. By combining these measures, we were then able to interrogate the pattern of task-based functional connectivity associated with freezing (compared to normal foot tapping) in a sub-cohort of 20 participants who experienced sufficient amounts of freezing during task functional MRI. Specifically, we used the first principal component from our behavioural analysis to classify patterns of functional connectivity into those that were associated with: (i) increased severity; (ii) increased compensation; or (iii) those that were independent of freezing severity. Coupling between the cognitive and limbic networks was associated with 'worse freezing severity', whereas anti-coupling between the putamen and the cognitive and limbic networks was related to 'increased compensation'. Additionally, anti-coupling between cognitive cortical regions and the caudate nucleus were 'independent of freezing severity' and thus may represent common neural underpinnings of freezing that are unaffected by heterogenous factors. Finally, we related these connectivity patterns to each of the individual components (cognitive, motor, affective) in turn, thus exposing latent heterogeneity in the freezing phenotype, while also identifying critical functional network signatures that may represent potential targets for novel therapeutic intervention. In conclusion, our findings provide confirmatory evidence for systems-level impairments in the pathophysiology of freezing of gait and further advance our understanding of the whole-brain deficits that mediate symptom expression in Parkinson's disease.

Neural correlates of emotional valence processing in Parkinson's disease: dysfunction in the subcortex

Parkinson's disease (PD) is frequently accompanied by cognitive and neuropsychiatric symptoms including impairments in affective processing. Despite this, mechanisms underlying vulnerability to deficits in affective processing remain unclear. In this study, we utilized functional Magnetic Resonance Imaging (fMRI) and an Affective Go-NoGo paradigm, to examine the neural correlates of emotional valence processing in PD. Results suggest that PD is associated with aberrant processing of emotional valence in subcortical limbic structures. Specifically, we found significant group-by-valence interactions in the ventral striatum and amygdala in response to words of differing emotional valence. Our findings contribute to a broader understanding of affective processing in PD and may provide insights into the mechanisms underlying vulnerability to mood disorders in PD.

Dopamine depletion alters macroscopic network dynamics in Parkinson's disease

Parkinson's disease is primarily characterized by diminished dopaminergic function; however, the impact of these impairments on large-scale brain dynamics remains unclear. It has been difficult to disentangle the direct effects of Parkinson's disease from compensatory changes that reconfigure the functional signature of the whole brain network. To examine the causal role of dopamine depletion in network-level topology, we investigated time-varying network structure in 37 individuals with idiopathic Parkinson's disease, both ON and OFF dopamine replacement therapy, along with 50 age-matched, healthy control subjects using resting state functional MRI. By tracking dynamic network-level topology, we found that the Parkinson's disease OFF state was associated with greater network-level integration than in the ON state. The extent of integration in the OFF state inversely correlated with motor symptom severity, suggesting that a shift toward a more integrated network topology may be a compensatory mechanism associated with preserved motor function in the dopamine depleted OFF state. Furthermore, we were able to demonstrate that measures of both cognitive and brain reserve (i.e. premorbid intelligence and whole brain grey matter volume) had a positive relationship with the relative increase in network integration observed in the dopaminergic OFF state. This suggests that each of these factors plays an important role in promoting network integration in the dopaminergic OFF state. Our findings provide a mechanistic basis for understanding the Parkinson's disease OFF state and provide a further conceptual link with network-level reconfiguration. Together, our results highlight the mechanisms responsible for pathological and compensatory change in Parkinson's disease.

Cerebellar resting-state functional connectivity in Parkinson's disease and multiple system atrophy: Characterization of abnormalities and potential for differential diagnosis at the single-patient level

Background

Recent studies using resting-state functional connectivity and machine-learning to distinguish patients with neurodegenerative diseases from other groups of subjects show promising results. This approach has not been tested to discriminate between Parkinson's disease (PD) and multiple system atrophy (MSA) patients.

Objectives

Our first aim is to characterize possible abnormalities in resting-state functional connectivity between the cerebellum and a set of intrinsic-connectivity brain networks and between the cerebellum and different regions of the striatum in PD and MSA. The second objective of this study is to assess the potential of cerebellar connectivity measures to distinguish between PD and MSA patients at the single-patient level.

