Resting State Functional Magnetic Resonance Imaging in Parkinson’s Disease

Aberrant dynamic functional network connectivity in progressive supranuclear palsy

BACKGROUND

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

METHODS

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

RESULTS

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

DISCUSSION

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

Efficacy of Wearable low-intensity pulsed Ultrasound treatment in the Movement disorder in Parkinson's disease (the SWUMP trial): protocol for a single-site, double-blind, randomized controlled trial

BACKGROUND

Parkinson's disease (PD) is a progressive, neurodegenerative illness marked by the loss of dopaminergic neurons, causing motor symptoms. Oral levodopa replacement therapy remains the gold standard in the treatment of PD. It is, nevertheless, a symptomatic treatment. There is currently no effective treatment for PD. Therefore, new therapies for PD are highly desirable. Low-intensity pulsed ultrasound (LIPUS) has been shown to improve behavioral functions in PD animal models. It is a new type of neuromodulation approach that combines noninvasiveness with high spatial precision. The purpose of this study is to establish a new clinical protocol for LIPUS in the treatment of movement disorders in patients with PD.

METHODS

This protocol is a single-site, prospective, double-blind, randomized controlled trial (RCT). Forty-eight participants with clinically confirmed PD will be randomly allocated to one of two groups: LIPUS group or sham group. All of the participants continue to use pharmacological therapy as a fundamental treatment. The primary outcome is the difference between groups from baseline to 4 months in the change in the Unified Parkinson's Disease Rating Scale (UPDRS) motor score (part III). The secondary outcomes include the rating scales such as the Mini-Mental State Examination (MMSE), and other three rating scales, and medical examinations including high-density electroencephalography (hdEEG) and functional magnetic resonance imaging (fMRI). The primary safety outcome will be assessed at 4 months, and adverse events will be recorded.

DISCUSSION

This study represents the clinical investigation into the efficacy of therapeutic LIPUS in the treatment of PD for the first time. If LIPUS is determined to be effective, it could offer a practical and innovative means of expanding the accessibility of ultrasound therapy by using a wearable LIPUS device within a home setting.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2100052093. Registered on 17 October 2021.

Lifestyle Modulators of Neuroplasticity in Parkinson's Disease: Evidence in Human Neuroimaging Studies

Parkinson's disease (PD) is a neurodegenerative disease characterized by both motor and non-motor symptoms. A progressive neuronal loss and the consequent clinical impairment lead to deleterious effects on daily living and quality of life. Despite effective symptomatic therapeutic approaches, no disease-modifying therapies are currently available. Emerging evidence suggests that adopting a healthy lifestyle can improve the quality of life of PD patients. In addition, modulating lifestyle factors can positively affect the microstructural and macrostructural brain levels, corresponding to clinical improvement. Neuroimaging studies may help to identify the mechanisms through which physical exercise, dietary changes, cognitive enrichment, and exposure to substances modulate neuroprotection. All these factors have been associated with a modified risk of developing PD, with attenuation or exacerbation of motor and non-motor symptomatology, and possibly with structural and molecular changes. In the present work, we review the current knowledge on how lifestyle factors influence PD development and progression and the neuroimaging evidence for the brain structural, functional, and molecular changes induced by the adoption of positive or negative lifestyle behaviours.

Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here?

Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.

Resting-state functional magnetic resonance imaging alterations in borderline personality disorder: A systematic review

BACKGROUND

Borderline personality disorder (BPD) is a severe psychiatric disorder characterized by emotion dysregulation, impulsivity, and interpersonal disturbances. Several structural and functional neuroimaging abnormalities have been described in BPD. In particular, resting-state functional magnetic resonance imaging (rs-fMRI) studies have recently suggested various connectivity alterations within and between large-scale brain networks in BPD. This review aimed at providing an updated summary of the evidence reported by the available rs-fMRI studies in BPD individuals.

METHODS

A search on PubMed, Scopus, and Web of Science was performed to identify rs-fMRI alterations in BPD. A total of 15 studies met our inclusion criteria.

RESULTS

Overall, aberrant resting-state functional connectivity (rs-FC) within and between default mode network (DMN), salience network (SN), and central executive network (CEN) were observed in BPD compared to healthy controls, as well as selective functional impairments in bilateral amygdala, anterior and posterior cingulate cortex, hippocampus, and prefrontal cortex.

LIMITATIONS

The observational design, small sample size, prevalence of females, high rates of concurrent comorbidities and medications, and heterogeneity across imaging methodologies limit the generalizability of the results.

CONCLUSIONS

The identification of altered patterns of rs-FC within and between selective brain networks, including DMN, SN, and CEN, could further our knowledge of the clinical symptoms of BPD, and therefore, future studies with multimodal methodologies and longitudinal designs are warranted to further explore the neural correlates of this disorder.

Multifunctional role of natural products for the treatment of Parkinson's disease: At a glance

Natural substances originating from plants have long been used to treat neurodegenerative disorders (NDs). Parkinson's disease (PD) is a ND. The deterioration and subsequent cognitive impairments of the midbrain nigral dopaminergic neurons distinguish by this characteristic. Various pathogenic mechanisms and critical components have been reported, despite the fact that the origin is unknown, such as protein aggregation, iron buildup, mitochondrial dysfunction, neuroinflammation and oxidative stress. Anti-Parkinson drugs like dopamine (DA) agonists, levodopa, carbidopa, monoamine oxidase type B inhibitors and anticholinergics are used to replace DA in the current treatment model. Surgery is advised in cases where drug therapy is ineffective. Unfortunately, the current conventional treatments for PD have a number of harmful side effects and are expensive. As a result, new therapeutic strategies that control the mechanisms that contribute to neuronal death and dysfunction must be addressed. Natural resources have long been a useful source of possible treatments. PD can be treated with a variety of natural therapies made from medicinal herbs, fruits, and vegetables. In addition to their well-known anti-oxidative and anti-inflammatory capabilities, these natural products also play inhibitory roles in iron buildup, protein misfolding, the maintenance of proteasomal breakdown, mitochondrial homeostasis, and other neuroprotective processes. The goal of this research is to systematically characterize the currently available medications for Parkinson's and their therapeutic effects, which target diverse pathways. Overall, this analysis looks at the kinds of natural things that could be used in the future to treat PD in new ways or as supplements to existing treatments. We looked at the medicinal plants that can be used to treat PD. The use of natural remedies, especially those derived from plants, to treat PD has been on the rise. This article examines the fundamental characteristics of medicinal plants and the bioactive substances found in them that may be utilized to treat PD.

