The default mode network integrity in patients with Parkinson's disease is levodopa equivalent dose-dependent

The neurophysiological brain-fingerprint of Parkinson's disease

BACKGROUND

Research in healthy young adults shows that characteristic patterns of brain activity define individual "brain-fingerprints" that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson's disease (PD).

METHODS

We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s.

FINDINGS

The arrhythmic spectral components of cortical activity in patients with Parkinson's disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson's brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson's symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology.

INTERPRETATION

The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson's disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets.

FUNDING

Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).

Resting-state networks and their relationship with MoCA performance in PD patients

Although mild cognitive impairment is a common non-motor symptom experienced by individuals with Parkinson's Disease, the changes in intrinsic resting-state networks associated with its onset in Parkinson's remain underexamined. To address the issue, our study sought to examine resting-state network alterations and their association with total performance in the Montreal Cognitive Assessment and its cognitive domains in Parkinson's by means of functional magnetic resonance imaging of 29 Parkinson's patients with normal cognition, 25 Parkinson's patients with mild cognitive impairment, and 13 healthy controls. To contrast the Parkinson's groups with each other and the controls, the images were used to estimate the Z-score coefficient between the regions of interest from the default mode network, the salience network and the central executive network. Our first finding was that default mode and salience network connectivity decreased significantly in Parkinson's patients regardless of their cognitive status. Additionally, default mode network nodes had a negative and salience network nodes a positive correlation with the global assessment in Parkinson's with normal cognition; this inverse relationship of both networks to total score was not found in the group with cognitive impairment. Finally, a positive correlation was found between executive scores and anterior and posterior cortical network connectivity and, in the group with cognitive impairment, between language scores and salience network connectivity. Our results suggest that specific resting-state networks of Parkinson's patients with cognitive impairment differ from those of Parkinson's patients with normal cognition, supporting the evidence that cognitive impairment in Parkinson's Disease displays a differentiated neurodegenerative pattern.

Striato-cortical functional connectivity changes in mild cognitive impairment with Lewy bodies

BACKGROUND

Functional connectivity changes in clinically overt neurodegenerative diseases such as dementia with Lewy bodies have been described, but studies on connectivity changes in the pre-dementia phase are scarce.

OBJECTIVES

We concentrated on evaluating striato-cortical functional connectivity differences between patients with Mild Cognitive Impairment with Lewy bodies and healthy controls and on assessing the relation to cognition.

METHODS

Altogether, we enrolled 77 participants (47 patients, of which 35 met all the inclusion criteria for the final analysis, and 30 age- and gender-matched healthy controls, of which 28 met all the inclusion criteria for the final analysis) to study the seed-based connectivity of the dorsal, middle, and ventral striatum. We assessed correlations between functional connectivity in the regions of between-group differences and neuropsychological scores of interest (visuospatial and executive domains z-scores).

RESULTS

Subjects with Mild Cognitive Impairment with Lewy Bodies, as compared to healthy controls, showed increased connectivity from the dorsal part of the striatum particularly to the bilateral anterior part of the temporal cortex with an association with executive functions.

CONCLUSIONS

We were able to capture early abnormal connectivity within cholinergic and noradrenergic pathways that correlated with cognitive functions known to be linked to cholinergic/noradrenergic deficits. The knowledge of specific alterations may improve our understanding of early neural changes in pre-dementia stages and enhance research of disease modifying therapy.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

The neurophysiological brain-fingerprint of Parkinson's disease

In this study, we investigate the clinical potential of brain-fingerprints derived from electrophysiological brain activity for diagnostics and progression monitoring of Parkinson's disease (PD). We obtained brain-fingerprints from PD patients and age-matched healthy controls using short, task-free magnetoencephalographic recordings. The rhythmic components of the individual brain-fingerprint distinguished between patients and healthy participants with approximately 90% accuracy. The most prominent cortical features of the Parkinson's brain-fingerprint mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also show that Parkinson's disease stages can be decoded directly from cortical neurophysiological activity. Additionally, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. We further demonstrate that the arrhythmic components of cortical activity are more variable over short periods of time in patients with Parkinson's disease than in healthy controls, making individual differentiation between patients based on these features more challenging and explaining previous negative published results. Overall, we outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and clinical staging of Parkinson's disease. For this reason, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification and to the improved identification and testing of therapeutic neurostimulation targets.

Normalization effect of dopamine replacement therapy on brain functional connectome in Parkinson's disease

Dopamine replacement therapy (DRT) represents the standard treatment for Parkinson's disease (PD), however, instant and long-term medication influence on patients' brain function have not been delineated. Here, a total of 97 drug-naïve patients, 43 patients under long-term DRT, and 94 normal control (NC) were, retrospectively, enrolled. Resting-state functional magnetic resonance imaging data and motor symptom assessments were conducted before and after levodopa challenge test. Whole-brain functional connectivity (FC) matrices were constructed. Network-based statistics were performed to assess FC difference between drug-naïve patients and NC, and these significant FCs were defined as disease-related connectomes, which were used for further statistical analyses. Patients showed better motor performances after both long-term DRT and levodopa challenge test. Two disease-related connectomes were observed with distinct patterns. The FC of the increased connectome, which mainly consisted of the motor, visual, subcortical, and cerebellum networks, was higher in drug-naïve patients than that in NC and was normalized after long-term DRT (p-value <.050). The decreased connectome was mainly composed of the motor, medial frontal, and salience networks and showed significantly lower FC in all patients than NC (p-value <.050). The global FC of both increased and decreased connectome was significantly enhanced after levodopa challenge test (q-value <0.050, false discovery rate-corrected). The global FC of increased connectome in ON-state was negatively associated with levodopa equivalency dose (r = -.496, q-value = 0.007). Higher global FC of the decreased connectome was related to better motor performances (r = -.310, q-value = 0.022). Our findings provided insights into brain functional alterations under dopaminergic medication and its benefit on motor symptoms.

