Thalamic projection fiber integrity in de novo Parkinson disease

Altered Thalamocortical Signaling in a Mouse Model of Parkinson's Disease

Activation of the primary motor cortex (M1) is important for the execution of skilled movements and motor learning, and its dysfunction contributes to the pathophysiology of Parkinson's disease (PD). A well-accepted idea in PD research, albeit not tested experimentally, is that the loss of midbrain dopamine leads to decreased activation of M1 by the motor thalamus. Here, we report that midbrain dopamine loss altered motor thalamus input in a laminar- and cell type-specific fashion and induced laminar-specific changes in intracortical synaptic transmission. Frequency-dependent changes in synaptic dynamics were also observed. Our results demonstrate that loss of midbrain dopaminergic neurons alters thalamocortical activation of M1 in both male and female mice, and provide novel insights into circuit mechanisms for motor cortex dysfunction in a mouse model of PD.SIGNIFICANCE STATEMENT Loss of midbrain dopamine neurons increases inhibition from the basal ganglia to the motor thalamus, suggesting that it may ultimately lead to reduced activation of primary motor cortex (M1). In contrast with this line of thinking, analysis of M1 activity in patients and animal models of Parkinson's disease report hyperactivation of this region. Our results are the first report that midbrain dopamine loss alters the input-output function of M1 through laminar and cell type specific effects. These findings support and expand on the idea that loss of midbrain dopamine reduces motor cortex activation and provide experimental evidence that reconciles reduced thalamocortical input with reports of altered activation of motor cortex in patients with Parkinson's disease.

Fiber-specific white matter alterations in Parkinson's disease patients with freezing of gait

Freezing of gait (FOG) is a gait disorder that usually occurs in advanced stages of Parkinson's disease (PD). Understanding the underlying mechanism of FOG is important for treatment and prevention. Previous studies have investigated white matter (WM) structure to explore the pathology of FOG. However, the pathology is still unclear, possibly due to the methodological limitation in identifying specific fiber tracts. This study aimed to investigate tract-specific WM structural changes in FOG patients and their relationships with clinical characteristics. We enrolled 19 PD patients with FOG (PD-FOG), 19 without FOG (PD-woFOG) and 21 controls. Fixel-based analysis is a novel framework to avoid the effect of crossing fibers, which provides the metrics to assess WM morphology. By combining a method for segmenting fibers, we identified abnormalities in the specific fiber tracts. Compared to PD-woFOG, PD-FOG showed significant increased fiber-bundle cross-section (FC) in the corpus callosum (CC), fornix (FX), inferior longitudinal fasciculus (ILF), striato-premotor (ST_PREM), superior thalamic radiation (STR), thalamo-premotor (T_PREM), increased fiber density and cross-section (FDC) in the STR, and decreased fiber density (FD) in the CC and ILF. Additionally, the ILF was correlated with motor, cognition and memory, the CC was correlated with anxiety, and the T_PREM was also correlated with cognition. In conclusion, in addition to impairments of WM found in PD-FOG, we found enhancements in WM, which may imply compensatory mechanisms. Furthermore, multiple fiber tracts were correlated with clinical characteristics, especially the ILF, validating the involvement of transmission circuits of multiple distinct information in mechanisms of FOG.

In Vivo Super-Resolution Track-Density Imaging for Thalamic Nuclei Identification

The development of novel techniques for the in vivo, non-invasive visualization and identification of thalamic nuclei has represented a major challenge for human neuroimaging research in the last decades. Thalamic nuclei have important implications in various key aspects of brain physiology and many of them show selective alterations in various neurologic and psychiatric disorders. In addition, both surgical stimulation and ablation of specific thalamic nuclei have been proven to be useful for the treatment of different neuropsychiatric diseases. The present work aimed at describing a novel protocol for histologically guided delineation of thalamic nuclei based on short-tracks track-density imaging (stTDI), which is an advanced imaging technique exploiting high angular resolution diffusion tractography to obtain super-resolved white matter maps. We demonstrated that this approach can identify up to 13 distinct thalamic nuclei bilaterally with very high inter-subject (ICC: 0.996, 95% CI: 0.993-0.998) and inter-rater (ICC:0.981; 95% CI:0.963-0.989) reliability, and that both subject-based and group-level thalamic parcellation show a fair share of similarity to a recent standard-space histological thalamic atlas. Finally, we showed that stTDI-derived thalamic maps can be successfully employed to study structural and functional connectivity of the thalamus and may have potential implications both for basic and translational research, as well as for presurgical planning purposes.

Increasing Serotonin to Reduce Parkinsonian Tremor

While current dopamine-based drugs seem to be effective for most Parkinson's disease (PD) motor dysfunctions, they produce variable responsiveness for resting tremor. This lack of consistency could be explained by considering recent evidence suggesting that PD resting tremor can be divided into different partially overlapping phenotypes based on the dopamine response. These phenotypes may be associated with different pathophysiological mechanisms produced by a cortical-subcortical network involving even non-dopaminergic areas traditionally not directly related to PD. In this study, we propose a bio-constrained computational model to study the neural mechanisms underlying a possible type of PD tremor: the one mainly involving the serotoninergic system. The simulations run with the model demonstrate that a physiological serotonin increase can partially recover dopamine levels at the early stages of the disease before the manifestation of overt tremor. This result suggests that monitoring serotonin concentration changes could be critical for early diagnosis. The simulations also show the effectiveness of a new pharmacological treatment for tremor that acts on serotonin to recover dopamine levels. This latter result has been validated by reproducing existing data collected with human patients.

Dopaminergic and Serotonergic Degeneration and Cortical [18 F]Fluorodeoxyglucose Positron Emission Tomography in De Novo Parkinson's Disease

BACKGROUND

Degeneration of the nigrostriatal dopaminergic (DA) and the raphe-thalamic serotonergic (SE) systems is among the earliest changes observed in Parkinson's disease (PD). The consequences of those changes on brain metabolism, especially regarding their impact on the cortex, are poorly understood.