Connectivity impairment of cerebellar and sensorimotor connector hubs in Parkinson’s disease

Cognitive and movement processes involved integration of several large-scale brain networks. Central to these integrative processes are connector hubs, brain regions characterized by strong connections with multiple networks. Growing evidence suggests that many neurodegenerative and psychiatric disorders are associated with connector hub dysfunctions. Using a network metric called functional connectivity overlap ratio, we investigated connector hub alterations in Parkinson’s disease. Resting-state functional MRI data from 99 patients (male/female = 44/55) and 99 age- and sex-matched healthy controls (male/female = 39/60) participating in our cross-sectional study were used in the analysis. We have identified two sets of connector hubs, mainly located in the sensorimotor cortex and cerebellum, with significant connectivity alterations with multiple resting-state networks. Sensorimotor connector hubs have impaired connections primarily with primary processing (sensorimotor, visual), visuospatial, and basal ganglia networks, whereas cerebellar connector hubs have impaired connections with basal ganglia and executive control networks. These connectivity alterations correlated with patients’ motor symptoms. Specifically, values of the functional connectivity overlap ratio of the cerebellar connector hubs were associated with tremor score, whereas that of the sensorimotor connector hubs with postural instability and gait disturbance score, suggesting potential association of each set of connector hubs with the disorder’s two predominant forms, the akinesia/rigidity and resting tremor subtypes. In addition, values of the functional connectivity overlap ratio of the sensorimotor connector hubs were highly predictive in classifying patients from controls with an accuracy of 75.76%. These findings suggest that, together with the basal ganglia, cerebellar and sensorimotor connector hubs are significantly involved in Parkinson’s disease with their connectivity dysfunction potentially driving the clinical manifestations typically observed in this disorder.

Characterization of Early Stage Parkinson's Disease From Resting-State fMRI Data Using a Long Short-Term Memory Network

Parkinson's disease (PD) is a common and complex neurodegenerative disorder with five stages on the Hoehn and Yahr scaling. Characterizing brain function alterations with progression of early stage disease would support accurate disease staging, development of new therapies, and objective monitoring of disease progression or treatment response. Functional magnetic resonance imaging (fMRI) is a promising tool in revealing functional connectivity (FC) differences and developing biomarkers in PD. While fMRI and FC data have been utilized for diagnosis of PD through application of machine learning approaches such as support vector machine and logistic regression, the characterization of FC changes in early-stage PD has not been investigated. Given the complexity and non-linearity of fMRI data, we propose the use of a long short-term memory (LSTM) network to distinguish the early stages of PD and understand related functional brain changes. The study included 84 subjects (56 in stage 2 and 28 in stage 1) from the Parkinson's Progression Markers Initiative (PPMI), the largest-available public PD dataset. Under a repeated 10-fold stratified cross-validation, the LSTM model reached an accuracy of 71.63%, 13.52% higher than the best traditional machine learning method and 11.56% higher than a CNN model, indicating significantly better robustness and accuracy compared with other machine learning classifiers. Finally, we used the learned LSTM model weights to select the top brain regions that contributed to model prediction and performed FC analyses to characterize functional changes with disease stage and motor impairment to gain better insight into the brain mechanisms of PD.

Functional Brain Dysconnectivity in Parkinson's Disease: A 5-Year Longitudinal Study

Background

Tracking longitudinal functional brain dysconnectivity in Parkinson's disease (PD) is a key element to decoding the underlying physiopathology and understanding PD progression.

Objectives

The objectives of this follow‐up study were to explore, for the first time, the longitudinal changes in the functional brain networks of PD patients over 5 years and to associate them with their cognitive performance and the lateralization of motor symptoms.

Methods

We used a 5‐year longitudinal cohort of PD patients (n = 35) who completed motor and non‐motor assessments and sequent resting state (RS) high‐density electroencephalography (HD‐EEG) recordings at three timepoints: baseline (BL), 3 years follow‐up (3YFU) and 5 years follow‐up (5YFU). We assessed disruptions in frequency‐dependent functional networks over the course of the disease and explored their relation to clinical symptomatology.

Results

In contrast with HC (n = 32), PD patients showed a gradual connectivity impairment in α2 (10‐13 Hz) and β (13–30 Hz) frequency bands. The deterioration in the global cognitive assessment was strongly correlated with the disconnected networks. These disconnected networks were also associated with the lateralization of motor symptoms, revealing a dominance of the right hemisphere in terms of impaired connections in the left‐affected PD patients in contrast to dominance of the left hemisphere in the right‐affected PD patients.

Conclusions

Taken together, our findings suggest that with disease progression, dysconnectivity in the brain networks in PD can reflect the deterioration of global cognitive deficits and the lateralization of motor symptoms. RS HD‐EEG may be an early biomarker of PD motor and non‐motor progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Neuroimaging approaches to cognition in Parkinson's disease

While direct visualization of Lewy body accumulation within the brain is not yet possible in living Parkinson's disease patients, brain imaging studies offer insights into how the buildup of Lewy body pathology impacts different regions of the brain. Unlike biological biomarkers and purely behavioral research, these brain imaging studies therefore offer a unique opportunity to relate brain localization to cognitive function and dysfunction in living patients. Magnetic resonance imaging studies can reveal physical changes in brain structure as they relate to different cognitive domains and task specific impairments. Functional imaging studies use a combination of task and resting state magnetic resonance imaging, as well as positron emission tomography and single photon emission computed tomography, and can be used to determine changes in blood flow, neuronal activation and neurochemical changes in the brain associated with PD cognition and cognitive impairments. Other unique advantages to brain imaging studies are the ability to monitor changes in brain structure and function longitudinally as patients progress and the ability to study changes in brain function when patients are exposed to different pharmacological manipulations. This is particularly true when assessing the effects of dopaminergic replacement therapy on cognitive function in Parkinson's disease patients. Together, this chapter will describe imaging studies that have helped identify structural and functional brain changes associated with cognition, cognitive impairment, and dementia in Parkinson's disease.

Deficient Interhemispheric Connectivity Underlies Movement Irregularities in Parkinson's Disease

BACKGROUND

Movement execution is impaired in patients with Parkinson's disease. Evolving neurodegeneration leads to altered connectivity between distinct regions of the brain and altered activity at interconnected areas. How connectivity alterations influence complex movements like drawing spirals in Parkinson's disease patients remains largely unexplored.