Impaired Brain Information Transmission Efficiency and Flexibility in Parkinson’s Disease and Rapid Eye Movement Sleep Behavior Disorder: Evidence from Functional Connectivity and Functional Dynamics

Parkinson’s disease (PD) is a common neurodegenerative disorder. Rapid eye movement sleep behavior disorder (RBD) is one of the prodromal symptoms of PD. Studies have shown that brain information transmission is affected in PD patients. Consequently, we hypothesized that brain information transmission is impaired in RBD and PD. To prove our hypothesis, we performed functional connectivity (FC) and functional dynamics analysis of three aspects—based on the whole brain, within the resting-state network (RSN), and the interaction between RSNs—using normal control (NC) (n = 21), RBD (n = 24), and PD (n = 45) resting-state functional magnetic resonance imaging (rs-fMRI) data sets. Furthermore, we tested the explanatory power of FC and functional dynamics for the clinical features. Our results found that the global functional dynamics and FC of RBD and PD were impaired. Within RSN, the impairment concentrated in the visual network (VIS) and sensorimotor network (SMN), and the impaired degree of SMN in RBD was higher than that in PD. On the interaction between RSNs, RBD showed a widespread decrease, and PD showed a focal decrease which concentrated in SMN and VIS. Finally, we proved FC and functional dynamics were related to clinical features. These differences confirmed that brain information transmission efficiency and flexibility are impaired in RBD and PD, and these impairments are associated with the clinical features of patients.

The Effects of Cardiorespiratory and Motor Skill Fitness on Intrinsic Functional Connectivity of Neural Networks in Individuals with Parkinson's Disease

Background:

Studies in aging older adults have shown the positive association between cognition and exercise related fitness, particularly cardiorespiratory fitness. These reports have also demonstrated the association of high cardiorespiratory fitness, as well as other types of fitness, on the reversal of age-related decline in neural network connectivity, highlighting the potential role of fitness on age- and disease-related brain changes. While the clinical benefits of exercise are well-documented in Parkinson’s disease (PD), the extent to which cardiorespiratory fitness (assessed by estimated VO_2max testing) or motor skill fitness (assessed by the Physical Performance Test (PPT)) affects neural network connectivity in PD remains to be investigated. The purpose of this study was to explore the hypothesis that higher fitness level is associated with an increase in the intrinsic network connectivity of cognitive networks commonly affected in PD.

Methods:

In this cross-sectional resting state fMRI, we used a multivariate statistical approach based on high-dimensional independent component analysis (ICA) to investigate the association between two independent fitness metrics (estimated VO_2max and PPT) and resting state network connectivity.

Results:

We found that increased estimated VO_2max was associated with increased within network connectivity in cognitive networks known to be impaired in PD, including those sub-serving memory and executive function. There was a similar trend for high levels of PPT to be associated with increased within network connectivity in distinct resting state networks. The between functional network connectivity analysis revealed that cardiorespiratory fitness was associated with increased functional connectivity between somatosensory motor network and several cognitive networks sub-serving memory, attention, and executive function.

Conclusion:

This study provides important empirical data supporting the potential association between two forms of fitness and multiple resting state networks impacting PD cognition. Linking fitness to circuit specific modulation of resting state network connectivity will help establish a neural basis for the positive effects of fitness and specific exercise modalities and provide a foundation to identify underlying mechanisms to promote repair.

Neuroimaging alterations in dementia with Lewy bodies and neuroimaging differences between dementia with Lewy bodies and Alzheimer's disease: An activation likelihood estimation meta-analysis

Aims

The aim of this study was to identify brain regions with local, structural, and functional abnormalities in dementia with Lewy bodies (DLB) and uncover the differences between DLB and Alzheimer's disease (AD). The neural networks involved in the identified abnormal brain regions were further described.

Methods

PubMed, Web of Science, OVID, Science Direct, and Cochrane Library databases were used to identify neuroimaging studies that included DLB versus healthy controls (HCs) or DLB versus AD. The coordinate‐based meta‐analysis and functional meta‐analytic connectivity modeling were performed using the activation likelihood estimation algorithm.

Results

Eleven structural studies and fourteen functional studies were included in this quantitative meta‐analysis. DLB patients showed a dysfunction in the bilateral inferior parietal lobule and right lingual gyrus compared with HC patients. DLB patients showed a relative preservation of the medial temporal lobe and a tendency of lower metabolism in the right lingual gyrus compared with AD. The frontal‐parietal, salience, and visual networks were all abnormally co‐activated in DLB, but the default mode network remained normally co‐activated compared with AD.

Conclusions

The convergence of local brain regions and co‐activation neural networks might be potential specific imaging markers in the diagnosis of DLB. This might provide a pathway for the neural regulation in DLB patients, and it might contribute to the development of specific interventions for DLB and AD.

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.

Neural networks associated with quality of life in patients with Parkinson's disease

INTRODUCTION

The neural underpinnings of health-related quality of life in Parkinson's disease remain unclear. This study was conducted to unravel which motor and non-motor symptoms in Parkinson's disease influence health-related quality of life and reveal neural networks most likely linked to it.

METHODS

Comprehensive clinical assessments were conducted for 247 Parkinson's disease patients and image analyses were performed for 181 patients. Clinical scores commonly used to assess various symptoms related to health-related quality of life were investigated. Factor and resting-state functional magnetic resonance imaging analyses were reviewed to reveal health-related quality of life-associated brain networks.

RESULTS

The Spearman's rank correlation coefficient for the Parkinson's disease Questionnaire-39 summary index was high in the Activities-specific Balance Confidence Scale, Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part 2, Freezing of Gait Questionnaire, and Self-reported Autonomic Symptoms in Parkinson's disease. Multiple regression and Random Forest regression analyses indicated that health-related quality of life-associated factors were Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale part 1, Depression Rating Scales, and the above-mentioned scales. The resting-state functional magnetic resonance imaging analysis revealed decreased functional connectivity between the anterior cingulate cortex and right temporo-parietal junction as health-related quality of life worsened.