OBJECTIVES

Using multi-tracer molecular imaging, we assessed in a cohort of drug-naive PD patients the association between cortical metabolism and DA and SE system deafferentation of either striatum or thalamus, and we explored whether this association was mediated by either striatum or thalamus metabolism.

METHODS

We recruited 96 drug-naive PD patients (aged 71.9 ± 7.5 years) who underwent [¹²³ I]ioflupane single-photon emission computed tomography ([¹²³ I]FP-CIT-SPECT) and brain [¹⁸ F]fluorodeoxyglucose positron emission tomography ([¹⁸ F]FDG-PET). We used a voxel-wise analysis of [¹⁸ F]FDG-PET images to correlate regional metabolism with striatal DA and thalamic SE innervation as assessed using [¹²³ I]FP-CIT-SPECT.

RESULTS

We found that [¹²³ I]FP-CIT specific to nondisplaceable binding ratio (SBR) and glucose metabolism positively correlated with one another in the deep gray matter (thalamus: P = 0.001, r = 0.541; caudate P = 0.001, r = 0.331; putamen P = 0.001, r = 0.423). We then observed a direct correlation between temporoparietal metabolism and caudate DA innervation, as well as a direct correlation between prefrontal metabolism and thalamus SE innervation. The effect of caudate [¹²³ I]FP-CIT SBR values on temporoparietal metabolism was mediated by caudate metabolic values (percentage mediated: 89%, P-value = 0.008), and the effect of thalamus [¹²³ I]FP-CIT SBR values on prefrontal metabolism was fully mediated by thalamus metabolic values (P < 0.001).

CONCLUSIONS

These data suggest that the impact of deep gray matter monoaminergic deafferentation on cortical function is mediated by striatal and thalamic metabolism in drug-naive PD. © 2021 International Parkinson and Movement Disorder Society.

Brain White-Matter Degeneration Due to Aging and Parkinson Disease as Revealed by Double Diffusion Encoding

Microstructure imaging by means of multidimensional diffusion encoding is increasingly applied in clinical research, with expectations that it yields a parameter that better correlates with clinical disability than current methods based on single diffusion encoding. Under the assumption that diffusion within a voxel can be well described by a collection of diffusion tensors, several parameters of this diffusion tensor distribution can be derived, including mean size, variance of sizes, orientational dispersion, and microscopic anisotropy. The information provided by multidimensional diffusion encoding also enables us to decompose the sources of the conventional fractional anisotropy and mean kurtosis. In this study, we explored the utility of the diffusion tensor distribution approach for characterizing white-matter degeneration in aging and in Parkinson disease by using double diffusion encoding. Data from 23 healthy older subjects and 27 patients with Parkinson disease were analyzed. Advanced age was associated with greater mean size and size variances, as well as smaller microscopic anisotropy. By analyzing the parameters underlying diffusion kurtosis, we found that the reductions of kurtosis in aging and Parkinson disease reported in the literature are likely driven by the reduction in microscopic anisotropy. Furthermore, microscopic anisotropy correlated with the severity of motor impairment in the patients with Parkinson disease. The present results support the use of multidimensional diffusion encoding in clinical studies and are encouraging for its future clinical implementation.

Diffusion Tensor Imaging in Parkinson's Disease and Parkinsonian Syndrome: A Systematic Review

Diffusion tensor imaging (DTI) allows measuring fractional anisotropy and similar microstructural indices of the brain white matter. Lower than normal fractional anisotropy as well as higher than normal diffusivity is associated with loss of microstructural integrity and neurodegeneration. Previous DTI studies in Parkinson's disease (PD) have demonstrated abnormal fractional anisotropy in multiple white matter regions, particularly in the dopaminergic nuclei and dopaminergic pathways. However, DTI is not considered a diagnostic marker for the earliest Parkinson's disease since anisotropic alterations present a temporally divergent pattern during the earliest Parkinson's course. This article reviews a majority of clinically employed DTI studies in PD, and it aims to prove the utilities of DTI as a marker of diagnosing PD, correlating clinical symptomatology, tracking disease progression, and treatment effects. To address the challenge of DTI being a diagnostic marker for early PD, this article also provides a comparison of the results from a longitudinal, early stage, multicenter clinical cohort of Parkinson's research with previous publications. This review provides evidences of DTI as a promising marker for monitoring PD progression and classifying atypical PD types, and it also interprets the possible pathophysiologic processes under the complex pattern of fractional anisotropic changes in the first few years of PD. Recent technical advantages, limitations, and further research strategies of clinical DTI in PD are additionally discussed.

Investigation of local white matter abnormality in Parkinson's disease by using an automatic fiber tract parcellation

The deficits of white matter (WM) microstructure are involved during Parkinson's disease (PD) progression. Most current methods identify key WM tracts relying on cortical regions of interest (ROIs). However, such ROI methods can be challenged due to low diffusion anisotropy near the gray matter (GM), which could result in a low sensitivity of tract identification. This work proposes an automatic WM parcellation method to improve the accuracy of WM tract identification and locate abnormal tracts by using sensitive features. The proposed method consists of 1) whole brain WM parcellation using an established fiber clustering method, without using any ROIs, 2) features of fasciculus were calculated to quantify diffusion measures at each equal cross-section along the whole cluster. Then, we use the proposed features to investigate the WM difference in PD compared with healthy controls (HC). We also use these features to investigate the relationship of clinical symptoms and specific fiber tracts. The novelty of the proposed method is that it automatically identifies the abnormal WM fibers in cluster degree. Experiment results indicated that the proposed method had advantage in detecting the local WM abnormality by performing between-group statistical analysis in 30 patients with PD and 28 HC. We found 13 hemisphere clusters and 8 commissural clusters had significant group difference (p < 0.05, corrected by FDR method) in local regions, which belonged to multiple fiber tracts including cingulum bundle (CB), inferior occipito-frontal fasciculus (IoFF), corpus callosum (CC), external capsule (EC), uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and thalamo front (TF). We also found clusters that had relevance with clinical indices of cognitive function (2 clusters), athletic function (6 clusters), and depressive state (2 clusters) in these significant clusters. From the experiment results, it confirmed the ability of the proposed method to identify potential WM microstructure abnormality.