Methods

Fifty-nine healthy controls, 62 PD patients, and 30 MSA patients underwent resting-state functional MRI with a 3T scanner. Independent component analysis and dual regression were used to define seven resting-state networks of interest. To assess striatal connectivity, a seed-to-voxel approach was used after dividing the striatum into six regions bilaterally. Measures of cerebellar-brain network and cerebellar-striatal connectivity were then used as features in a support vector machine to discriminate between PD and MSA patients.

Results

MSA patients displayed reduced cerebellar connectivity with different brain networks and with the striatum compared with PD patients and with controls. The classification procedure achieved an overall accuracy of 77.17% with 83.33% of the MSA subjects and 74.19% of the PD patients correctly classified.

Conclusion

Our findings suggest that measures of cerebellar functional connectivity have the potential to distinguish between PD and MSA patients.

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Reduced cerebellar functional connectivity in MSA compared with healthy controls.

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Reduced cerebellar-striatal functional connectivity in MSA compared with PD.

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Reduced connectivity between cerebellum and brain networks in MSA compared with PD.

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Cerebellar connectivity might help discriminate between MSA and PD patients.

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

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

Apathy and brain alterations in Parkinson's disease: a multimodal imaging study

OBJECTIVE

Apathy is a common nonmotor symptom in Parkinson's disease (PD) affecting 40% of patients. The aim of the study was to investigate brain changes and correlates of frontal, striatal, and limbic pathways related to subclinical symptoms of apathy in PD patients.

METHODS

Thirty-two PD patients divided into low-subclinical symptoms of apathy (LSA) (n = 18) and high-subclinical symptoms of apathy (HSA) (n = 14) and 25 healthy controls (HC) underwent a T1-weighted, diffusion-weighted, and resting-state functional MRI. Apathy was evaluated with the Lille Apathy Rating Scale. Voxel-based morphometry, tract-based spatial statistics, and resting-state functional connectivity (FC) analyses were performed with a region-of-interest approach.

RESULTS

HSA-PD showed increased white matter axial and mean diffusivity compared with HC and increased white matter axial diffusivity compared with LSA-PD. HSA-PD showed decreased fronto-striatal and fronto-limbic FC compared with HC and decreased fronto-striatal FC compared with LSA-PD. LSA-PD showed decreased fronto-limbic but increased fronto-striatal FC (hyperconnectivity) compared with HC. No significant differences in grey matter were found. Fronto-striatal FC and white matter axial and mean diffusivity were associated with symptoms of apathy in HSA-PD. The fronto-striatal hyperconnectivity was associated with lower symptoms of apathy in LSA-PD.

INTERPRETATION

Findings suggest distinct brain alterations in PD groups with subclinical symptoms of apathy. The increased pattern of activation in LSA-PD, accompanied with lower apathetic symptomatology, might be the initial manifestation of compensatory mechanisms for dysfunctional limbic pathway. The same pattern of hyperconnectivity has been found in other pathologies and the implication of these abnormalities as a cross-disease model for initial apathy symptomatology is further discussed.

Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?

Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.

Distinct alterations in Parkinson's medication-state and disease-state connectivity

Altered brain connectivity has been described in people with Parkinson's disease and in response to dopaminergic medications. However, it is unclear whether dopaminergic medications primarily 'normalize' disease related connectivity changes or if they induce unique alterations in brain connectivity. Further, it is unclear how these disease- and medication-associated changes in brain connectivity relate differently to specific motor manifestations of disease, such as bradykinesia/rigidity and tremor. In this study, we applied a novel covariance projection approach in combination with a bootstrapped permutation test to resting state functional MRI data from 57 Parkinson's disease and 20 healthy control participants to determine the Parkinson's medication-state and disease-state connectivity changes associated with different motor manifestations of disease. First, we identified brain connections that best classified Parkinson's disease ON versus OFF dopamine and Parkinson's disease versus healthy controls, achieving 96.9 ± 5.9% and 72.7 ± 12.4% classification accuracy, respectively. Second, we investigated the connections that significantly contribute to the classifications. We found that the connections greater in Parkinson's disease OFF compared to ON dopamine are primarily between motor (cerebellum and putamen) and posterior cortical regions, such as the posterior cingulate cortex. By contrast, connections that are greater in ON compared to OFF dopamine are between the right and left medial prefrontal cortex. We also identified the connections that are greater in healthy control compared to Parkinson's disease and found the most significant connections are associated with primary motor regions, such as the striatum and the supplementary motor area. Notably, these are different connections than those identified in Parkinson's disease OFF compared to ON. Third, we determined which of the Parkinson's medication-state and disease-state connections are associated with the severity of different motor symptoms. We found two connections correlate with both bradykinesia/rigidity severity and tremor severity, whereas four connections correlate with only bradykinesia/rigidity severity, and five connections correlate with only tremor severity. Connections that correlate with only tremor severity are anchored by the cerebellum and the supplemental motor area, but only those connections that include the supplemental motor area predict dopaminergic improvement in tremor. Our results suggest that dopaminergic medications do not simply 'normalize' abnormal brain connectivity associated with Parkinson's disease, but rather dopamine drives distinct connectivity changes, only some of which are associated with improved motor symptoms. In addition, the dissociation between of connections related to severity of bradykinesia/rigidity versus tremor highlights the distinct abnormalities in brain circuitry underlying these specific motor symptoms.