CONCLUSION

Fear of falling, daily living activities, gait freezing, and autonomic dysfunction have notable effects on health-related quality of life in Parkinson's disease. Brain networks consisting of the anterior cingulate cortex and temporo-parietal junction may be associated with the emotion-related and social factors of health-related quality of life in Parkinson's disease.

The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach

Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.

Global Functional Network Connectivity Disturbances in Parkinson's Disease with Mild Cognitive Impairment by Resting-State Functional MRI

Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson's disease (PD) with mild cognitive impairment (MCI) is a focus in resting-state functional MRI (rs-fMRI) studies. This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels: functional connectivity analysis within resting state networks (RSNs) and functional network connectivity (FNC) analysis. Using group independent component analysis (ICA) on rs-fMRI data acquired from 30 participants (14 healthy controls and 16 PD patients with MCI), 16 RSNs were identified, and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups. Compared to controls, patients with PD showed decreased functional connectivity within putamen network, thalamus network, cerebellar network, attention network, and self-referential network, and increased functional connectivity within execution network. Globally disturbed, mostly increased functional connectivity of FNC was observed in PD group, and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs. Cerebellar network showed decreased functional connectivity with caudate network, insular network, and self-referential network. In general, decreased functional connectivity within RSNs and globally disturbed, mostly increased functional connectivity of FNC may be characteristics of PD. Increased functional connectivity within execution network may be an early marker of PD. The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN, contributing to the understanding of the neural mechanism of PD.

Are there any differential responses to concussive injury in civilian versus athletic populations: a neuroimaging study

Accurate identification and classification of patients suffering from mild traumatic brain injury (mTBI) is a significant challenge faced by clinicians and researchers. To examine if there are different pathophysiological responses to concussive injury in different populations, evaluated here comparing collegiate athletes versus age-matched non-athletes. Resting-state fMRI data were acquired in the acute phase of concussion from 30 collegiate athletes and from 30 injury and age matched non-athletes. Resting-state functional connectivity measures revealed group differences with reduced connectivity in the anterior cingulate cortex (p < .05) and posterior cingulate cortex (p < 0.05) hubs of the Default Mode Network in the athletes. Given the known positive effects of exercise on brain functional reserves and neural efficiency concept, we expected less pronounced effect of concussion in athletic population. In contrast, there were significant decreases in functional connectivity in athletes that could be a result of previous repetitive subconcussive impacts and history of concussion.

Connectivity Correlates of Anxiety Symptoms in Drug-Naive Parkinson's Disease Patients

BACKGROUND

Anxiety symptoms are common in Parkinson's disease (PD). A link between anxiety and cognitive impairment in PD has been demonstrated.

OBJECTIVES

Using resting-state functional magnetic resonance imaging, we investigated intrinsic brain network connectivity correlates of anxiety symptoms in a cohort of drug-naive, cognitively unimpaired patients with PD.

METHODS

The intrinsic functional brain connectivity of 25 drug-naive, cognitively unimpaired PD patients with anxiety, 25 without anxiety, and 20 matched healthy controls was compared. All patients underwent a detailed behavioral and neuropsychological evaluation. Anxiety presence and severity were assessed using the Parkinson's Disease Anxiety Scale. Single-subject and group-level independent component analyses were used to investigate functional connectivity differences within and between the major resting-state networks.

RESULTS

Decreased connectivity within the default-mode and sensorimotor networks (SMN), increased connectivity within the executive-control network (ECN), and divergent connectivity measures within salience and frontoparietal networks (SN and FPN) were detected in PD patients with anxiety compared with those without anxiety. Moreover, patients with anxiety showed a disrupted inter-network connectivity between SN and SMN, ECN, and FPN. Anxiety severity was correlated with functional abnormalities within these networks.

CONCLUSIONS

Our findings demonstrated that an abnormal intrinsic connectivity within and between the most reported large-scale networks may represent a potential neural correlate of anxiety symptoms in drug-naive PD patients even in the absence of clinically relevant cognitive impairment. We hypothesize that these specific cognitive and limbic network architecture changes may represent a potential biomarker of treatment response in clinical trials. © 2020 International Parkinson and Movement Disorder Society.

Alterations in Degree Centrality and Functional Connectivity in Parkinson's Disease Patients With Freezing of Gait: A Resting-State Functional Magnetic Resonance Imaging Study

Objective

Freezing of gait (FOG) is a common disabling motor symptom in Parkinson's disease (PD), but the potential pathogenic mechanisms are still unclear.

Methods

A total of 22 patients with PD with FOG (PD-FOG), 28 patients with PD without FOG (PD-nFOG), and 33 healthy controls (HCs) were recruited in this study. Degree centrality (DC)-a graph theory-based measurement of global connectivity at the voxel level by measuring the number of instantaneous functional connections between one region and the rest of the brain-can map brain hubs with high sensitivity, specificity, and reproducibility. DC was used to explore alterations in the centrality of PD-FOG correlated with brain node levels. PD-FOG cognitive network dysfunction was further revealed via a seed-based functional connectivity (FC) analysis. In addition, correlation analyses were carried out between clinical symptoms and acquired connectivity measurement.

Results

Compared to the PD-nFOG group, the PD-FOG group showed remarkably increased DC values in the right middle frontal gyrus (RMFG). There were no significant differences in other gray matter regions. Importantly, the clinical severity of FOG was related to the mean DC values in the RMFG. This brain region served as a seed in secondary seed-based FC analysis, and we further found FC changes in the right precuneus, right inferior frontal gyrus, right superior frontal gyrus (SFG), and cerebellum.

Conclusion

Increased RMFG activity and FC network alterations in the middle frontal cortex with the precuneus, inferior, and SFG, and the cerebellum may have great potential in brain dysfunction in PD with FOG.

Connectivity Between Brain Networks Dynamically Reflects Cognitive Status of Parkinson's Disease: A Longitudinal Study

BACKGROUND

Cognitive impairment in Parkinson's disease (PD) is associated with altered connectivity of the resting state networks (RSNs). Longitudinal studies in well cognitively characterized PD subgroups are missing.

