An abnormal resting-state functional brain network indicates progression towards Alzheimer＇s disease

Brain structure and cognitive function change in the temporal lobe,hippocampus,and prefrontal cortex of patients with mild cognitive impairment and Alzheimer’s disease,and brain network-connection strength,network efficiency,and nodal attributes are abnormal.However,existing research has only analyzed the differences between these patients and normal controls.In this study,we constructed brain networks using resting-state functional MRI data that was extracted from four populations(normal controls,patients with early mild cognitive impairment,patients with late mild cognitive impairment,and patients with Alzheimer’s disease)using the Alzheimer’s Disease Neuroimaging Initiative data set.The aim was to analyze the characteristics of resting-state functional neural networks,and to observe mild cognitive impairment at different stages before the transformation to Alzheimer’s disease.Results showed that as cognitive deficits increased across the four groups,the shortest path in the resting-state functional network gradually increased,while clustering coefficients gradually decreased.This evidence indicates that dementia is associated with a decline of brain network efficiency.In addition,the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and Alzheimer’s disease.The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions,and we speculate that early impairments in memory,hearing,and language function can eventually lead to diffuse brain injury and other cognitive impairments.     

A novel method for evaluating brain function and microstructural changes in Parkinson's disease

In this study,microstructural brain damage in Parkinson’s disease patients was examined using diffusion tensor imaging and tract-based spatial statistics.The analyses revealed the presence of neuronal damage in the substantia nigra and putamen in the Parkinson’s disease patients.Moreover,disease symptoms worsened with increasing damage to the substantia nigra,confirming that the substantia nigra and basal ganglia are the main structures affected in Parkinson’s disease.We also found that microstructural damage to the putamen,caudate nucleus and frontal lobe positively correlated with depression.Based on the tract-based spatial statistics,various white matter tracts appeared to have microstructural damage,and this correlated with cognitive disorder and depression.Taken together,our results suggest that diffusion tensor imaging and tract-based spatial statistics can be used to effectively study brain function and microstructural changes in patients with Parkinson’s disease.Our novel findings should contribute to our understanding of the histopathological basis of cognitive dysfunction and depression in Parkinson’s disease.     

Preliminary examination of early neuroconnectivity features in the R6/1 mouse model of Huntington's disease by ultra-high field diffusion MRI

During the last decades,advances in the understanding of genetic,cellular,and microstructural alterations associated to Huntington's disease(HD)have improved the understanding of this progressive and fatal illness.However,events related to early neuropathological events,neuroinflammation,deterioration of neuronal connectivity and compensatory mechanisms still remain vastly unknown.Ultra-high field diffusion MRI(UHFD-MRI)techniques can contribute to a more comprehensive analysis of the early microstructural changes observed in HD.In addition,it is possible to evaluate if early imaging microstructural parameters might be linked to histological biomarkers.Moreover,qualitative studies analyzing histological complexity in brain areas susceptible to neurodegeneration could provide information on inflammatory events,compensatory increase of neuroconnectivity and mechanisms of brain repair and regeneration.The application of ultra-high field diffusion-MRI technology in animal models,particularly the R6/1 mice(a common preclinical mammalian model of HD),provide the opportunity to analyze alterations in a physiologically intact model of the disease.Although some disparities in volumetric changes across different brain structures between preclinical and clinical models has been documented,further application of different diffusion MRI techniques used in combination like diffusion tensor imaging,and neurite orientation dispersion and density imaging have proved effective in characterizing early parameters associated to alteration in water diffusion exchange within intracellular and extracellular compartments in brain white and grey matter.Thus,the combination of diffusion MRI imaging techniques and more complex neuropathological analysis could accelerate the discovery of new imaging biomarkers and the early diagnosis and neuromonitoring of patients affected with HD.     