Brain Magnetic Resonance Imaging (MRI) as a Potential Biomarker for Parkinson's Disease (PD)

Magnetic resonance imaging (MRI) has the potential to serve as a biomarker for Parkinson's disease (PD). However, the type or types of biomarker it could provide remain to be determined. At this time there is not sufficient sensitivity or specificity for MRI to serve as an early diagnostic biomarker, i.e., it is unproven in its ability to determine if a single individual is normal, has mild PD, or has some other forms of degenerative parkinsonism. However there is accumulating evidence that MRI may be useful in staging and monitoring disease progression (staging biomarker), and also possibly as a means to monitor pathophysiological aspects of disease and associated response to treatments, i.e., theranostic marker. As there are increasing numbers of manuscripts that are dedicated to diffusion- and neuromelanin-based imaging methods, this review will focus on these topics cursorily and will delve into pharmacodynamic imaging as a means to get at theranostic aspects of PD.

Cognition in Parkinson's Disease

Cognitive decline is now recognized as a common nonmotor symptom of Parkinson's disease, and it has been the subject of increasing research in recent decades. Cognitive deficits in Parkinson's disease can be distinguished as dopaminergically mediated executive dysfunction seen in the milder stages vs a global dementia syndrome that can occur with disease progression. The neural basis of these deficits has been explored from the perspective of multimodal imaging techniques to measure the structural, functional, and metabolic correlates of cognitive decline in Parkinson's disease. Increasingly, changes in neurotransmitter systems beyond dopamine, including the noradrenergic, serotonergic, and cholinergic systems, are being recognized for their contribution to cognitive decline. The impact of certain genetic variations on cognitive function has also been established, including links between cognitive decline and polymorphisms affecting COMT, MAPT, APOE, and GBA genotypes. Although therapeutic options for cognitive decline are still far less established than for motor systems, both pharmacological and nonpharmacological strategies are continuing to develop.

Effects of levodopa on corticostriatal circuits supporting working memory in Parkinson's disease

Working memory dysfunction is common in Parkinson's disease, even in its early stages, but its neural basis is debated. Working memory performance likely reflects a balance between corticostriatal dysfunction and compensatory mechanisms. We tested this hypothesis by examining working memory performance with a letter n-back task in 19 patients with mild-moderate Parkinson's disease and 20 demographically matched healthy controls. Parkinson's disease patients were tested after an overnight washout of their usual dopamine replacement therapy, and again after a standard dose of levodopa. FMRI was used to assess task-related activation and resting state functional connectivity; changes in BOLD signal were related to performance to disentangle pathological and compensatory processes. Parkinson's disease patients off dopamine replacement therapy displayed significantly reduced spatial extent of task-related activation in left prefrontal and bilateral parietal cortex, and poorer working memory performance, compared to controls. Amongst the Parkinson's disease patients off dopamine replacement therapy, relatively better performance was associated with greater activation of right dorsolateral prefrontal cortex compared to controls, consistent with compensatory right hemisphere recruitment. Administration of levodopa remediated the working memory deficit in the Parkinson's disease group, and resulted in a different pattern of performance-correlated activity, with a shift to greater left ventrolateral prefrontal cortex activation in patients on, compared to off dopamine replacement therapy. Levodopa also significantly increased resting-state functional connectivity between caudate and right parietal cortex (within the right fronto-parietal attentional network). The strength of this connectivity contributed to better performance in patients and controls, suggesting a general compensatory mechanism. These findings argue that Parkinson's disease patients can recruit additional neural resources, here, the right fronto-parietal network, to optimize working memory performance despite impaired corticostriatal function. Levodopa seems to both boost engagement of a task-specific prefrontal region, and strengthen a putative compensatory caudate-cortical network to support this executive function.