OBJECTIVES

To assess changes of the whole-brain connectivity and between-network connectivity (BNC) of large-scale functional networks related to cognition in well characterized PD patients using a longitudinal study design and various analytical methods.

METHODS

We explored the whole-brain connectivity and BNC of the frontoparietal control network (FPCN) and the default mode, dorsal attention, and visual networks in PD with normal cognition (PD-NC, n = 17) and mild cognitive impairment (PD-MCI, n = 22) as compared to 51 healthy controls (HC). We applied regions of interest-based, partial least squares, and graph theory based network analyses. The differences among groups were analyzed at baseline and at the one-year follow-up visit (37 HC, 23 PD all).

RESULTS

The BNC of the FPCN and other RSNs was reduced, and the whole-brain analysis revealed increased characteristic path length and decreased average node strength, clustering coefficient, and global efficiency in PD-NC compared to HC. Values of all measures in PD-MCI were between that of HC and PD-NC. After one year, the BNC was further increased in the PD-all group; no changes were detected in HC. No cognitive domain z-scores deteriorated in either group.

CONCLUSION

As compared to HC, PD-NC patients display a less efficient transfer of information globally and reduced BNC of the visual and frontoparietal control network. The BNC increases with time and MCI status, reflecting compensatory efforts.

The Pharmacology of Visual Hallucinations in Synucleinopathies

Visual hallucinations (VH) are commonly found in the course of synucleinopathies like Parkinson's disease and dementia with Lewy bodies. The incidence of VH in these conditions is so high that the absence of VH in the course of the disease should raise questions about the diagnosis. VH may take the form of early and simple phenomena or appear with late and complex presentations that include hallucinatory production and delusions. VH are an unmet treatment need. The review analyzes the past and recent hypotheses that are related to the underlying mechanisms of VH and then discusses their pharmacological modulation. Recent models for VH have been centered on the role played by the decoupling of the default mode network (DMN) when is released from the control of the fronto-parietal and salience networks. According to the proposed model, the process results in the perception of priors that are stored in the unconscious memory and the uncontrolled emergence of intrinsic narrative produced by the DMN. This DMN activity is triggered by the altered functioning of the thalamus and involves the dysregulated activity of the brain neurotransmitters. Historically, dopamine has been indicated as a major driver for the production of VH in synucleinopathies. In that context, nigrostriatal dysfunctions have been associated with the VH onset. The efficacy of antipsychotic compounds in VH treatment has further supported the notion of major involvement of dopamine in the production of the hallucinatory phenomena. However, more recent studies and growing evidence are also pointing toward an important role played by serotonergic and cholinergic dysfunctions. In that respect, in vivo and post-mortem studies have now proved that serotonergic impairment is often an early event in synucleinopathies. The prominent cholinergic impairment in DLB is also well established. Finally, glutamatergic and gamma aminobutyric acid (GABA)ergic modulations and changes in the overall balance between excitatory and inhibitory signaling are also contributing factors. The review provides an extensive overview of the pharmacology of VH and offers an up to date analysis of treatment options.

Association Between Social Cognition Changes and Resting State Functional Connectivity in Frontotemporal Dementia, Alzheimer's Disease, Parkinson's Disease, and Healthy Controls

OBJECTIVE

To determine the relationship between alterations in resting state functional connectivity and social cognition dysfunction among patients with frontotemporal dementia (FTD), Alzheimer's disease (AD), Parkinson's disease (PD), and healthy controls (HC).

METHODS

Fifty-seven participants (FTD = 10, AD = 18, PD = 19, and HC = 10) underwent structural and functional imaging and completed the Awareness of Social Inference Test-Emotion Evaluation Test (TASIT-EET), Behavioral Inhibition System/Behavioral Activation System (BIS/BAS) scale, Revised Self-Monitoring Scale (RSMS), Interpersonal Reactivity Index (IRI), and Social Norms Questionnaire (SNQ). A multi-variate pattern analysis (MVPA) was carried out to determine activation differences between the groups. The clusters from the MVPA were used as seeds for the ROI-to-voxel analysis. Relationship between social cognition deficits and uncinate integrity was also investigated.

RESULTS

BOLD signal activation differed among the four groups of AD, PD, FTD, and HC in the left inferior temporal gyrus-anterior division [L-ITG (ant)], right central opercular cortex (R-COp), right supramarginal gyrus, posterior division (R-SMG, post), right angular gyrus (R-AG), and R-ITG. The BOLD co-activation of the L-ITG (ant) with bilateral frontal pole (FP) and paracingulate gyrus was positively associated with IRI-perspective taking (PT) (r = 0.38, p = 0.007), SNQ total (r = 0.37, p = 0.009), and TASIT-EET (r = 0.47, p < 0.001).

CONCLUSION

Patients with neurodegenerative diseases showed alterations in connectivity in brain regions important for social cognition compared with HCs. Functional connectivity correlated with performance on social cognition tasks and alterations could be responsible for some of the social cognition deficits observed in all neurodegenerative diseases.

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.

Somatic symptoms disorders in Parkinson's disease are related to default mode and salience network dysfunction

Background

Somatic Symptoms Disorder (SSD) has been shown to have a clinically very high prevalence in Parkinson's Disease (PD) with frequencies ranging from 7.0% to 66.7%, higher than in the general population (10%- 25%).

SSD has been associated with dysfunction in Default Mode and Salience network.

Aim

With the present study we aim to verify by means of resting state functional MRI whether possible specific abnormalities in the activation and functional connectivity of the default mode network (DMN) and salience network in cognitively intact PD patients may be more prominent in PD patients with somatic symptoms (SSD-PD) as compared with patients without SSD (PD).

Methods

Eighteen SSD-PD patients (61% male), 18 PD patients (83% male) and 22 healthy age-matched subjects (59% male) were enrolled in the study and underwent resting state functional MRI.