OBJECTIVE

We investigated whether deteriorations in interregional connectivity relate to impaired execution of drawing.

METHODS

Twenty-nine patients and 31 age-matched healthy control participants drew spirals with both hands on a digital graphics tablet, and the regularity of drawing execution was evaluated by sample entropy. We recorded resting-state fMRI and task-related EEG, and calculated the time-resolved partial directed coherence to estimate effective connectivity for both imaging modalities to determine the extent and directionality of interregional interactions.

RESULTS

Movement performance in Parkinson's disease patients was characterized by increased sample entropy, corresponding to enhanced irregularities in task execution. Effective connectivity between the motor cortices of both hemispheres, derived from resting-state fMRI, was significantly reduced in Parkinson's disease patients in comparison to controls. The connectivity strength in the nondominant to dominant hemisphere direction in both modalities was inversely correlated with irregularities during drawing, but not with the clinical state.

CONCLUSION

Our findings suggest that interhemispheric connections are affected both at rest and during drawing movements by Parkinson's disease. This provides novel evidence that disruptions of interhemispheric information exchange play a pivotal role for impairments of complex movement execution in Parkinson's disease patients.

Enriched Rehabilitation Improves Gait Disorder and Cognitive Function in Parkinson's Disease: A Randomized Clinical Trial

Background: Studies on non-pharmacological strategies for improving gait performance and cognition in Parkinson's disease (PD) are of great significance. We aimed to investigate the effect of and mechanism underlying enriched rehabilitation as a potentially effective strategy for improving gait performance and cognition in early-stage PD. Methods: Forty participants with early-stage PD were randomly assigned to receive 12 weeks (2 h/day, 6 days/week) of enriched rehabilitation (ER; n = 20; mean age, 66.14 ± 4.15 years; 45% men) or conventional rehabilitation (CR; n = 20; mean age 65.32 ± 4.23 years; 50% men). In addition, 20 age-matched healthy volunteers were enrolled as a control (HC) group. We assessed the general motor function using the Unified PD Rating Scale-Part III (UPDRS-III) and gait performance during single-task (ST) and dual-task (DT) conditions pre- and post-intervention. Cognitive function assessments included the Montreal Cognitive Assessment (MoCA), the Symbol Digit Modalities Test (SDMT), and the Trail Making Test (TMT), which were conducted pre- and post-intervention. We also investigated alteration in positive resting-state functional connectivity (RSFC) of the left dorsolateral prefrontal cortex (DLPFC) in participants with PD, mediated by ER, using functional magnetic resonance imaging (fMRI). Results: Compared with the HC group, PD participants in both ER and CR groups performed consistently poorer on cognitive and motor assessments. Significant improvements were observed in general motor function as assessed by the UPDRS-III in both ER and CR groups post-intervention. However, only the ER group showed improvements in gait parameters under ST and DT conditions post-intervention. Moreover, ER had a significant effect on cognition, which was reflected in increased MoCA, SDMT, and TMT scores post-intervention. MoCA, SDMT, and TMT scores were significantly different between ER and CR groups post-intervention. The RSFC analysis showed strengthened positive functional connectivity between the left DLPFC and other brain areas including the left insula and left inferior frontal gyrus (LIFG) post-ER. Conclusion: Our findings indicated that ER could serve as a potentially effective therapy for early-stage PD for improving gait performance and cognitive function. The underlying mechanism based on fMRI involved strengthened RSFC between the left DLPFC and other brain areas (e.g., the left insula and LIFG).

Altered microstructural properties of superficial white matter in patients with Parkinson's disease

Parkinson's disease (PD), a chronic neurodegenerative disease, is characterized by sensorimotor and cognitive deficits. Previous diffusion tensor imaging (DTI) studies found abnormal DTI metrics in white matter bundles, such as the corpus callosum, cingulate, and frontal-parietal bundles, in PD patients. These studies mainly focused on alterations in microstructural features of long-range bundles within the deep white matter (DWM) that connects pairs of distant cortical regions. However, less is known about the DTI metrics of the superficial white matter (SWM) that connects local cortical regions in PD patients. To determine whether the DTI metrics of the SWM were different between the PD patients and the healthy controls, we recruited DTI data from 34 PD patients and 29 gender- and age-matched healthy controls. Using a probabilistic tractographic approach, we first defined a population-based SWM mask across all the subjects. Using a tract-based spatial statistical (TBSS) analytic approach, we then identified the SWM bundles showing abnormal DTI metrics in the PD patients. We found that the PD patients showed significantly lower DTI metrics in the SWM bundles connecting the sensorimotor cortex, cingulate cortex, posterior parietal cortex (PPC), and parieto-occipital cortex than the healthy controls. We also found that the clinical measures in the PD patients was significantly negatively correlated with the fractional anisotropy in the SWM (FA_SWM) that connects core regions in the default mode network (DMN). The FA_SWM in the bundles that connected the PPC was significantly positively correlated with cognitive performance in the PD patients. Our findings suggest that SWM may serve as the brain structural basis underlying the sensorimotor deficits and cognitive degeneration in PD patients.

Disrupted Spontaneous Neural Activity in Patients With Thyroid-Associated Ophthalmopathy: A Resting-State fMRI Study Using Amplitude of Low-Frequency Fluctuation

PURPOSE

The purpose of the study was to investigate the brain functional alteration in patients with thyroid-associated ophthalmopathy (TAO) by evaluating the spontaneous neural activity changes using resting-state functional magnetic resonance imaging (rs-fMRI) with the amplitude of low-frequency fluctuation (ALFF) method.

MATERIALS AND METHODS

The rs-fMRI data of 30 TAO patients (15 active and 15 inactive) and 15 healthy controls (HCs) were included for analyses. The ALFF values were calculated and compared among groups. Correlations between ALFF values and clinical metrics were assessed.

RESULTS

Compared with HCs, active TAOs showed significantly decreased ALFF values in the left middle occipital gyrus, superior occipital gyrus, and cuneus. Compared with inactive TAOs, active TAOs showed significantly increased ALFF values in the bilateral precuneus. Additionally, inactive TAOs showed significantly decreased ALFF values in the left middle occipital gyrus, superior occipital gyrus, cuneus, and bilateral precuneus than HCs. The ALFF value in the right precuneus of TAOs was positively correlated with clinical activity score (r = 0.583, P < 0.001) and Mini-Mental State Examination (MMSE) score (r = 0.377, P = 0.040), and negatively correlated with disease duration (r = -0.382, P = 0.037). Moreover, the ALFF value in the left middle occipital gyrus of TAOs was positively correlated with visual acuity (r = 0.441, P = 0.015).