Structural brain changes in Ser129-phosphorylated alpha-synuclein rats based on voxel-based morphometry

Parkinson's disease has become one of the most common neurodegenerative diseases. Pathological changes typically manifest following dopaminergic neuron loss in the substantia nigra and abnormal alpha-synuclein (α-syn) aggregation in the neurons. α-Syn is the major component of Lewy bodies. However, research pertaining to the spread of abnormal α-syn aggregations, which results in specific damage to the brain structure and function, is lacking. In the present study, full-length human α-syn fibrils were injected into the medial forebrain bundle of rats, with an experimental endpoint of 6 months. Histological analysis was conducted to observe the pathological progress of abnormal endogenous α-syn aggregation and nerve fiber quality. Changes in gray and white matter integrity were quantitatively analyzed using voxel-based morphometry (VBM). Behavioral changes were observed over the 6-month period. Histological analysis showed reduced dopamine transporter levels in the striatum of the experimental rats; widespread abnormal endogenous α-syn accumulation; and damaged, sparse, and disordered nerve fibers in the experimental group. VBM showed that at 6 months after surgery, bilateral anterior limbic, bilateral inferior limbic, right hippocampal, and right cortical volumes had reduced, whereas thalamic volume had increased in the experimental group compared with that in the control group. Damage to the limbic and thalamic fiber structure may occur in the earlier stages of Parkinson's disease.

Breathing new life into neurotoxic-based monkey models of Parkinson's disease to study the complex biological interplay between serotonin and dopamine

Numerous clinical studies have shown that the serotonergic system also degenerates in patients with Parkinson's disease. The causal role of this impairment in Parkinson's symptomatology and the response to treatment remains to be refined, in particular thanks to approaches allowing the two components DA and 5-HT to be isolated if possible. We have developed a macaque monkey model of Parkinson's disease exhibiting a double lesion (dopaminergic and serotonergic) thanks to the sequential use of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) and MDMA (3,4-methylenedioxy-N-methamphetamine) (or MDMA prior MPTP). We characterized this monkey model by multimodal imaging (PET, positron emission tomography with several radiotracers; DTI, diffusion tensor imaging), behavioral assessments (parkinsonism, dyskinesia, neuropsychiatric-like behavior) and post-mortem analysis (with DA and 5-HT markers). When administrated after MPTP, MDMA damaged the 5-HT presynaptic system without affecting the remaining DA neurons. The lesion of 5-HT fibers induced by MDMA altered rigidity and prevented dyskinesia and neuropsychiatric-like symptoms induced by levodopa therapy in MPTP-treated animals. Interestingly also, prior MDMA administration aggravates the parkinsonian deficits and associated DA injury. Dystonic postures, action tremor and global spontaneous activities were significantly affected. All together, these data clearly indicate that late or early lesions of the 5-HT system have a differential impact on parkinsonian symptoms in the macaque model of Parkinson's disease. Whether MDMA has an impact on neuropsychiatric-like symptoms such as apathy, anxiety, depression remains to be addressed. Despite its limitations, this toxin-based double-lesioned monkey model takes on its full meaning and provides material for the experimental study of the heterogeneity of patients.

NfL as a biomarker for neurodegeneration and survival in Parkinson disease

OBJECTIVE

To determine whether neurofilament light chain protein in CSF (cNfL), a sensitive biomarker of neuroaxonal damage, reflects disease severity or can predict survival in Parkinson disease (PD).

METHODS

We investigated whether disease severity, phenotype, or survival in patients with new-onset PD correlates with cNfL concentrations around the time of diagnosis in the population-based New Parkinsonism in Umeå (NYPUM) study cohort (n = 99). A second, larger new-onset PD cohort (n = 194) was used for independent validation. Association of brain pathology with the cNfL concentration was examined with striatal dopamine transporter imaging and repeated diffusion tensor imaging at baseline and 1 and 3 years.

RESULTS

Higher cNfL in the early phase of PD was associated with greater severity of all cardinal motor symptoms except tremor in both cohorts and with shorter survival and impaired olfaction. cNfL concentrations above the median of 903 ng/L conferred an overall 5.8 times increased hazard of death during follow-up. After adjustment for age and sex, higher cNfL correlated with striatal dopamine transporter uptake deficits and lower fractional anisotropy in diffusion tensor imaging of several axonal tracts.

CONCLUSIONS

cNfL shows usefulness as a biomarker of disease severity and to predict survival in PD. The present results indicate that the cNfL concentration reflects the intensity of the neurodegenerative process, which could be important in future clinical trials.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that in patients with PD, cNfL concentrations are associated with more severe disease and shorter survival.

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest–based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease

To meet the need for Parkinson's disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson's disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson's disease patients and 54 healthy controls) were collected using b-values of 0-4000s/mm2. Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm2 (fractional anisotropy (FA), Axial-, Mean- and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson's disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson's disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.