Results

fractional amplitude of low-frequency fluctuation (fALFF) showed reduced activity in bilateral lateral parietal cortex and in left anterior insula in both SSD-PD and PD compared to control group. Functional connectivity (FC) values in the DMN areas and between DMN and salience network areas were found to be lower in SSD-PD than in control group and PD. No significant correlation was found between fMRI results and demographic and clinical variables, excluding the effect of possible confounders on fMRI results.

The present study, showing reduced activity in bilateral parietal areas and in the left anterior insula as compared to healthy controls, suggests a dysfunction of the DMN and salience network in PD, either with or without SSD.

The FC reduction within DMN areas and between DMN and salience network areas in SSD-PD patients suggests a role of dysfunctional connectivity in the resting state network of patients with SSD.

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Reduced activity in parietal areas and in anterior insula in Parkinson's Disease.

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Functional connectivity is lower in Parkinson's disease with somatic symptoms.

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Somatic Symptoms in PD are related to default mode and salience network alterations.

Hallucinations, somatic-functional disorders of PD-DLB as expressions of thalamic dysfunction

Hallucinations, delusions, and functional neurological manifestations (conversion and somatic symptom disorders) of Parkinson's disease (PD) and dementia with Lewy bodies increase in frequency with disease progression, predict the onset of cognitive decline, and eventually blend with and are concealed by dementia. These symptoms share the absence of reality constraints and can be considered comparable elements of the PD-dementia with Lewy bodies psychosis. We propose that PD-dementia with Lewy bodies psychotic disorders depend on thalamic dysfunction promoting a theta burst mode and subsequent thalamocortical dysrhythmia with focal cortical coherence to theta electroencephalogram rhythms. This theta electroencephalogram activity, also called fast-theta or pre-alpha, has been shown to predict cognitive decline and fluctuations in Parkinson's disease with dementia and dementia with Lewy bodies. These electroencephalogram alterations are now considered a predictive marker for progression to dementia. The resulting thalamocortical dysrhythmia inhibits the frontal attentional network and favors the decoupling of the default mode network. As the default mode network is involved in integration of self-referential information into conscious perception, unconstrained default mode network activity, as revealed by recent imaging studies, leads to random formation of connections that link strong autobiographical correlates to trivial stimuli, thereby producing hallucinations, delusions, and functional neurological disorders. The thalamocortical dysrhythmia default mode network decoupling hypothesis provides the rationale for the design and testing of novel therapeutic pharmacological and nonpharmacological interventions in the context of PD, PD with dementia, and dementia with Lewy bodies. © 2019 International Parkinson and Movement Disorder Society.

L-Dopa Modulation of Brain Connectivity in Parkinson's Disease Patients: A Pilot EEG-fMRI Study

Studies of functional neurosurgery and electroencephalography in Parkinson's disease have demonstrated abnormally synchronous activity between basal ganglia and motor cortex. Functional neuroimaging studies investigated brain dysfunction during motor task or resting state and primarily have shown altered patterns of activation and connectivity for motor areas. L-dopa administration relatively normalized these functional alterations. The aim of this pilot study was to examine the effects of L-dopa administration on functional connectivity in early-stage PD, as revealed by simultaneous recording of functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) data. Six patients with diagnosis of probable PD underwent EEG-fMRI acquisitions (1.5 T MR scanner and 64-channel cap) before and immediately after the intake of L-dopa. Regions of interest in the primary motor and sensorimotor regions were used for resting state fMRI analysis. From the EEG data, weighted partial directed coherence was computed in the inverse space after the removal of gradient and cardioballistic artifacts. fMRI results showed that the intake of L-dopa increased functional connectivity within the sensorimotor network, and between motor areas and both attention and default mode networks. EEG connectivity among regions of the motor network did not change significantly, while regions of the default mode network showed a strong tendency to increase their outflow toward the rest of the brain. This pilot study provided a first insight into the potentiality of simultaneous EEG-fMRI acquisitions in PD patients, showing for both techniques the analogous direction of increased connectivity after L-dopa intake, mainly involving motor, dorsal attention and default mode networks.

Influence of analytic techniques on comparing DTI-derived measurements in early stage Parkinson's disease

Diffusion tensor imaging (DTI) studies in early Parkinson's disease (PD) to understand pathologic changes in white matter (WM) organization are variable in their findings. Evaluation of different analytic techniques frequently employed to understand the DTI-derived change in WM organization in a multisite, well-characterized, early stage PD cohort should aid the identification of the most robust analytic techniques to be used to investigate WM pathology in this disease, an important unmet need in the field. Thus, region of interest (ROI)-based analysis, voxel-based morphometry (VBM) analysis with varying spatial smoothing, and the two most widely used skeletonwise approaches (tract-based spatial statistics, TBSS, and tensor-based registration, DTI-TK) were evaluated in a DTI dataset of early PD and Healthy Controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) cohort. Statistical tests on the DTI-derived metrics were conducted using a nonparametric approach from this cohort of early PD, after rigorously controlling for motion and signal artifacts during DTI scan which are frequent confounds in this disease population. Both TBSS and DTI-TK revealed a significantly negative correlation of fractional anisotropy (FA) with disease duration. However, only DTI-TK revealed radial diffusivity (RD) to be driving this FA correlation with disease duration. HC had a significantly positive correlation of MD with cumulative DaT score in the right middle-frontal cortex after a minimum smoothing level (at least 13mm) was attained. The present study found that scalar DTI-derived measures such as FA, MD, and RD should be used as imaging biomarkers with caution in early PD as the conclusions derived from them are heavily dependent on the choice of the analysis used. This study further demonstrated DTI-TK may be used to understand changes in DTI-derived measures with disease progression as it was found to be more accurate than TBSS. In addition, no singular region was identified that could explain both disease duration and severity in early PD. The results of this study should help standardize the utilization of DTI-derived measures in PD in an effort to improve comparability across studies and time, and to minimize variability in reported results due to variation in techniques.