CONCLUSION

TAO patients had altered spontaneous brain activities in the left occipital lobe and bilateral precuneus. The neuropsychological aspect of the disease should be noticed during clinical diagnosis and treatment.

Functional connectivity of spoken language processing in early-stage Parkinson's disease: An MEG study

Parkinson's disease (PD) is a neurodegenerative disorder, well-known for its motor symptoms; however, it also adversely affects cognitive functions, including language, a highly important human ability. PD pathology is associated, even in the early stage of the disease, with alterations in the functional connectivity within cortico-subcortical circuitry of the basal ganglia as well as within cortical networks. Here, we investigated functional cortical connectivity related to spoken language processing in early-stage PD patients. We employed a patient-friendly passive attention-free paradigm to probe neurophysiological correlates of language processing in PD patients without confounds related to active attention and overt motor responses. MEG data were recorded from a group of newly diagnosed PD patients and age-matched healthy controls who were passively presented with spoken word stimuli (action and abstract verbs, as well as grammatically correct and incorrect inflectional forms) while focussing on watching a silent movie. For each of the examined linguistic aspects, a logistic regression classifier was used to classify participants as either PD patients or healthy controls based on functional connectivity within the temporo-fronto-parietal cortical language networks. Classification was successful for action verbs (accuracy = 0.781, p-value = 0.003) and, with lower accuracy, for abstract verbs (accuracy = 0.688, p-value = 0.041) and incorrectly inflected forms (accuracy = 0.648, p-value = 0.021), but not for correctly inflected forms (accuracy = 0.523, p-value = 0.384). Our findings point to quantifiable differences in functional connectivity within the cortical systems underpinning language processing in newly diagnosed PD patients compared to healthy controls, which arise early, in the absence of clinical evidence of deficits in cognitive or general language functions. The techniques presented here may aid future work on establishing neurolinguistic markers to objectively and noninvasively identify functional changes in the brain's language networks even before clinical symptoms emerge.

Within- and across-network alterations of the sensorimotor network in Parkinson's disease

Purpose

Parkinson’s disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks.

Methods

Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters.

Results

There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON.

Conclusion

PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-021-02731-w.

Voxel-wise functional connectivity of the default mode network in epilepsies: a systematic review and meta-analysis

Background:

Default Mode Network (DMN) is recognized to be involved in the generation and propagation of epileptic activities in various epilepsies. Converging evidence has suggested disturbed Functional Connectivity (FC) in epilepsies, which was inferred to be related to underlying pathological mechanisms. However, abnormal changes of FC in DMN revealed by different studies are controversial, which obscures the role of DMN in distinct epilepsies.

Objective:

The present work aims to investigate the voxel-wise FC in DMN across epilepsies.

Methods:

A systematic review was conducted on 22 published articles before October 2020, indexed in PubMed and Web of Science. A meta-analysis with a random-effect model was performed using the effect-size signed differential mapping approach. Subgroup analyses were performed in three groups: Idiopathic Generalized Epilepsy (IGE), mixed Temporal Lobe Epilepsy (TLE), and mixed Focal Epilepsy (FE) with different foci.

Results:

The meta-analysis suggested commonly decreased FC in mesial prefrontal cortices across different epilepsies. Additionally decreased FC in posterior DMN was observed in IGE. The TLE showed decreased FC in temporal lobe regions and increased FC in the dorsal posterior cingulate cortex. Interestingly, an opposite finding in the ventral and dorsal middle frontal gyrus was observed in TLE. The FE demonstrated increased FC in the cuneus.

Opposite effects of one session of 1 Hz rTMS on functional connectivity between pre-supplementary motor area and putamen depending on the dyskinesia state in Parkinson's disease

OBJECTIVE

To explore the effects of low-frequency repetitive transcranial magnetic stimulation (LF rTMS) on cortico-striatal-cerebellar resting state functional connectivity in Parkinson's disease (PD), with and without dyskinesias.

METHODS

Because there is increasing evidence of an involvement of the pre-supplementary motor area (pre-SMA) in the pathophysiology of levodopa induced dyskinesias, we targeted the right pre-SMA with LF rTMS in 17 PD patients. We explored the effects of one sham-controlled LF rTMS session on resting state functional connectivity of interconnected brain regions by using functional MRI, and how it is modified by levodopa. The clinical effect on motor function and dyskinesias was documented.

RESULTS

As expected, one LF rTMS session did not alleviate dyskinesias. However, real, and not sham LF rTMS significantly increased the functional connectivity with the right putamen in patients with dyskinesias. In patients without dyskinesias, the real LF rTMS session significantly decreased functional connectivity in the right putamen and the cerebellum. We found no effects on functional connectivity after levodopa ingestion.

CONCLUSION

One session of 1 Hz rTMS has opposing effects on pre-SMA functional connectivity depending on the PD patients' dyskinesia state.

SIGNIFICANCE

Patients dyskinesias state determines the way LF rTMS affects functional connectivity in late stage PD.

Cortical thickness in Parkinson's disease: a coordinate-based meta-analysis

Parkinson's disease (PD) is a common age-related neurodegenerative disease that affects the structural architecture of the cerebral cortex. Cortical thickness (CTh) via surface-based morphometry (SBM) analysis is a popular measure to assess brain structural alterations in the gray matter in PD. However, the results of CTh analysis in PD lack consistency and have not been systematically reviewed. We conducted a comprehensive coordinate-based meta-analysis (CBMA) of 38 CTh studies (57 comparison datasets) in 1,843 patients with PD using the latest seed-based d mapping software. Compared with 1,172 healthy controls, no significantly consistent CTh alterations were found in patients with PD, suggesting CTh as an unreliable neuroimaging marker for PD. The lack of consistent CTh alterations in PD could be ascribed to the heterogeneity in clinical populations, variations in imaging methods, and underpowered small sample sizes. These results highlight the need to control for potential confounding factors to produce robust and reproducible CTh results in PD.