Loss of glutamate signaling from the thalamus to dorsal striatum impairs motor function and slows the execution of learned behaviors

Parkinson’s disease (PD) is primarily associated with the degeneration of midbrain dopamine neurons, but it is now appreciated that pathological processes like Lewy-body inclusions and cell loss affect several other brain regions, including the central lateral (CL) and centromedian/parafascicular (CM/PF) thalamic regions. These thalamic glutamatergic neurons provide a non-cortical excitatory input to the dorsal striatum, a major projection field of dopamine neurons. To determine how thalamostriatal signaling may contribute to cognitive and motor abnormalities found in PD, we used a viral vector approach to generate mice with loss of thalamostriatal glutamate signaling specifically restricted to the dorsal striatum (CAV2^Cre-Slc17a6^lox/lox mice). We measured motor function and behaviors corresponding to cognitive domains (visuospatial function, attention, executive function, and working memory) affected in PD. CAV2^Cre-Slc17a6^lox/lox mice were impaired in motor coordination tasks such as the rotarod and beam-walk tests compared with controls (CAV2^Cre-Slc17a6^+/+ mice). They did not demonstrate much cognitive impairment in the Morris water maze or a water U-maze, but had slower processing reaction times in those tests and in a two-way active avoidance task. These mice could model an aspect of bradyphrenia, the slowness of thought that is often seen in patients with PD and other neurological disorders.

Mice in which glutamate signaling from the thalamus to dorsal striatum has been genetically inactivated mimic the slowness of thought that is often observed in patients with Parkinson’s disease (PD). The midbrain and striatum are the brain regions that are most affected in PD, however, it is increasingly recognized that cell loss in other areas of the brain also contribute to disease symptoms. Martin Darvas at the University of Washington, Seattle, USA, and colleagues found that disrupting the excitatory input from thalamic projection neurons into the dorsal striatum affected motor coordination and balance in mice. Although these mice did not have significant impairments in spatial learning and memory, they were slower at reacting to cues and executing learned behaviors suggesting that they could be used to test new approaches for treating this specific cognitive symptom of PD.

Determination of Imaging Biomarkers to Decipher Disease Trajectories and Differential Diagnosis of Neurodegenerative Diseases (DIsease TreND)

BACKGROUND

Understanding disease progression of neurodegenerative diseases (NDs) is important for better prognosis and decisions on the appropriate course of treatment to slow down the disease progression.

NEW METHOD

We present here an innovative machine learning framework capable of (1) indicating the trajectory of disease progression by identifying relevant imaging biomarkers and (2) automated disease diagnosis. Self-Organizing Maps (SOM) have been used for data dimensionality reduction and to reveal potentially useful disease-specific biomarkers, regions of interest (ROIs). These ROIs have been used for automated disease diagnosis using Least Square Support Vector Machines (LS-SVM) and to delineate disease progression.

RESULTS

A multi-site, multi-scanner dataset containing 1316 MRIs was obtained from ADNI³ and PPMI. Identified biomarkers have been used to decipher (1) trajectory of disease progression and (2) identify clinically relevant ROIs. Furthermore, we have obtained a classification accuracy of 94.29 ± 0.08% and 95.37 ± 0.02% for distinguishing AD and PD from HC subjects respectively.

COMPARISON WITH OTHER EXISTING METHODS

The goal of this study was fundamentally different from other machine learning based studies for automated disease diagnosis. We aimed to develop a method that has two-fold benefits (1) It can be used to understand pathology of neurodegenerative diseases and (2) It also achieves automated disease diagnosis.

CONCLUSIONS

In the absence of established disease biomarkers, clinical diagnosis is heavily prone to misdiagnosis. Being clinically relevant and readily adaptable in the current clinical settings, the developed framework could be a stepping stone to make machine learning based Clinical Decision Support System (CDSS) for neurodegenerative disease diagnosis a reality.

Changes in sensorimotor-related thalamic diffusion properties and cerebrospinal fluid hydrodynamics predict gait responses to tap test in idiopathic normal-pressure hydrocephalus

OBJECTIVES

To compare diffusion tensor (DT)-derived indices from the thalamic nuclei and cerebrospinal fluid (CSF) hydrodynamic parameters for the prediction of gait responsiveness to the CSF tap test in early iNPH patients.

METHODS

In this study, 22 patients with iNPH and 16 normal controls were enrolled with the approval of an institutional review board. DT imaging and phase-contrast magnetic resonance imaging were performed in patients and controls to determine DT-related indices of the sensorimotor-related thalamic nuclei and CSF hydrodynamics. Gait performance was assessed in patients using gait scale before and after the tap test. The Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis were applied to compare group differences between patients and controls and assess the predictive performance of gait responsiveness to the tap test in the patients.

RESULTS

Fractional anisotropy (FA) and axial diffusivity showed significant increases in the ventrolateral (VL) and ventroposterolateral (VPL) nuclei of the iNPH group compared with those of the control group (p < 0.05). The predictions of gait responsiveness of ventral thalamic FA alone (area under the ROC curve [AUC] < 0.8) significantly outperformed those of CSF hydrodynamics alone (AUC < 0.6). The AUC curve was elevated to 0.812 when the CSF peak systolic velocity and FA value were combined for the VPL nucleus, yielding the highest sensitivity (0.769) and specificity (0.778) to predict gait responses.

CONCLUSIONS

Combined measurements of sensorimotor-related thalamic FA and CSF hydrodynamics can provide potential biomarkers for gait response to the CSF tap test in patients with iNPH.

KEY POINTS

• Ventrolateral and ventroposterolateral thalamic FA may predict gait responsiveness to tap test. • Thalamic neuroplasticity can be assessed through DTI in idiopathic normal-pressure hydrocephalus. • Changes in the CST associated with gait control could trigger thalamic neuroplasticity. • Activities of sensorimotor-related circuits could alter in patients with gait disturbance. • Management of patients with iNPH could be more appropriate.