Distinct Role of Striatal Functional Connectivity and Dopaminergic Loss in Parkinson's Symptoms

Degeneration of dopaminergic neurons is a hallmark of Parkinson's disease. However, its link to Parkinson's disease symptoms remains unclear. Striatal resting state functional connectivity differentiates between Parkinson's disease patients and healthy controls and might be a potential mediator of the effects of striatal dopaminergic degeneration onto Parkinson's disease symptoms. Here, we evaluated the relationship between dopaminergic deficits, striatal functional connectivity (SFC) at rest and different Parkinson's disease clinical symptoms in the largest currently established cohort of de novo Parkinson's disease patients. We show that SFC is an independent predictor of symptom severity in Parkinson's disease in addition to striatal dopaminergic deficits. Furthermore, we find that distinct SFC networks are associated with symptoms reflecting the ability to perform daily routine automatized motor tasks and clinician-rated Parkinson's disease motor symptoms. We find that reduced SFC is a major and independent predictor of Parkinson's disease symptoms going beyond the mere reflection of striatal dopaminergic input loss. These findings indicate the high value of SFC as a clinically relevant biomarker in Parkinson's disease.

Dopamine depletion impairs gait automaticity by altering cortico-striatal and cerebellar processing in Parkinson's disease

Impairments in motor automaticity cause patients with Parkinson's disease to rely on attentional resources during gait, resulting in greater motor variability and a higher risk of falls. Although dopaminergic circuitry is known to play an important role in motor automaticity, little evidence exists on the neural mechanisms underlying the breakdown of locomotor automaticity in Parkinson's disease. This impedes clinical management and is in great part due to mobility restrictions that accompany the neuroimaging of gait. This study therefore utilized a virtual reality gait paradigm in conjunction with functional MRI to investigate the role of dopaminergic medication on lower limb motor automaticity in 23 patients with Parkinson's disease that were measured both on and off dopaminergic medication. Participants either operated foot pedals to navigate a corridor ('walk' condition) or watched the screen while a researcher operated the paradigm from outside the scanner ('watch' condition), a setting that controlled for the non-motor aspects of the task. Step time variability during walk was used as a surrogate measure for motor automaticity (where higher variability equates to reduced automaticity), and patients demonstrated a predicted increase in step time variability during the dopaminergic "off" state. During the "off" state, subjects showed an increased blood oxygen level-dependent response in the bilateral orbitofrontal cortices (walk>watch). To estimate step time variability, a parametric modulator was designed that allowed for the examination of brain regions associated with periods of decreased automaticity. This analysis showed that patients on dopaminergic medication recruited the cerebellum during periods of increasing variability, whereas patients off medication instead relied upon cortical regions implicated in cognitive control. Finally, a task-based functional connectivity analysis was conducted to examine the manner in which dopamine modulates large-scale network interactions during gait. A main effect of medication was found for functional connectivity within an attentional motor network and a significant condition by medication interaction for functional connectivity was found within the striatum. Furthermore, functional connectivity within the striatum correlated strongly with increasing step time variability during walk in the off state (r=0.616, p=0.002), but not in the on state (r=-0.233, p=0.284). Post-hoc analyses revealed that functional connectivity in the dopamine depleted state within an orbitofrontal-striatal limbic circuit was correlated with worse step time variability (r=0.653, p<0.001). Overall, this study demonstrates that dopamine ameliorates gait automaticity in Parkinson's disease by altering striatal, limbic and cerebellar processing, thereby informing future therapeutic avenues for gait and falls prevention.