Distinct Effects of Motor Training on Resting-State Functional Networks of the Brain in Parkinson’s Disease

Background. Nigrostriatal dopaminergic loss is a hallmark of Parkinson’s disease (PD) pathophysiology, leading to motor Parkinsonism. Different intervention protocols have shown that motor and cognitive functions improvement in PD occur via the modulation of distinct motor and cognitive pathways. Objective. To investigate the effects of two motor training programs on the brains’ functional networks in PD patients. Methods. Thirty-seven PD patients were prospectively studied. All enrolled patients underwent either treadmill training (TT) (n = 19) or treadmill with virtual reality (TT + VR) (n = 18) for 6 weeks. Magnetic resonance imaging (MRI) scans (3 T) acquiring 3-dimensional T1-weighted and resting-state functional MRI (rs-fMRI) data sets were performed at baseline and after 6 weeks. Independent component analysis (ICA) was conducted, and functional connectivity (FC) changes within large-scale functional brain networks were examined. Results. In both groups, significant post-training FC decrease in striatal, limbic, and parietal regions within the basal ganglia network, executive control network, and frontal-striatal network, and significant FC increase in the caudate, and cingulate within the sensorimotor network (SMN) were observed. Moreover, a significant time × group interaction was detected where TT + VR training had greater effects on FC levels in the supplementary motor area (SMA) and right precentral gyrus within the SMN, and in the right middle frontal gyrus (MFG) within the cerebellar network. These FC alterations were associated with improved usual and dual-task walking performance. Conclusions. These results suggest that TT with-and-without the addition of a VR component affects distinct neural pathways, highlighting the potential for beneficial neural plasticity in PD. Such distinctive task-specific pathways may foster the facilitation of interventions tailored to the individual needs of PD patients. Registered at Clinicaltrials.gov number: NCT01732653.

Levodopa Changes Functional Connectivity Patterns in Subregions of the Primary Motor Cortex in Patients With Parkinson's Disease

Background

The primary motor cortex (M1) is a critical node in Parkinson’s disease (PD)-related motor circuitry; however, the functional roles of its subregions are poorly understood. In this study, we investigated changes in the functional connectivity patterns of M1 subregions and their relationships to improved clinical symptoms following levodopa administration.

Methods

Thirty-six PD patients and 37 healthy controls (HCs) were enrolled. A formal levodopa challenge test was conducted in the PD group, and the Unified Parkinson’s Disease Rating Scale motor section (UPDRS-III) was assessed before (off state) and 1 h after administration of levodopa (on state). The PD group underwent resting-state functional magnetic resonance imaging in both off and on states, whereas the HC group was scanned once. We used the Human Brainnetome Atlas template to subdivide M1 into twelve regions of interest (ROIs). Functional connectivity (FC) was compared between PD on and off states [paired t-test, voxel-level p < 0.001, cluster-level p < 0.05, Gaussian random field (GRF) correction] and between patients and HC (two-sample t-test voxel-level p < 0.001, cluster-level p < 0.05). Correlations between ΔFC (differences in FC between PD off and on states) and clinical symptom improvements were examined.

Results

There was decreased FC between the right caudal dorsolateral area 6 and the anterior cingulate gyrus (ACC), the right upper limb region and the left medial dorsal thalamus (mdTHA), as well as increased FC between the left tongue and larynx region and the left medial frontal gyrus. ΔFC between the right caudal dorsolateral area 6 and ACC was positively correlated with improvements in UPDRS-III total scores as well as the rigidity (item 22) and bradykinesia (items 23–26 and 31) subscores. ΔFC between the right upper limb region and left thalamus was positively correlated with improvements in the left upper limb tremor (items 20c and 21b) and postural tremor (item 21b) subscores.

Conclusions

Our results reveal novel information regarding the underlying mechanisms in the motor circuits in the M1 and a promising way to explore the internal function of the M1 in PD patients. Notably, M1 is a potential therapeutic target in PD, and the exploration of its subregions provides a basis and a source of new insights for clinical intervention and precise drug treatment.

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.

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

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

MRI biomarkers of motor and non-motor symptoms in Parkinson's disease

Parkinson's disease is a heterogeneous disorder with both motor and non-motor symptoms that contribute to functional impairment. To develop effective, disease modifying treatments for these symptoms, biomarkers are necessary to detect neuropathological changes early in the disease course and monitor changes over time. Advances in MRI scan sequences and analytical techniques present numerous promising metrics to detect changes within the nigrostriatal system, implicated in the cardinal motor symptoms of the disease, and detect broader dysfunction involved in the non-motor symptoms, such as cognitive impairment. There is emerging evidence that iron sensitive, neuromelanin sensitive, diffusion sensitive, and resting state functional magnetic imaging measures can capture changes within the nigrostriatal system. Iron, neuromelanin, and diffusion sensitive measures demonstrate high specificity and sensitivity in distinguishing Parkinson's disease relative to controls, with inconsistent results differentiating Parkinson's disease relative to atypical parkinsonian disorders. They may also serve as useful monitoring biomarkers, with each possibly detecting different aspects of the disease course (early nigrosome changes versus broader substantia nigra changes). Investigations of non-motor symptoms, such as cognitive impairment, require careful consideration of the nature of cognitive deficits to characterize regional and network specific impairment. While the early, executive dysfunction observed is consistent with nigrostriatal degeneration, the memory and visuospatial impairments, the harbingers of a dementia process reflect dopaminergic independent dysfunction involving broader regions of the brain.

Altered spontaneous brain activity pattern in patients with ophthalmectomy: an resting-state fMRI study

AIM

To use the voxel-wise degree centrality (DC) method to explore the underlying functional network brain-activity in patients with ophthalmectomy.

METHODS

A total of 32 ophthalmic surgery patients (10 women and 22 men), and 32 healthy subjects (10 women and 22 men) highly matched in gender, age, and the same operation method. Everyone experienced a resting-state functional magnetic resonance imaging scan. The spontaneous brain activity could be assessed by DC. Correlation analysis was used to explore the relationships between the average DC signal values and behavior performance in different regions. Receiver operating characteristic (ROC) curve analysis was utilized to differentiate between ophthalmectomy patients and healthy controls (HCs).

RESULTS

Compared with HCs, ophthalmectomy patients had greatly reduced DC values in left lingual gyrus, bilateral lingual lobe, left cingulate gyrus, and increased DC values of left cerebellum posterior lobe, left middle frontal gyrus1, right supramarginal gyrus, left middle frontal gyrus2, right middle frontal gyrus. However, we did not find that there was a correlation between the average DC values from various brain regions and clinical manifestations.