Substantia Nigra Free Water Increases Longitudinally in Parkinson Disease

BACKGROUND AND PURPOSE

Free water in the posterior substantia nigra obtained from a bi-tensor diffusion MR imaging model has been shown to significantly increase over 1- and 4-year periods in patients with early-stage idiopathic Parkinson disease compared with healthy controls, which suggests that posterior substantia nigra free water may be an idiopathic Parkinson disease progression biomarker. Due to the known temporal posterior-to-anterior substantia nigra degeneration in idiopathic Parkinson disease, we assessed longitudinal changes in free water in both the posterior and anterior substantia nigra in patients with later-stage idiopathic Parkinson disease and age-matched healthy controls for comparison.

MATERIALS AND METHODS

Nineteen subjects with idiopathic Parkinson disease and 19 age-matched healthy control subjects were assessed on the same 3T MR imaging scanner at baseline and after approximately 3 years.

RESULTS

Baseline mean idiopathic Parkinson disease duration was 7.1 years. Both anterior and posterior substantia nigra free water showed significant intergroup differences at baseline (P < .001 and P = .014, respectively, idiopathic Parkinson disease versus healthy controls); however, only anterior substantia nigra free water showed significant longitudinal group × time interaction increases (P = .021, idiopathic Parkinson disease versus healthy controls). There were no significant longitudinal group × time interaction differences found for conventional diffusion tensor imaging or free water-corrected DTI assessments in either the anterior or posterior substantia nigra.

CONCLUSIONS

Results from this study provide further evidence supporting substantia nigra free water as a promising disease-progression biomarker in idiopathic Parkinson disease that may help to identify disease-modifying therapies if used in future clinical trials. Our novel finding of longitudinal increases in anterior but not posterior substantia nigra free water is potentially a result of the much longer disease duration of our cohort compared with previously studied cohorts and the known posterior-to-anterior substantia nigra degeneration that occurs over time in idiopathic Parkinson disease.

Serotonin transporter binding and anxiety symptoms in Parkinson's disease

BACKGROUND

Anxiety is a common neuropsychiatric symptom in Parkinson's disease (PD), yet the neural mechanisms have been scarcely investigated. Disturbances in dopaminergic and serotonergic signalling may play a role in its pathophysiology. ¹²³I-N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane (¹²³I-FP-CIT) is a single-photon emission CT radiotracer, and its binding in striatal and extrastriatal subcortical brain areas represents predominant binding to the presynaptic dopamine transporter (DAT) and the serotonin transporter (SERT), respectively. Availability of DAT and SERT may thus provide an in vivo measure for the integrity of both dopamine and serotonin neurons.

METHODS

We studied the association between anxiety symptoms, measured with an affective subscale of the Beck Anxiety Inventory, and (extra)striatal ¹²³I-FP-CIT binding in 127 non-demented patients with PD with a median disease duration of 2.55 (IQR 2.90) years. We conducted the analyses on patients currently on or not on dopamine replacement therapy (DRT).

RESULTS

Severity of anxiety symptoms showed a significant negative association with ¹²³I-FP-CIT binding ratios in the right thalamus (β=-0.203, p=0.019; ΔR²=0.040) (multiple testing p_corr <0.020). In the subgroup of patients not on DRT (n=81), we found a significant negative association between anxiety and thalamic ¹²³I-FP-CIT binding ratios bilaterally (right: β=-0.349, p=0.001, ΔR²=0.119; left: β=-0.269, p=0.017, ΔR²=0.071) (p_corr <0.020).

CONCLUSION

This study shows that higher levels of anxiety in patients with PD are associated with lower thalamic ¹²³I-FP-CIT binding, pointing towards a contribution of serotonergic degeneration to anxiety symptoms in PD.

Analysis of white matter characteristics with tract-based spatial statistics according to diffusion tensor imaging in early Parkinson's disease

OBJECTIVE

To analyze the microstructure of brain white matter according to diffusion tensor imaging (DTI) based on tract-based spatial statistics (TBSS) in early Parkinson's disease (PD).

MATERIALS AND METHODS

A total of 31 age- and sex-matched early PD patients and 22 healthy volunteers were recruited in the present study. DTI was performed, and the data analyzed with fsl4.0 software. The fractional anisotropy (FA) was compared between both groups with an independent t test, and the differential area was analyzed. White matter fiber tracts with significant difference in FA between the two groups were selected, and their FAs were measured. Pearson's correlation analysis was employed to analyze the unified Parkinson's disease rating scale (UPDRS) score and its association with FA of different tracts.

RESULTS

When compared with healthy volunteers, early PD patients had reduced FA in the following areas: bilateral anterior corona radiate, upper corona radiate, fasciculus arcuatus, crus anterius capsulae internae, crus posterius capsulae internae, capsula externa, posterior thalamic radiation, optic radiation, sagittal layer (including fasciculus arcuatus and inferior fronto-occipital fasciculus), crura fornicis, stria terminalis, fornix, genu, body and pad of corpus callosum, left unciform fasciculus, right cingulate bundle, right medipeduncle, and arcuate fibers in the bilateral frontal, temporal, and occipital lobes (P < 0.05). When compared with healthy volunteers, early PD patients showed abnormal FA of fasciculus in the white matter mainly in following areas: bilateral crus anterius capsulae internae, bilateral capsula externa, right anterior corona radiate, body and pad of bilateral corpus callosum, and left sagittal layer (including fasciculi longitudinalis inferior and fasciculus occipitofrontalis inferior) (P < 0.05). In addition, in early PD patients, the UPDRS score and movement score had no relationship with the FA of different fasciculi in the white matter (P > 0.05).

CONCLUSION

There is wide alteration of white matter microstructure in early PD patients, which is characterized by disruption of projection fibers in the descending pathway, limbic system-related fasciculi, corpus callosum, thalamus after radiation, posterior thalamic radiation, Gratiolet's bundle and other fasciculi in the white matter.