Disrupted structural and functional brain connectomes in mild cognitive impairment and Alzheimer＇s disease

Alzheimer＇s disease （AD） is the most common type of dementia, comprising an estimated 60-80% of all dementia cases. It is clinically characterized by impairments of memory and other cognitive functions. Previous studies have demonstrated that these impairments are associated with abnormal structural and functional connections among brain regions, leading to a disconnection concept of AD. With the advent of a combination of non-invasive neuroimaging （structural magnetic resonance imaging （MRI）, diffusion MRI, and functional MRI） and neurophysiological techniques （electroencephalography and magnetoencephaJography） with graph theoretical analysis, recent studies have shown that patients with AD and mild cognitive impairment （MCI）, the prodromal stage of AD, exhibit disrupted topological organization in large-scale brain networks （i.e., connectomics） and that this disruption is significantly correlated with the decline of cognitive functions. In this review, we summarize the recent progress of brain connectomics in AD and MCI, focusing on the changes in the topological organization of large-scale structural and functional brain networks using graph theoretical approaches. Based on the two different perspectives of information segregation and integration, the literature reviewed here suggests that AD and MCI are associated with disrupted segregation and integration in brain networks. Thus, these connectomics studies open up a new window for understanding the pathophysiological mechanisms of AD and demonstrate the potential to uncover imaging biomarkers for clinical diagnosis and treatment evaluation for this disease.     

White matter changes in 80 mild cognitive impairment patients using magnetic resonance imaging

BACKGROUND： Many studies have suggested that one possible etiology of mild cognitive impairment is small vessel cerebrovascular disease, which is associated with small subcortical infarcts and white matter abnormalities. These white matter changes have been detected as white matter hyperintensity （WMH） using magnetic resonance imaging. WMH may be associated with frontal lobe dysfunction. OBJECTIVE： To examine white matter changes in mild cognitive impairment patients of different subtypes, and to evaluate the correlation between white matter changes and neuropsychological characteristics, demographic information, vascular risk factors, and mild cognitive impairment subtypes. DESIGN, TIME AND SETTING： The neurophysiological, comparison study was performed at the Department of Neurology Memory Clinic, Ulsan University Hospital, South Korea, between March 2007 and March 2008. PARTICIPANTS： Out of a total of 83 subjects with clinically diagnosed mild cognitive impairment at the out-patient clinic, 3 subjects with severe WMH were excluded. A total of 80 subjects were included in this study. No patients suffered from cognitive impairment induced by neurological diseases, mental disorders, or somatic diseases. In accordance with magnetic resonance imaging results, the patients were assigned to two subtypes： 56 subjects without WMH and 24 subjects with WMH. METHODS： All patients were subjected to a standard neuropsychological battery using the Korean version of the Mini-Mental State Examination, Clinical Dementia Rating, and comprehensive Seoul Neuropsychological Screening Battery. The Clinical Dementia Rating reflected general cognitive function of patients. Results from the Seoul Neuropsychological Screening Battery reflected attention, language function, visuospatial function, verbal memory, nonverbal memory, long-term memory, and frontal/executive function. Magnetic resonance imaging was used to map changes in the brain. MAIN OUTCOME MEASURES： The association between various white matter changes and neuropsychological characteristics, demographic information, vascular risk factors, and mild cognitive impairment subtypes was measured, based primarily on neuropsychological profiles using statistical methods. RESULTS： WMH was significantly associated with neuropsychological characteristics in MCI patients （P 〈 0.05 or P 〈 0.01）, in particular with frontal/executive dysfunction. WMH was significantly correlated with age （P = 0.022） and vascular risk factors （P = 0.006）, independent of gender and MCI subtypes. CONCLUSION： WMH was significantly associated with frontal/executive dysfunction in mild cognitive impairment.     

Can multi-modal neuroimaging evidence from hippocampus provide biomarkers for the progression of amnestic mild cognitive impairment?

Impaired structure and function of the hippocampus is a valuable predictor of progression from amnestic mild cognitive impairment(a MCI) to Alzheimer’s disease(AD). As a part of the medial temporal lobe memory system,the hippocampus is one of the brain regions affected earliest by AD neuropathology,and shows progressive degeneration as a MCI progresses to AD. Currently,no validated biomarkers can precisely predict the conversion from a MCI to AD. Therefore,there is a great need of sensitive tools for the early detection of AD progression. In this review,we summarize the specifi c structural and functional changes in the hippocampus from recent a MCI studies using neurophysiological and neuroimaging data. We suggest that a combination of advanced multi-modal neuroimaging measures in discovering biomarkers will provide more precise and sensitive measures of hippocampal changes than using only one of them. These will potentially affect early diagnosis and disease-modifying treatments. We propose a new sequential and progressive framework in which the impairment spreads from the integrity of fibers to volume and then to function in hippocampal subregions. Meanwhile,this is likely to be accompanied by progressive impairment of behavioral and neuropsychological performance in the progression of a MCI to AD.     