CONCLUSION

Dysfunction may be caused by ophthalmectomy in lots of cerebral areas, which may show the potential pathological mechanism of ophthalmectomy and it is beneficial to clinical diagnosis.

Network degeneration in Parkinson’s disease: multimodal imaging of nigro-striato-cortical dysfunction

The spreading hypothesis of neurodegeneration assumes an expansion of neural pathologies along existing neural pathways. Multimodal neuroimaging studies have demonstrated distinct topographic patterns of cerebral pathologies in neurodegeneration. For Parkinson’s disease the hypothesis so far rests largely on histopathological evidence of α-synuclein spreading in a characteristic pattern and progressive nigrostriatal dopamine depletion. Functional consequences of nigrostriatal dysfunction on cortical activity remain to be elucidated. Our goal was to investigate multimodal imaging correlates of degenerative processes in Parkinson’s disease by assessing dopamine depletion and its potential effect on striatocortical connectivity networks and cortical metabolism in relation to parkinsonian symptoms. We combined 18F-DOPA-PET, 18F-fluorodeoxyglucose (FDG)-PET and resting state functional MRI to multimodally characterize network alterations in Parkinson’s disease. Forty-two patients with mild-to-moderate stage Parkinson’s disease and 14 age-matched healthy control subjects underwent a multimodal imaging protocol and comprehensive clinical examination. A voxel-wise group comparison of 18F-DOPA uptake identified the exact location and extent of putaminal dopamine depletion in patients. Resulting clusters were defined as seeds for a seed-to-voxel functional connectivity analysis. 18F-FDG metabolism was compared between groups at a whole-brain level and uptake values were extracted from regions with reduced putaminal connectivity. To unravel associations between dopaminergic activity, striatocortical connectivity, glucose metabolism and symptom severity, correlations between normalized uptake values, seed-to-cluster β-values and clinical parameters were tested while controlling for age and dopaminergic medication. Aside from cortical hypometabolism, 18F-FDG-PET data for the first time revealed a hypometabolic midbrain cluster in patients with Parkinson’s disease that comprised caudal parts of the bilateral substantia nigra pars compacta. Putaminal dopamine synthesis capacity was significantly reduced in the bilateral posterior putamen and correlated with ipsilateral nigral 18F-FDG uptake. Resting state functional MRI data indicated significantly reduced functional connectivity between the dopamine depleted putaminal seed and cortical areas primarily belonging to the sensorimotor network in patients with Parkinson’s disease. In the inferior parietal cortex, hypoconnectivity in patients was significantly correlated with lower metabolism (left P = 0.021, right P = 0.018). Of note, unilateral network alterations quantified with different modalities corresponded with contralateral motor impairments. In conclusion, our results support the hypothesis that degeneration of nigrostriatal fibres functionally impairs distinct striatocortical connections, disturbing the efficient interplay between motor processing areas and impairing motor control in patients with Parkinson’s disease. The present study is the first to reveal trimodal evidence for network-dependent degeneration in Parkinson’s disease by outlining the impact of functional nigrostriatal pathway impairment on striatocortical functional connectivity networks and cortical metabolism.

Detecting and Testing Altered Brain Connectivity Networks with K-partite Network Topology

Emerging brain connectivity network studies suggest that interactions between various distributed neuronal populations may be characterized by an organized complex topological structure. Many neuropsychiatric disorders are associated with altered topological patterns of brain connectivity. Therefore, a key inquiry of connectivity analysis is to detect group-level differentially expressed connectome patterns from the massive neuroimaging data. Recently, statistical methods have been developed to detect differentially expressed connectivity features at a subnetwork level, extending more commonly applied edge level analysis. However, the graph topological structures in these methods are limited to community/cliques which may not effectively uncover the underlying complex and disease-related brain circuits/subnetworks. Building on these previous subnetwork detection methods, a new statistical approach is developed to automatically identify the latent differentially expressed brain connectivity subnetworks with k-partite graph topological structures from large brain connectivity matrices. In addition, statistical inferential techniques are provided to test the detected topological structure. The new methods are evaluated via extensive simulation studies and then applied to resting state fMRI data (24 cases and 18 controls) for Parkinson's disease research. A differentially expressed connectivity network with the k-partite graph topological structure is detected which reveals underlying neural features distinguishing Parkinson's disease patients from healthy control subjects.

Patterns of olfactory functional networks in Parkinson's disease dementia and Alzheimer's dementia

Hyposmia is common in Alzheimer's dementia (AD) and Parkinson's disease dementia (PDD). We evaluated the pattern of olfactory functional connectivity (FC) in AD and PDD to uncover neural correlates that are related to olfactory dysfunction. This study enrolled 57 patients with AD and PDD and 25 control subjects. Using a seed-based approach, we compared the resting-state network from the seed-region-of-interest in the olfactory bulb, olfactory tract, piriform cortex, and orbitofrontal cortex (OFC) between groups. The PDD group showed lower FC with striatal-thalamic-frontal regions from the olfactory bulb than the AD group. The PDD group showed lower FC from left OFC with striatal-frontal regions and lower FC from right OFC with left fronto-temporal areas than the AD group. In a correlation analysis, the FC from left OFC with right insula that differed between the PDD and control groups was positively correlated with olfactory function. The present study demonstrated that this distinct olfactory functional network pattern may represent different neural mechanisms for olfactory dysfunction in AD and PDD.

Allelic variant in SLC6A3 rs393795 affects cerebral regional homogeneity and gait dysfunction in patients with Parkinson's disease

Aims

We sought to explore the role of the SLC6A3rs393795 allelic variant in cerebral spontaneous activity and clinical features in Parkinson’s disease (PD) via imaging genetic approach.

Methods

Our study recruited 50 PD and 45 healthy control (HC) participants to provide clinical, genetic, and resting state functional magnetic resonance imaging (rs-fMRI) data. All subjects were separated into 16 PD-AA, 34 PD-CA/CC, 14 HC-AA, and 31 HC-CA/CC four subgroups according to SLC6A3rs393795 genotyping. Afterwards, main effects and interactions of groups (PD versus HC) and genotypes (AA versus CA/CC) on cerebral function reflected by regional homogeneity (ReHo) were explored using two-way analysis of covariance (ANCOVA) after controlling age and gender. Finally, Spearman’ s correlations were employed to investigate the relationships between significantly interactive brain regions and clinical manifestations in PD subgroups.