Biomarkers for Parkinson's Disease: Recent Advancement

As a multi-factorial degenerative disease, Parkinson's disease (PD) leads to tremor, gait rigidity, and hypokinesia, thus hampering normal living. As this disease is usually detected in the later stages when neurons have degenerated completely, cure is on hold, ultimately leading to death due to the lack of early diagnostic techniques. Thus, biomarkers are required to detect the disease in the early stages when prevention is possible. Various biomarkers providing early diagnosis of the disease include those of imaging, cerebrospinal fluid, oxidative stress, neuroprotection, and inflammation. Also, biomarkers, alone or in combination, are used in the diagnosis and evolution of PD. This review encompasses various biomarkers available for PD and discusses recent advances in their development.

Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study

This study aimed to identify the utility of diffusion tensor imaging (DTI) in measuring the regional distribution of abnormal microstructural progression in patients with Parkinson’s disease who were enrolled in the Parkinson's progression marker initiative (PPMI). One hundred and twenty two de-novo PD patients (age = 60.5±9) and 50 healthy controls (age = 60.6±11) had DTI scans at baseline and 12.6±1 months later. Automated image processing included an intra-subject registration of all time points and an inter-subjects registration to a brain atlas. Annualized rates of DTI variations including fractional anisotropy (FA), radial (rD) and axial (aD) diffusivity were estimated in a total of 118 white matter and subcortical regions of interest. A mixed effects model framework was used to determine the degree to which DTI changes differed in PD relative to changes in healthy subjects. Significant DTI changes were also tested for correlations with changes in clinical measures, dopaminergic imaging and CSF biomarkers in PD patients. Compared to normal aging, PD was associated with higher rates of FA reduction, rD and aD increases predominantly in the substantia nigra, midbrain and thalamus. The highest rates of FA reduction involved the substantia nigra (3.6±1.4%/year from baseline, whereas the highest rates of increased diffusivity involved the thalamus (rD: 8.0±2.9%/year, aD: 4.0±1.5%/year). In PD patients, high DTI changes in the substantia nigra correlated with increasing dopaminergic deficits as well as with declining α-synuclein and total tau protein concentrations in cerebrospinal fluid. Increased DTI rates in the thalamus correlated with progressive decline in global cognition in PD. The results suggest that higher rates of regional microstructural degeneration are potential markers of PD progression.

A Bayesian approach to fiber orientation estimation guided by volumetric tract segmentation

Diffusion magnetic resonance imaging (dMRI) provides information about the microstructure of white matter in the human brain. From dMRI, streamlining tractography is often used to reconstruct computational representations of white matter tracts from which differences in structural connectivity can be explored. In the fiber tracking process, anatomical information can help reduce tracking errors caused by crossing fibers and image noise. In this paper, we propose a Bayesian method for estimating fiber orientations (FOs) guided by anatomical tract information using diffusion tensor imaging (DTI), which is a standard clinical and research dMRI protocol. The proposed method is named Fiber Orientation Reconstruction guided by Tract Segmentation (FORTS). A first step segments and labels the white matter tracts volumetrically, including explicit representations of crossing regions. A second step estimates the FOs using the diffusion information and the anatomical knowledge from segmented white matter tracts. A single FO is estimated in the noncrossing regions while two FOs are estimated in the crossing regions. A third step carries out streamlining tractography that uses information from both the segmented tracts and the estimated FOs. Experiments performed on a digital crossing phantom, a physical phantom, and brain DTI of 18 healthy subjects show that FORTS is able to use the anatomical information to produce FOs with better accuracy and to reduce anatomically incorrect streamlines. In particular, on the brain DTI data, we studied the connectivity of anatomically defined tracts to cortical areas, which is not straightforwardly achievable using only volumetric tract segmentation. These connectivity results demonstrate the potential application of FORTS to scientific studies.

Depiction of dentatorubrothalamic tract fibers in patients with Parkinson's disease and multiple sclerosis in deep brain stimulation

BACKGROUND

We wanted to depict fibers of the dentatorubrothalamic tract in patients with Parkinson's disease and multiple sclerosis in order to use this knowledge for clinical routine and to show its relation to the corticospinal tract for deep brain stimulation. Fibers of these white matter tracts were depicted between February 2014 and February 2015 in nine patients of all ages. There were seven men and two women. The mean age was 60 years. We used a 3DT1 sequence for the navigation. Additional scanning time was less than 9 min. Both tracts were portrayed in all patients.

RESULTS

We were able to successfully portray these white matter tracts in all patients. We visualized the medial and lateral parts of the corticospinal tract by using a region of interest which covered the whole motor cortex. Furthermore we segmented the motor cortex. The fibers ran from this area of the brain through the internal capsule and they could be followed until their entry in the brainstem. The dentatorubrothalamic tract was smaller than the corticospinal tract. It was situated medio-posteriorly of the corticospinal tract. After decussation to the contralateral red nucleus it was localised next to the midline when it entered the motor cortex. From the thalamus on, it proceeds medially and posteriorly of the corticospinal tract further to the motor cortex. Depiction of the whole tract is essential for the differentiation of the dentatorubrothalamic tract with the corticospinal tract.

CONCLUSIONS

The depiction of the dentatorubrothalamic tract might be useful for neurosurgeons when deep brain stimulation is planned. Knowing its relation to other white matter tracts can help physicians like neurosurgeons or neurologists avoid side effects and deal with patients with DBS. The position of the electrode might be crucial for a satisfactory outcome.