Neural correlates of early cognitive dysfunction in Parkinson's disease

OBJECTIVE

Dementia is a common and feared aspect of Parkinson's disease but there are no robust predictors of cognitive outcome. Visuoperceptual deficits are linked to risk of dementia in Parkinson's disease but whether they predict cognitive change is not known, and the neural substrates of visuoperceptual dysfunction in Parkinson's have not yet been identified.

METHODS

We compared patients with Parkinson's disease and unaffected controls who underwent BOLD fMRI while performing our previously validated visuoperceptual task and tested how functional connectivity between task-specific regions and the rest of the brain differed between patients who performed well and poorly in the task.

RESULTS

We show that task performance at baseline predicts change in cognition in Parkinson's disease after 1 year. Our task-based fMRI study showed that the performance in this task is associated with activity in the posterior cingulate cortex/precuneus. We found that functional connectivity between this region and dorsomedial prefrontal cortex was reduced in poor performers compared with good performers of this task.

INTERPRETATION

Our findings suggest that functional connectivity is reduced between posterior and anterior hubs of the default mode network in Parkinson's patients who are likely to progress to worsening cognitive dysfunction. Our work implicates posterior default mode nodes and their connections as key brain regions in early stages of dementia in Parkinson's disease.

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

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

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

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Akinesia should be disentangled from bradykinesia and hypokinesia.

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

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Future neuroimaging studies should probe more specific neurocognitive processes.

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

Imaging Markers of Progression in Parkinson's Disease

Background

Parkinson's disease (PD) is the second-most common neurodegenerative disorder after Alzheimer's disease; however, to date, there is no approved treatment that stops or slows down disease progression. Over the past decades, neuroimaging studies, including molecular imaging and MRI are trying to provide insights into the mechanisms underlying PD.

Methods

This work utilized a literature review.

Results

It is now becoming clear that these imaging modalities can provide biomarkers that can objectively detect brain changes related to PD and monitor these changes as the disease progresses, and these biomarkers are required to establish a breakthrough in neuroprotective or disease-modifying therapeutics.

Conclusions

Here, we provide a review of recent observations deriving from PET, single-positron emission tomography, and MRI studies exploring PD and other parkinsonian disorders.

Resting-state network connectivity in cognitively unimpaired drug-naïve patients with rigidity-dominant Parkinson's disease

BACKGROUND

Parkinson's disease (PD) could be classified into akinetic-rigidity (PD_AR), tremor-dominant (PD_TD) and mixed subtypes. PD_AR patients are more prone to develop cognitive deficits. The default mode network (DMN), fronto-parietal network (FPN) and dorsal attention network (DAN) play important roles in cognitive processing. Our aim was to evaluate changes in connectivity patterns of the DMN, and its interrelation with the FPN and DAN in cognitively unimpaired drug-naïve PD_AR patients.

METHOD

Resting-state functional MRI (rs-fMRI) data was collected in 20 cognitively unimpaired early-stage drug-naïve PD_AR patients and 20 age-, gender- and cognition- matched healthy controls (HCs). Group-level independent component analysis (ICA) was used to investigate changes in functional connectivity (FC) within the DMN between PD_AR and HCs groups, and relationships between the DMN and FPN/DAN were evaluated by seed-based approach.

RESULTS

In PD_AR patients, a significantly decreased FC, as compared with HCs, was observed in the left inferior parietal lobule (IPL) within the DMN. And the left IPL had a reduced FC with the left anterior cingulate cortex (ACC), left superior frontal gyrus (SFG), and left precuneus. However, no differences were detected in the FC between the left IPL and FPN/DAN. In addition, cognitive scores on the brief visuospatial memory test revised (BVMT-R), representing for cognitive memory domain, were positively correlated with the FC of the left IPL with bilateral SFG.

CONCLUSIONS

Our study mainly revealed altered within-DMN connectivity in cognitively unimpaired PD_AR patients, which could provide further insights into the mechanism underlying cognitive decline evolution in the PD subtype.

Amnestic mild cognitive impairment individuals with dissimilar pathologic origins show common regional vulnerability in the default mode network

INTRODUCTION

Alzheimer's and Parkinson's disease (AD and PD) are distinct disorders but share similar biomarker profiles. The regions of the default mode network are implicated in these diseases and are associated with amnestic symptoms. The role of apolipoprotein-ε4 (APOE-ε4), which is associated with cognitive function, is unclear in PD.

METHODS

In this work, we evaluated cortical thickness of default mode network regions that are likely affected in both early AD and PD individuals, that is, with amnestic mild cognitive impairment. We identified the prevalence of APOE-ε4 and evaluated its association with cortical atrophy.

RESULTS

We observed significant parahippocampal atrophy and hippocampal atrophy rates in amnestic mild cognitive impairment subjects, regardless of disease origins (AD or PD). Similarly, mild cognitive impairment ε4 carriers showed significant precuneal atrophy compared with noncarriers.

DISCUSSION

This work supports that converging changes to default mode network regions, especially the temporal lobe and precuneus, are shared in AD and PD.

Can neuroimaging predict dementia in Parkinson's disease?

Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.

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.

High-Intensity Exercise Acutely Increases Substantia Nigra and Prefrontal Brain Activity in Parkinson's Disease

Background

Pathologic alterations in resting-state brain activity patterns exist among individuals with Parkinson’s disease (PD). Since physical exercise alters resting-state brain activity in non-PD populations and improves PD symptoms, we assessed the acute effect of exercise on resting-state brain activity in exercise-trained individuals with PD.

Material/Methods

Resting-state functional magnetic resonance imaging (fMRI) was collected twice for 17 PD participants at the conclusion of an exercise intervention. The acute effect of exercise was examined for PD participants using the amplitude of low frequency fluctuation (ALFF) before and after a single bout of exercise. Correlations of clinical variables (i.e., PDQ-39 quality of life and MDS-UPDRS) with ALFF values were examined for the exercise-trained PD participants.

Results

An effect of acute exercise was observed as an increased ALFF signal within the right ventromedial prefrontal cortex (PFC), left ventrolateral PFC, and bilaterally within the substantia nigra (SN). Quality of life was positively correlated with ALFF values within the vmPFC and vlPFC.