Disrupted functional connectivity of striatal sub-regions in Bell's palsy patients

The striatum plays an important role in controlling motor function in humans, and its degeneration has the ability to cause severe motor disorders. More specifically, previous studies have demonstrated a disruption in the connectivity of the cortico-striatal loop in patients suffering from motor disorders caused by dopamine dysregulation, such as Parkinson's disease. However, little is known about striatal functional connectivity in patients with motor dysfunction not caused by dopamine dysregulation. In this study, we used early-state Bell's palsy (BP) patients (within 14 days of onset) to investigate how functional connectivity between the striatum and motor cortex is affected by peripheral nerve injury in which the dopamine system remains fully functional. We found a significant increase in the connectivity between the contralateral putamen, and the ipsilateral primary sensory (S1) and motor cortex (M1) in BP patients compared to healthy controls. We also found increased connectivity between the ventral striatum and supplementary motor area (SMA), and the dorsal caudate and medial prefrontal lobe in BP patients compared to healthy controls. Our results demonstrate that the entirety of the striatum is affected following acute peripheral nerve injury, and suggests that this disrupted striatal functional connectivity may reflect a compensatory mechanism for the sensory-motor mismatch caused by BP.

The study of brain functional connectivity in Parkinson's disease

Parkinson’s disease (PD) is a neurodegenerative disorder primarily affecting the aging population. The neurophysiological mechanisms underlying parkinsonian symptoms remain unclear. PD affects extensive neural networks and a more thorough understanding of network disruption will help bridge the gap between known pathological changes and observed clinical presentations in PD. Development of neuroimaging techniques, especially functional magnetic resonance imaging, allows for detection of the functional connectivity of neural networks in patients with PD. This review aims to provide an overview of current research involving functional network disruption in PD relating to motor and non-motor symptoms. Investigations into functional network connectivity will further our understanding of the mechanisms underlying the effectiveness of clinical interventions, such as levodopa and deep brain stimulation treatment. In addition, identification of PD-specific neural network patterns has the potential to aid in the development of a definitive diagnosis of PD.

Structural Brain Alterations in Motor Subtypes of Parkinson's Disease: Evidence from Probabilistic Tractography and Shape Analysis

BACKGROUND AND OBJECTIVES

The postural instability and gait disorder (PIGD) and tremor dominant (TD) subtypes of Parkinson's disease (PD) show different patterns of alterations in functional connectivity (FC) between specific brain regions. This study aimed to investigate the relation between symptomatic heterogeneity in PD and structural alterations underlying these FC changes.

METHODS

68 PD patients classified as PIGD (n = 41) or TD (n = 19) and 19 age-matched controls underwent Magnetic Resonance Imaging (MRI). Diffusion-weighted images were used to assess fractional anisotropy (FA) and mean diffusivity (MD) at the whole-brain level using tract-based spatial statistics (TBSS). In addition, structural connectivity was assessed between regions that previously showed altered FC using probabilistic tractography. Anatomical images were used to determine shape and volume of the putamen, caudate and pallidum.

RESULTS

TBSS revealed widespread FA reductions in PIGD compared to controls involving the superior longitudinal fasciculi and corpus callosum. No such differences were found in TD. Both PD subgroups had increased MD compared to controls in tracts connecting the left caudate with the bilateral ventral putamen. TD patients additionally showed increased MD compared to PIGD and controls in tracts connecting the right inferior parietal lobule with the right premotor and primary motor cortex, which previously showed altered FC. We also found grey matter atrophy in the rostrodorsal head of the caudate in PIGD compared to controls.

CONCLUSION

Microstructural changes in white matter tracts, particularly in those connecting striatal sub-areas, partly underlie FC alterations in PD subtypes. Caudate shape alterations further implicate the striatum in PIGD pathophysiology.

Functional reversal of (-)-Stepholidine analogues by replacement of benzazepine substructure using the ring-expansion strategy

(-)-Stepholidine is an active ingredient of the Chinese herb Stephania and naturally occurring tetrahydroprotoberberine alkaloid with mixed dopamine receptor D1 agonistic and dopamine receptor D2 antagonistic activities. In this work, a series of novel hexahydrobenzo[4,5]azepino [2,1-a]isoquinolines were designed and synthesized as ring-expanded analogues of (-)-Stepholidine. Initial pharmacological assays demonstrated that a benzazepine replacement was associated with significant increase in selectivity and functional reversal at dopamine receptor D1 . Compound-(-)-15e (Ki  = 5.32 ± 0.01 nm) is more potent than (-)-Stepholidine (Ki  = 13 nm) and was identified as a selective dopamine receptor D1 antagonist (IC50  = 0.14 μm). Moreover, molecular modeling suggested that (-)-15e might exert its dopamine receptor D1 antagonistic activities through interacting with the transmembrane helix 7 of dopamine receptor D1 .