Alterations of Diffusion Kurtosis and Neurite Density Measures in Deep Grey Matter and White Matter in Parkinson's Disease

In Parkinson’s disease (PD), pathological microstructural changes occur and such changes might be detected using diffusion magnetic resonance imaging (dMRI). However, it is unclear whether dMRI improves PD diagnosis or helps differentiating between phenotypes, such as postural instability gait difficulty (PIGD) and tremor dominant (TD) PD. We included 105 patients with PD and 44 healthy controls (HC), all of whom underwent dMRI as part of the prospective Swedish BioFINDER study. Diffusion kurtosis imaging (DKI) and neurite density imaging (NDI) analyses were performed using regions of interest in the basal ganglia, the thalamus, the pons and the midbrain as well as tractography of selected white matter tracts. In the putamen, the PD group showed increased mean diffusivity (MD) (p = .003), decreased fractional anisotropy (FA) (p = .001) and decreased mean kurtosis (MK), compared to HC (p = .024). High MD and a low MK in the putamen were associated with more severe motor and cognitive symptomatology (p < .05). Also, patients with PIGD exhibited increased MD in the putamen compared to the TD patients (p = .009). In the thalamus, MD was increased (p = .001) and FA was decreased (p = .032) in PD compared to HC. Increased MD and decreased FA correlated negatively with motor speed and balance (p < .05). In the superior longitudinal fasciculus (SLF), MD (p = .019) and f_iso were increased in PD compared to HC (p = .03). These changes correlated negatively with motor speed (p < .002) and balance (p < .037). However, most of the observed changes in PD were also present in cases with either multiple system atrophy (n = 11) or progressive supranuclear palsy (n = 10). In conclusion, PD patients exhibit microstructural changes in the putamen, the thalamus, and the SLF, which are associated with worse disease severity. However, the dMRI changes are not sufficiently specific to improve the diagnostic work-up of PD. Longitudinal studies should evaluate whether dMRI measures can be used to track disease progression.

Basal ganglia and cerebellar interconnectivity within the human thalamus

Basal ganglia and the cerebellum are part of a densely interconnected network. While both subcortical structures process information in basically segregated loops that primarily interact in the neocortex, direct subcortical interaction has been recently confirmed by neuroanatomical studies using viral transneuronal tracers in non-human primate brains. The thalamus is thought to be the main relay station of both projection systems. Yet, our understanding of subcortical basal ganglia and cerebellar interconnectivity within the human thalamus is rather sparse, primarily due to limitation in the acquisition of in vivo tracing. Consequently, we strive to characterize projections of both systems and their potential overlap within the human thalamus by diffusion MRI and tractography. Our analysis revealed a decreasing anterior-to-posterior gradient for pallido-thalamic connections in: (1) the ventral-anterior thalamus, (2) the intralaminar nuclei, and (3) midline regions. Conversely, we found a decreasing posterior-to-anterior gradient for dentato-thalamic projections predominantly in: (1) the ventral-lateral and posterior nucleus; (2) dorsal parts of the intralaminar nuclei and the subparafascicular nucleus, and (3) the medioventral and lateral mediodorsal nucleus. A considerable overlap of connectivity pattern was apparent in intralaminar nuclei and midline regions. Notably, pallidal and cerebellar projections were both hemispherically lateralized to the left thalamus. While strikingly consistent with findings from transneuronal studies in non-human primates as well as with pre-existing anatomical studies on developmentally expressed markers or pathological human brains, our assessment provides distinctive connectional fingerprints that illustrate the anatomical substrate of integrated functional networks between basal ganglia and the cerebellum. Thereby, our findings furnish useful implications for cerebellar contributions to the clinical symptomatology of movement disorders.

Neuroanatomical changes in Parkinson's disease in relation to cognition: An update

The pathophysiological changes underlying impairment of cognition in Parkinson's disease (PD) are complex and not fully understood till date. Hence, understanding the structural changes responsible for cognitive decline in PD is essential for early diagnosis and to offer effective treatment. In this review, we discuss the neuroanatomical changes in major brain structures responsible for cognition in PD. We have included the key findings of various studies to provide up-to-date information for better understanding of pathophysiology of PD, which will help researchers and clinicians in planning and developing new treatment methods for the benefit of PD patients.

Unsupervised learning based feature extraction for differential diagnosis of neurodegenerative diseases: A case study on early-stage diagnosis of Parkinson disease

BACKGROUND

The development of MRI based methods could prove extremely valuable for identification of reliable biomarkers to aid diagnosis of neurodegenerative diseases (NDs). A great deal of current research has been aimed at identification biomarkers for both diagnosis at early stage and evaluation of the progression of NDs.

NEW METHOD

We present here a novel synergetic paradigm integrating Kohonen self organizing map (KSOM) and least squares support vector machine (LS-SVM) for individual-level clinical diagnosis of NDs. Feature are extracted in an unsupervised manner using KSOM on preprocessed brain MRIs. Thereafter, these features are fed as input to LSSVM for subject classification.

RESULTS

The applicability of the proposed methodology has been demonstrated using 831 T1-weighted MRIs obtained from Parkinson's Progression Markers Initiative (PPMI) database. We have achieved classification accuracy of up to 99% for differential diagnosis of Parkinson disease with confidence interval of 99.9%.

COMPARISON WITH OTHER EXISTING METHODS

The potential for translation of similar research findings to clinical application is greatly dependent upon two factors (1) accuracy of subject classification achieved and (2) size of the dataset used. Here, we report very high accuracy achieved on one of the largest MRI datasets using multivariate analysis tools.

CONCLUSIONS

In this paper, we describe a methodology that has the potential to be translated into first-line diagnostic tool for NDs. We also demonstrate the applicability of this methodology for diagnosing PD subjects in early stages of the disease, i.e., subjects in age of 31-60 years.

Microstructural effects of Ramadan fasting on the brain: a diffusion tensor imaging study

PURPOSE

We aimed to examine whether the brain displays any microstructural changes after a three-week Ramadan fasting period using diffusion tenson imaging.

METHODS

This study included a study and a control group of 25 volunteers each. In the study group, we examined and compared apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values of the participants during (phase 1) and after (phase 2) a period of fasting. The control group included individuals who did not fast. ADC and FA values obtained in phase 1 and phase 2 were compared between the study and control groups.