Conclusions

Given the role of the SN and PFC in motor and non-motor symptoms in PD, the acute increases in brain activity within these regions, if repeated frequently over time (i.e., exercise training), may serve as a potential mechanism underlying exercise-induced PD-specific clinical benefits.

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

Multiple system atrophy (MSA) and Idiopathic Parkinson's disease (IPD) show overlapping clinical manifestations with different treatment and prognosis. However, the shared and distinct underlying neural substrates are not yet understood, which needs to be explored between MSA and IPD. Resting-state functional magnetic resonance imaging data were collected from 29 MSA patients, 17 IPD patients and 25 healthy controls (HC) and the Amplitude of Low-Frequency Fluctuations (ALFF) was compared. Lower ALFF in bilateral basal ganglion, bilateral ventrolateral prefrontal cortex and right amygdala, as well as higher ALFF in parieto-temporo-occipital cortex and right cerebellum was shared between both patient groups to compare with HC. In contrast to IPD, decreased or increased ALFF in different regions of visual associative cortices and decreased ALFF in right cerebellum were found in MSA group. Our findings suggested shared and distinct spontaneous brain activity abnormalities in striato-thalamo-cortical (STC) loop, default mood network, visual associative cortices and cerebellum were present in MSA and IPD, which may help to explain similar clinical symptoms in both disorders but a more severe illness prognosis in MSA. Further research is needed to better describe the functional role of the cerebellum and visual associative cortices in early stages of MSA and IPD.

Long reaction times are associated with delayed brain activity in lewy body dementia

A significant symptom of Lewy body dementia (LBD) is slow cognitive processing or bradyphrenia. In a previous fMRI task‐based study, we found slower responses in LBD, accompanied by greater deactivation in the default mode network. In this study, we investigated the timing and magnitude of the activations and deactivations with respect to reaction time to determine whether the slower responses in LBD were associated with delayed neuronal activity. Using fMRI, we examined the magnitude and latency of activations and deactivations during an event‐related attention task in 32 patients with LBD and 23 healthy controls using predefined regions of interest. Default mode network deactivations did not significantly differ in their timing between groups or task conditions, while the task‐related activations in the parietal, occipital, frontal, and motor cortex were all significantly later in the LBD group. Repeating the analysis with reaction time as a parametric modulator of activation magnitude produced similar findings, with the reaction time modulator being significant in a number of regions including the default mode network, suggesting that the increased deactivation in LBD is partly explained by slower task completion. Our data suggest that the default mode network deactivation is initiated at the start of the task, and remains deactivated until its end, with the increased magnitude of deactivation in LBD reflecting the more prolonged cognitive processing in these patients. These data add substantially to our understanding of the neural origins of bradyphrenia, which will be essential for determining optimum therapeutic strategies for cognitive impairment in LBD. Hum Brain Mapp 39:633–643, 2018. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Applications of Resting State Functional MR Imaging to Neuropsychiatric Diseases

Resting state studies in neuropsychiatric disorders have already provided much useful information, but the field is regarded as being at a relatively preliminary stage and subject to several design issues that set limits on the overall utility.

Connectivity Changes in Parkinson's Disease

Parkinson's disease (PD) is a chronic and progressive movement disorder of the central nervous system characterized by widespread alterations in several non-motor aspects such as mood, sleep, olfactory, and cognition in addition to motor dysfunctions. Advanced neuroimaging using functional connectivity reconstruction of the human brain has provided a vast knowledge on the pathophysiological mechanisms underlying this disorder, but this, however, does not cover the overall inter-/intra-individual variability of PD phenotypes. The present review is aimed at discussing to what extent the evidence provided by group-based neuroimaging analysis in this field of study (using seed-based, network-based, or graph theory approaches) may be generalized. In particular, we summarized the literature on the application of resting-state functional connectivity studies to explore different neural correlates of motor and non-motor symptoms of PD and the neural mechanisms involved in treatment effects: effects of levodopa or deep brain stimulation. The lesson learnt from one decade of studies provides consistent evidence on the role of the altered communication between the striato-frontal pathways as a marker of PD-related motor degeneration, whereas in the non-motor domain, several missing pieces of a complex puzzle are provided. However, the main target is to present a new era of intelligent neuroimaging applications, where automated multivariate analysis of functional connectivity data may be used for moving from group-level statistical results to personalized predictions in a clinical setting. Although in its relative infancy, the evidence gathered so far suggests a new era of clinical neuroimaging is starting.

Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis

BACKGROUND

Neuroimaging studies help us better understand the pathophysiology and symptoms of Parkinson's disease (PD). In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. Although data have been provided as regards to specific brain areas, a whole brain meta-analysis is still missing.

METHODS

We compiled 39 studies in this meta-analysis: 14 used fractional anisotropy (FA), 1 used mean diffusivity (MD), and 24 used both indicators. These studies comprised 1855 individuals, 1087 with PD and 768 healthy controls. Regions of interest were classified anatomically (subcortical structures; white matter; cortical areas; cerebellum). Our statistical analysis considered the disease effect size (DES) as the main variable; the heterogeneity index (I2) and Pearson's correlations between the DES and co-variables (demographic, clinical and MRI parameters) were also calculated.

RESULTS

Our results showed that FA-DES and MD-DES were able to distinguish between patients and healthy controls. Significant differences, indicating degenerations, were observed within the substantia nigra, the corpus callosum, and the cingulate and temporal cortices. Moreover, some findings (particularly in the corticospinal tract) suggested opposite brain changes associated with PD. In addition, our results demonstrated that MD-DES was particularly sensitive to clinical and MRI parameters, such as the number of DTI directions and the echo time within white matter.

CONCLUSIONS

Despite some limitations, DTI appears as a sensitive method to study PD pathophysiology and severity. The association of DTI with other MRI methods should also be considered and could benefit the study of brain degenerations in PD.