Diffusion tensor imaging assesses white matter injury in neonates with hypoxic-ischemic encephalopathy

With improvements in care of at-risk neonates, more and more children survive. This makes it increasingly important to assess, soon after birth, the prognosis of children with hypoxic-ischemic encephalopathy. Computed tomography, ultrasound, and conventional magnetic resonance imaging are helpful to diagnose brain injury, but cannot quantify white matter damage. In this study, ten full-term infants without brain injury and twenty-two full-term neonates with hypoxic-ischemic encephalopathy (14 moderate cases and 8 severe cases) underwent diffusion tensor imaging to assess its feasibility in evaluating white matter damage in this condition. Results demonstrated that fractional anisotropy, voxel volume, and number of fiber bundles were different in some brain areas between infants with brain injury and those without brain injury. The correlation between fractional anisotropy values and neonatal behavioral neurological assessment scores was closest in the posterior limbs of the internal capsule. We conclude that diffusion tensor imaging can quantify white matter injury in neonates with hypoxic-ischemic encephalopathy.     

Detecting white matter alterations in multiple sclerosis using advanced diffusion magnetic resonance imaging

Multiple sclerosis is a neurodegenerative and inflammatory disease, a hallmark of which is demyelinating lesions in the white matter. We hypothesized that alterations in white matter microstructures can be non-invasively characterized by advanced diffusion magnetic resonance imaging. Seven diffusion metrics were extracted from hybrid diffusion imaging acquisitions via classic diffusion tensor imaging, neurite orientation dispersion and density imaging, and q-space imaging. We investigated the sensitivity of the diffusion metrics in 36 sets of regions of interest in the brain white matter of six female patients(age 52.8 ± 4.3 years) with multiple sclerosis. Each region of interest set included a conventional T2-defined lesion, a matched perilesion area, and normal-appearing white matter. Six patients with multiple sclerosis(n = 5) or clinically isolated syndrome(n = 1) at a mild to moderate disability level were recruited. The patients exhibited microstructural alterations from normal-appearing white matter transitioning to perilesion areas and lesions, consistent with decreased tissue restriction, decreased axonal density, and increased classic diffusion tensor imaging diffusivity. The findings suggest that diffusion compartment modeling and q-spa ce analysis appeared to be sensitive for detecting subtle microstructural alterations between perilesion areas and normal-appearing white matter.     

Abnormal characterization of dynamic functional connectivity in Alzheimer’s disease

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer’s disease(AD)or amnestic mild cognitive impairment(aMCI).However,most studies examined traditional resting state functional connections,ignoring the instantaneous connection mode of the whole brain.In this case-control study,we used a new method called dynamic functional connectivity(DFC)to look for abnormalities in patients with AD and aMCI.We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant,and then used a support vector machine to classify AD patients and normal controls.Finally,we highlighted brain regions and brain networks that made the largest contributions to the classification.We found differences in dynamic function connectivity strength in the left precuneus,default mode network,and dorsal attention network among normal controls,aMCI patients,and AD patients.These abnormalities are potential imaging markers for the early diagnosis of AD.     

Assessment of structural brain changes in patients with type 2 diabetes mellitus using the MRI-based brain atrophy and lesion index

Patients with type 2 diabetes mellitus(T2 DM) often have cognitive impairment and structural brain abnormalities.The magnetic resonance imaging(MRI)-based brain atrophy and lesion index can be used to evaluate common brain changes and their correlation with cognitive function,and can therefore also be used to reflect whole-brain structural changes related to T2 DM.A total of 136 participants(64 men and 72 women,aged 55–86 years) were recruited for our study between January 2014 and December 2016.All participants underwent MRI and Mini-Mental State Examination assessment(including 42 healthy control,38 T2 DM without cognitive impairment,26 with cognitive impairment but without T2 DM,and 30 T2 DM with cognitive impairment participants).The total and sub-category brain atrophy and lesion index scores in patients with T2 DM with cognitive impairment were higher than those in healthy controls.Differences in the brain atrophy and lesion index of gray matter lesions and subcortical dilated perivascular spaces were found between non-T2 DM patients with cognitive impairment and patients with T2 DM and cognitive impairment.After adjusting for age,the brain atrophy and lesion index retained its capacity to identify patients with T2 DM with cognitive impairment.These findings suggest that the brain atrophy and lesion index,based on T1-weighted and T2-weighted imaging,is of clinical value for identifying patients with T2 DM and cognitive impairment.Gray matter lesions and subcortical dilated perivascular spaces may be potential diagnostic markers of T2 DM that is complicated by cognitive impairment.This study was approved by the Medical Ethics Committee of University of South China(approval No.USC20131109003) on November 9,2013,and was retrospectively registered with the Chinese Clinical Trial Registry(registration No.Chi CTR1900024150) on June 27,2019.     