RESULTS

In the study group, ADC values of hypothalamus and, to a lesser extent, of insula were lower in phase 1 compared with phase 2 and the control group. The FA values of amygdala, middle temporal cortex, thalamus and, to a lesser extent, of medial prefrontal cortex were lower in phase 1 compared with phase 2 and the control group. Phase 2 ADC and FA values of the study group were not significantly different compared with the control group at any brain location.

CONCLUSION

A three-week Ramadan fasting period can cause microstructural changes in the brain, and diffusion tensor imaging enables the visualization of these changes. The identification of brain locations where changes occurred in ADC and FA values during fasting can be helpful in diagnostic imaging and understanding the pathophysiology of eating disorders.

Reduced topological efficiency in cortical-basal Ganglia motor network of Parkinson's disease: a resting state fMRI study

Parkinson's disease (PD) is mainly characterized by dopamine depletion of the cortico-basal ganglia (CBG) motor circuit. Given that dopamine dysfunction could affect functional brain network efficiency, the present study utilized resting-state fMRI (rs-fMRI) and graph theoretical approach to investigate the topological efficiency changes of the CBG motor network in patients with PD during a relatively hypodopaminergic state (12 hours after a last dose of dopamimetic treatment). We found that PD compared with controls had remarkable decreased efficiency in the CBG motor network, with the most pronounced changes observed in rostral supplementary motor area (pre-SMA), caudal SMA (SMA-proper), primary motor cortex (M1), primary somatosensory cortex (S1), thalamus (THA), globus pallidus (GP), and putamen (PUT). Furthermore, reduced efficiency in pre-SMA, M1, THA and GP was significantly correlated with Unified Parkinson's Disease Rating Scale (UPDRS) motor scores in PD patients. Together, our results demonstrate that individuals with PD appear to be less effective at information transfer within the CBG motor pathway, which provides a novel perspective on neurobiological explanation for the motor symptoms in patients. These findings are in line with the pathophysiology of PD, suggesting that network efficiency metrics may be used to identify and track the pathology of PD.

MRI reveals brain abnormalities in drug-naive Parkinson's disease

Most brain studies of Parkinson's disease (PD) focus on patients who are already taking antiparkinsonian medication. This makes it difficult to isolate the effects of disease from those of treatment. We review magnetic resonance imaging evidence supporting the hypothesis that early-stage untreated PD patients have structural and functional abnormalities in the brain, some of which are related to motor symptoms.

Mapping track density changes in nigrostriatal and extranigral pathways in Parkinson's disease

In Parkinson's disease (PD) the demonstration of neuropathological disturbances in nigrostriatal and extranigral brain pathways using magnetic resonance imaging remains a challenge. Here, we applied a novel diffusion-weighted imaging approach-track density imaging (TDI). Twenty-seven non-demented Parkinson's patients (mean disease duration: 5 years, mean score on the Hoehn & Yahr scale=1.5) were compared with 26 elderly controls matched for age, sex, and education level. Track density images were created by sampling each subject's spatially normalized fiber tracks in 1mm isotropic intervals and counting the fibers that passed through each voxel. Whole-brain voxel-based analysis was performed and significance was assessed with permutation testing. Statistically significant increases in track density were found in the Parkinson's patients, relative to controls. Clusters were distributed in disease-relevant areas including motor, cognitive, and limbic networks. From the lower medulla to the diencephalon and striatum, clusters encompassed the known location of the locus coeruleus and pedunculopontine nucleus in the pons, and from the substantia nigra up to medial aspects of the posterior putamen, bilaterally. The results identified in brainstem and nigrostriatal pathways show a large overlap with the known distribution of neuropathological changes in non-demented PD patients. Our results also support an early involvement of limbic and cognitive networks in Parkinson's disease.

The evolving role of diffusion magnetic resonance imaging in movement disorders

Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson's disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington's disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.

Vestibular insights into cognition and psychiatry

The vestibular system has traditionally been thought of as a balance apparatus; however, accumulating research suggests an association between vestibular function and psychiatric and cognitive symptoms, even when balance is measurably unaffected. There are several brain regions that are implicated in both vestibular pathways and psychiatric disorders. The present review examines the anatomical associations between the vestibular system and various psychiatric disorders. Despite the lack of direct evidence for vestibular pathology in the key psychiatric disorders selected for this review, there is a substantial body of literature implicating the vestibular system in each of the selected psychiatric disorders. The second part of this review provides complimentary evidence showing the link between vestibular dysfunction and vestibular stimulation upon cognitive and psychiatric symptoms. In summary, emerging research suggests the vestibular system can be considered a potential window for exploring brain function beyond that of maintenance of balance, and into areas of cognitive, affective and psychiatric symptomology. Given the paucity of biological and diagnostic markers in psychiatry, novel avenues to explore brain function in psychiatric disorders are of particular interest and warrant further exploration.

Specific frequency band of amplitude low-frequency fluctuation predicts Parkinson's disease

Resting-state functional magnetic resonance imaging (RS-fMRI) has been considered for development as a biomarker and analytical tool for evaluation of Parkinson's disease (PD). Here we utilized analysis of the amplitude low-frequency fluctuations (ALFF) to determine changes in intrinsic neural oscillations in 72 patients with PD. Two different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz) were analyzed. In the slow-5 band, PD patients compared with controls had increased ALFF values mainly in the caudate and several temporal regions, as well as decreased ALFF values in the cerebellum and the parieto-temporo-occipital cortex. Additionally, in the slow-4 band, PD patients relative to controls exhibited reduced ALFF value in the thalamus, cerebellum, and several occipital regions. Together, our data demonstrate that PD patients have widespread abnormal intrinsic neural oscillations in the corticostriatal network in line with the pathophysiology of PD, and further suggest that the abnormalities are dependent on specific frequency bands. Thus, frequency domain analyses of resting state BOLD signals may provide a useful means to study the pathophysiology of PD and the physiology of the brain's dopaminergic pathways.