Results

Compared with HC subjects, PD patients exhibited increased ReHo signals in left middle temporal gyrus and decreased ReHo signals in left pallidum. Compared with CA/CC carriers, AA genotype individuals showed abnormal increased ReHo signals in right inferior frontal gyrus (IFG) and supplementary motor area (SMA). Moreover, significant interactions (affected by both disease factor and allelic variation) were detected in right inferior temporal gyrus (ITG). Furthermore, aberrant increased ReHo signals in right ITG were observed in PD-AA in comparison with PD-CA/CC. Notably, ReHo values in right ITG were negatively associated with Tinetti Mobility Test (TMT) gait subscale scores and positively related to Freezing of Gait Questionnaire (FOG-Q) scores in PD-AA subgroup.

Conclusions

Our findings suggested that SLC6A3rs393795 allelic variation might have a trend to aggravate the severity of gait disorders in PD patients by altering right SMA and IFG function, and ultimately result in compensatory activation of right ITG. It could provide us with a new perspective for exploring deeply genetic mechanisms of gait disturbances in PD.

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.

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

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

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.

Why Is Aging a Risk Factor for Cognitive Impairment in Parkinson's Disease?-A Resting State fMRI Study

Using resting-state functional MRI (rsfMRI) data of younger and older healthy volunteers and patients with Parkinson's disease (PD) with and without mild cognitive impairment (MCI) and applying two different analytic approaches, we investigated the effects of age, pathology, and cognition on brain connectivity. When comparing rsfMRI connectivity strength of PD patients and older healthy volunteers, reduction between multiple brain regions in PD patients with MCI (PD-MCI) compared with PD patients without MCI (PD-non-MCI) was observed. This group difference was not affected by the number and location of clusters but was reduced when age was included as a covariate. Next, we applied a graph-theory method with a cost-threshold approach to the rsfMRI data from patients with PD with and without MCI as well as groups of younger and older healthy volunteers. We observed decreased hub function (measured by degree and betweenness centrality) mainly in the medial prefrontal cortex (mPFC) in older healthy volunteers compared with younger healthy volunteers. We also found increased hub function in the posterior medial structure (precuneus and the cingulate cortex) in PD-non-MCI patients compared with older healthy volunteers and PD-MCI patients. Hub function in these posterior medial structures was positively correlated with cognitive function in all PD patients. Together these data suggest that overlapping patterns of hub modifications could mediate the effect of age as a risk factor for cognitive decline in PD, including age-related reduction of hub function in the mPFC, and recruitment availability of the posterior medial structure, possibly to compensate for impaired basal ganglia function.

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.

Fetal and neonatal neuroimaging

Magnetic resonance imaging (MRI) can provide detail of the soft tissues of the fetal and neonatal brain that cannot be obtained by any other imaging modality. Conventional T1 and T2 weighted sequences provide anatomic detail of the normally developing brain and can demonstrate lesions, including those associated with preterm birth, hypoxic ischemic encephalopathy, perinatal arterial stroke, infections, and congenital malformations. Specialized imaging techniques can be used to assess cerebral vasculature (magnetic resonance angiography and venography), cerebral metabolism (magnetic resonance spectroscopy), cerebral perfusion (arterial spin labeling), and function (functional MRI). A wealth of quantitative tools, most of which were originally developed for the adult brain, can be applied to study the developing brain in utero and postnatally including measures of tissue microstructure obtained from diffusion MRI, morphometric studies to measure whole brain and regional tissue volumes, and automated approaches to study cortical folding. In this chapter, we aim to describe different imaging approaches for the fetal and neonatal brain, and to discuss their use in a range of clinical applications.

Structural and Functional Magnetic Resonance Imaging of Dementia With Lewy Bodies

Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimer's disease (AD). Although diagnosis may be challenging, there is increasing evidence that the use of biomarkers according to 2017 revised criteria for diagnosis and management of dementia with Lewy bodies can increase diagnostic accuracy. Apart from nuclear medicine techniques, various magnetic resonance imaging (MRI) techniques have been utilized in attempt to enhance diagnostic accuracy. This chapter reviews structural, functional and diffusion MRI studies in DLB cohorts being compared to healthy controls, AD or dementia in Parkinson's disease (PDD). We also included relatively new MRI methods that may have potential to identify early DLB subjects and aim at examining brain iron and neuromelanin.

Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.

Altered Whole-Brain and Network-Based Functional Connectivity in Parkinson's Disease

Background: Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson's disease. In this study we used a relatively new graph analysis approach in functional imaging: eigenvector centrality mapping. This model-free method, applied to all voxels in the brain, identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. In other neurological disorders, eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks.

Objectives: Examining changes in functional brain connectivity architecture on a whole brain and network level in patients with Parkinson's disease.

Methods: Whole brain resting-state functional architecture was studied with a recently introduced graph analysis approach (eigenvector centrality mapping). Functional connectivity was further investigated in relation to eight known resting-state networks. Cross-sectional analyses included group comparison of functional connectivity measures of Parkinson's disease patients (n = 107) with control subjects (n = 58) and correlations with clinical data, including motor and cognitive impairment and a composite measure of predominantly non-dopaminergic symptoms.

Results: Eigenvector centrality mapping revealed that frontoparietal regions were more prominent in the whole-brain network function in patients compared to control subjects, while frontal and occipital brain areas were less prominent in patients. Using standard resting-state networks, we found predominantly increased functional connectivity, namely within sensorimotor system and visual networks in patients. Regional group differences in functional connectivity of both techniques between patients and control subjects partly overlapped for highly connected posterior brain regions, in particular in the posterior cingulate cortex and precuneus. Clinico-functional imaging relations were not found.

Conclusions: Changes on the level of functional brain connectivity architecture might provide a different perspective of pathological consequences of Parkinson's disease. The involvement of specific, highly connected (hub) brain regions may influence whole brain functional network architecture in Parkinson's disease.