Aberrant Intrinsic Activity and Connectivity in Cognitively Normal Parkinson's Disease

Disturbances in intrinsic activity during resting-state functional MRI (rsfMRI) are common in Parkinson's disease (PD), but have largely been studied in a priori defined subnetworks. The cognitive significance of abnormal intrinsic activity is also poorly understood, as are abnormalities that precede the onset of mild cognitive impairment. To address these limitations, we leveraged three different analytic approaches to identify disturbances in rsfMRI metrics in 31 cognitively normal PD patients (PD-CN) and 30 healthy adults. Subjects were screened for mild cognitive impairment using the Movement Disorders Society Task Force Level II criteria. Whole-brain data-driven analytic approaches first analyzed the amplitude of low-frequency intrinsic fluctuations (ALFF) and regional homogeneity (ReHo), a measure of local connectivity amongst functionally similar regions. We then examined if regional disturbances in these metrics altered functional connectivity with other brain regions. We also investigated if abnormal rsfMRI metrics in PD-CN were related to brain atrophy and executive, visual organization, and episodic memory functioning. The results revealed abnormally increased and decreased ALFF and ReHo in PD-CN patients within the default mode network (posterior cingulate, inferior parietal cortex, parahippocampus, entorhinal cortex), sensorimotor cortex (primary motor, pre/post-central gyrus), basal ganglia (putamen, caudate), and posterior cerebellar lobule VII, which mediates cognition. For default mode network regions, we also observed a compound profile of altered ALFF and ReHo. Most regional disturbances in ALFF and ReHo were associated with strengthened long-range interactions in PD-CN, notably with regions in different networks. Stronger long-range functional connectivity in PD-CN was also partly expanded to connections that were outside the networks of the control group. Abnormally increased activity and functional connectivity appeared to have a pathological, rather than compensatory influence on cognitive abilities tested in this study. Receiver operating curve analyses demonstrated excellent sensitivity (≥90%) of rsfMRI variables in distinguishing patients from controls, but poor accuracy for brain volume and cognitive variables. Altogether these results provide new insights into the topology, cognitive relevance, and sensitivity of aberrant intrinsic activity and connectivity that precedes clinically significant cognitive impairment. Longitudinal studies are needed to determine if these neurocognitive associations presage the development of future mild cognitive impairment or dementia.

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.

Psychosis in parkinsonism: an unorthodox approach

Psychosis in Parkinson's disease (PD) is currently considered as the occurrence of hallucinations and delusions. The historical meaning of the term psychosis was, however, broader, encompassing a disorganization of both consciousness and personality, including behavior abnormalities, such as impulsive overactivity and catatonia, in complete definitions by the International Classification of Diseases-10 (ICD-10) and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Our review is aimed at reminding that complex psychotic symptoms, including impulsive overactivity and somatoform disorders (the last being a recent controversial entity in PD), were carefully described in postencephalitic parkinsonism (PEP), many decades before dopaminergic treatment era, and are now described in other parkinsonisms than PD. Eminent neuropsychiatrists of the past century speculated that studying psychosis in PEP might highlight its mechanisms in other conditions. Yet, functional assessments were unavailable at the time. Therefore, the second part of our article reviews the studies of neural correlates of psychosis in parkinsonisms, by taking into account both theories on the narrative functions of the default mode network (DMN) and hypotheses on DMN modulation.

The role of high-field magnetic resonance imaging in parkinsonian disorders: Pushing the boundaries forward

Historically, magnetic resonance imaging (MRI) has contributed little to the study of Parkinson's disease (PD), but modern MRI approaches have unveiled several complementary markers that are useful for research and clinical applications. Iron- and neuromelanin-sensitive MRI detect qualitative changes in the substantia nigra. Quantitative MRI markers can be derived from diffusion weighted and iron-sensitive imaging or volumetry. Functional brain alterations at rest or during task performance have been captured with functional and arterial spin labeling perfusion MRI. These markers are useful for the diagnosis of PD and atypical parkinsonism, to track disease progression from the premotor stages of these diseases and to better understand the neurobiological basis of clinical deficits. A current research goal using MRI is to generate time-dependent models of the evolution of PD biomarkers that can help understand neurodegeneration and provide reliable markers for therapeutic trials. This article reviews recent advances in MRI biomarker research at high-field (3T) and ultra high field-imaging (7T) in PD and atypical parkinsonism. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Arterial spin labelling detects posterior cortical hypoperfusion in non-demented patients with Parkinson's disease

While previous studies suggested that perfusion abnormalities in Parkinson's disease (PD) are driven by dementia, our study aimed to identify perfusion underpinning of cognitive alteration in non-demented PD patients. Cerebral blood flow was measured using arterial spin labelling (ASL) in 28 PD patients (age 65 years ± 9.9 SD) and 16 age-matched healthy controls (HC) (age 65 years ± 7.8 SD), who also underwent neurological and cognitive testing. The 3D pseudocontinuous ASL and T2-weighted scans from 22 PD patients and 16 HC were analysed in a voxel-wise manner using SPM8 software. Associations between the ASL values in volumes of interest (VOIs) and behavioural and cognitive measures were assessed by Spearman correlation analysis. Posterior cortical hypoperfusion was found in PD patients compared to HC in the left supramarginal gyrus/superior temporal gyrus (VOI1) and left posterior cingulate/precuneus (VOI2). Positive correlation was revealed between perfusion in the VOI2 and Addenbrooke's Cognitive Examination Revised (ACE-R) scores after filtering out the effect of age, levodopa equivalent dose (LED), and total intracranial volume (TIV) (R = 0.51, p = 0.04). Conversely, negative correlation between VOI1 and ACE-R was detected (R = -0.62, p = 0.01) after regressing out the effects of motor impairment, age, LED, and TIV. In non-demented subjects with PD, blood flow abnormalities in precuneus/posterior cingulate were linked to the level of motor impairment and global cognitive performance. Oppositely, perfusion abnormalities in supramarginal gyrus might serve as a compensatory mechanism for brain degeneration and decreased cognitive performance.