Default mode network modifications in Fabry disease: A resting-state fMRI study with structural correlations

Aim of the study was to evaluate the presence of Default Mode Network (DMN) modifications in Fabry Disease (FD), and their possible correlations with structural alterations and neuropsychological scores. Thirty-two FD patients with a genetically confirmed diagnosis of classical FD (12 males, mean age 43.3 ± 12.2) were enrolled, along with 35 healthy controls (HC) of comparable age and sex (14 males, mean age 42.1 ± 14.5). Resting-State fMRI data were analyzed using a seed-based approach, with six different seeds sampling the main hubs of the DMN. Structural modifications were assessed by means of Voxel-Based Morphometry (VBM) and Tract-Based Spatial Statistics analyses. Between-group differences and correlations with neuropsychological variables were probed voxelwise over the whole brain. Possible correlations between FC modifications and global measures of microstructural alteration were also tested in FD patients with a partial correlation analysis. In the FD group, clusters of increased functional connectivity involving both supratentorial and infratentorial regions emerged, partially correlated to the widespread white matter (WM) damage found in these patients. No gray matter volume differences were found at VBM between the two groups. The connectivity between right inferior frontal gyrus and precuneus was significantly correlated with the Corsi block-tapping test results (p = .0001). Widespread DMN changes are present in FD patients that correlate with WM alterations and cognitive performance. Our results confirm the current view of a cerebral involvement in FD patients not simply associated to major cerebrovascular events, but also related to significant and diffuse microstructural and functional changes.

Incorporating spatial constraint in co-activation pattern analysis to explore the dynamics of resting-state networks: An application to Parkinson's disease

The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD.

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.

On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification

Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc.

Frequency-Dependent Altered Functional Connections of Default Mode Network in Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder associated with the progressive dysfunction of cognitive ability. Previous research has indicated that the default mode network (DMN) is closely related to cognition and is impaired in Alzheimer’s disease. Because recent studies have shown that different frequency bands represent specific physiological functions, DMN functional connectivity studies of the different frequency bands based on resting state fMRI (RS-fMRI) data may provide new insight into AD pathophysiology. In this study, we explored the functional connectivity based on well-defined DMN regions of interest (ROIs) from the five frequency bands: slow-5 (0.01–0.027 Hz), slow-4 (0.027–0.073 Hz), slow-3 (0.073–0.198 Hz), slow-2 (0.198–0.25 Hzs) and standard low-frequency oscillations (LFO) (0.01–0.08 Hz). We found that the altered functional connectivity patterns are mainly in the frequency band of slow-5 and slow-4 and that the decreased connections are long distance, but some relatively short connections are increased. In addition, the altered functional connections of the DMN in AD are frequency dependent and differ between the slow-5 and slow-4 bands. Mini-Mental State Examination scores were significantly correlated with the altered functional connectivity patterns in the slow-5 and slow-4 bands. These results indicate that frequency-dependent functional connectivity changes might provide potential biomarkers for AD pathophysiology.

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.

Levodopa response differs in Parkinson's motor subtypes: A task-based effective connectivity study

Parkinson's disease (PD) is a circuit-level disorder with clinically-determined motor subtypes. Despite evidence suggesting each subtype may have different pathophysiology, few neuroimaging studies have examined levodopa-induced differences in neural activation between tremor dominant (TD) and postural instability/gait difficulty (PIGD) subtype patients during a motor task. The goal of this functional MRI (fMRI) study was to examine task-induced activation and connectivity in the cortico-striatal-thalamo-cortical motor circuit in healthy controls, TD patients, and PIGD patients before and after levodopa administration. Fourteen TD and 12 PIGD cognitively-intact patients and 21 age- and sex-matched healthy controls completed a right-hand, paced tapping fMRI paradigm. Collectively, PD patients off medication (OFF) showed hypoactivation of the motor cortex relative to healthy controls, even when controlling for performance. After levodopa intake, the PIGD patients had significantly increased activation in the left putamen compared with TD patients and healthy controls. Psychophysiological interaction analysis revealed that levodopa increased effective connectivity between the posterior putamen and other areas of the motor circuit during tapping in TD patients, but not in PIGD patients. This novel, levodopa-induced difference in the neural responses between PD motor subtypes may have significant implications for elucidating the mechanisms underlying the distinct phenotypic manifestations and enabling the classification of motor subtypes objectively using fMRI.

Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis

Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Studies using resting-state functional magnetic resonance imaging (fMRI) to investigate underlying pathophysiology of motor and non-motor symptoms in PD yielded largely inconsistent results. This quantitative neuroimaging meta-analysis aims to identify consistent abnormal intrinsic functional patterns in PD across studies. We used PubMed to retrieve suitable resting-state studies and stereotactic data were extracted from 28 individual between-group comparisons. Convergence across their findings was tested using the activation likelihood estimation (ALE) approach. We found convergent evidence for intrinsic functional disturbances in bilateral inferior parietal lobule (IPL) and the supramarginal gyrus in PD patients compared to healthy subjects. In follow-up task-based and task-independent functional connectivity (FC) analyses using two independent healthy subject data sets, we found that the regions showing convergent aberrations in PD formed an interconnected network mainly with the default mode network (DMN). Behavioral characterization of these regions using the BrainMap database suggested associated dysfunction of perception and executive processes. Taken together, our findings highlight the role of parietal cortex in the pathophysiology of PD.

Cognitive phenotypes in parkinson's disease differ in terms of brain-network organization and connectivity

Cognitive deficits are common in Parkinson's disease and we suspect that dysfunctions of connected brain regions can be the source of these deficits. The aim of the present study was to investigate changes in whole-brain intrinsic functional connectivity according to differences in cognitive profiles in Parkinson's disease. 119 participants were enrolled and divided into four groups according to their cognitive phenotypes (determined by a cluster analysis): (i) 31 cognitively intact patients (G1), (ii) 31 patients with only slight mental slowing (G2), (iii) 43 patients with mild to moderate deficits mainly in executive functions (G3), (iv) 14 patients with severe deficits in all cognitive domains (G4-5). Rs-fMRI whole-brain connectivity was examined by two complementary approaches: graph theory for studying network functional organization and network-based statistics (NBS) for exploring functional connectivity amongst brain regions. After adjustment for age, duration of formal education and center of acquisition, there were significant group differences for all functional organization indexes: functional organization decreased (G1 > G2 > G3 > G4-5) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, P < 0.01) mainly concerned the ventral prefrontal, parietal, temporal and occipital cortices as well as the basal ganglia. In Parkinson's disease, brain network organization is progressively disrupted as cognitive impairment worsens, with an increasing number of altered connections between brain regions. We observed reduced connectivity in highly associative areas, even in patients with only slight mental slowing. The association of slowed mental processing with loss of connectivity between highly associative areas could be an early marker of cognitive impairment in Parkinson's disease and may contribute to the detection of prodromal forms of Parkinson's disease dementia. Hum Brain Mapp 38:1604-1621, 2017. © 2016 Wiley Periodicals, Inc.