Magnetic resonance imaging: A biomarker for cognitive impairment in Parkinson's disease?

Dementia is a frequent and disabling complication of Parkinson's disease (PD). Clinicians and researchers lack a biomarker capable of tracking the structural and functional changes that underlie the evolution of cognitive dysfunction in PD. Magnetic resonance imaging (MRI) has been adopted as a biomarker in natural history and interventional studies of Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI), but its utility as a biomarker for PD and Parkinson's disease dementia (PDD) is unclear. In this review, the authors summarize the studies that have used MRI to investigate cognitive decline in PD, outline limitations of those studies, and suggest directions for future research. PD dementia is associated with extensive cortical atrophy, which may be quantified with structural MRI. More promisingly, patterns of atrophy may be present in those who have PD with MCI (PD‐MCI). Subcortical white matter tract degeneration is detectable early in the disease with diffusion tensor imaging and may precede changes observed on conventional structural MRI. Although less well studied, other MR techniques, such as functional MRI, MR perfusion imaging with arterial spin labeling, and MR spectroscopy, have demonstrated differences in activation and metabolism between PD and PDD. In this review, the ability to compare studies was limited by the heterogeneity of study populations, cognitive testing methods, and imaging protocols. Future work should adopt agreed scan protocols, should be adequately powered, and should use carefully phenotyped patients to fully maximize the contribution of MRI as a biomarker for PDD. © 2013 Movement Disorder Society     

Automated Classification to Predict the Progression of Alzheimer's Disease Using Whole-Brain Volumetry and DTI

Objective

This study proposes an automated diagnostic method to classify patients with Alzheimer''s disease (AD) of degenerative etiology using magnetic resonance imaging (MRI) markers.

Methods

Twenty-seven patients with subjective memory impairment (SMI), 18 patients with mild cognitive impairment (MCI), and 27 patients with AD participated. MRI protocols included three dimensional brain structural imaging and diffusion tensor imaging to assess the cortical thickness, subcortical volume and white matter integrity. Recursive feature elimination based on support vector machine (SVM) was conducted to determine the most relevant features for classifying abnormal regions and imaging parameters, and then a factor analysis for the top-ranked factors was performed. Subjects were classified using nonlinear SVM.

Results

Medial temporal regions in AD patients were dominantly detected with cortical thinning and volume atrophy compared with SMI and MCI patients. Damage to white matter integrity was also accredited with decreased fractional anisotropy and increased mean diffusivity (MD) across the three groups. The microscopic damage in the subcortical gray matter was reflected in increased MD. Classification accuracy between pairs of groups (SMI vs. MCI, MCI vs. AD, SMI vs. AD) and among all three groups were 84.4% (±13.8), 86.9% (±10.5), 96.3% (±4.6), and 70.5% (±11.5), respectively.

Conclusion

This proposed method may be a potential tool to diagnose AD pathology with the current clinical criteria.     

Diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease: a review

PURPOSE OF REVIEW: To provide a comprehensive review of diffusion tensor imaging in evaluating microstructural changes in the spectrum of cognitive decline from ageing to Alzheimer's disease, in particular focusing on mild cognitive impairment. RECENT FINDINGS: Mild cognitive impairment represents a transition phase between normal ageing and early Alzheimer's disease. Diffusion tensor imaging has emerged as a useful imaging modality that provides information about the structural integrity of tissue. In healthy ageing, diffusion tensor imaging abnormalities occur in the frontal regions, specifically the frontal white matter, anterior cingulum and the genu of the corpus callosum. Some studies report an anterior-posterior gradient change with greater abnormalities in the genu than the splenium of the corpus callosum and in the frontal than parietal white matter. In Alzheimer's disease, diffusion tensor imaging abnormalities are concentrated in the posterior regions: the parahippocampal gyrus, temporal white matter, splenium of corpus callosum and posterior cingulum. In mild cognitive impairment, changes seem to parallel those in Alzheimer's disease, with similar posterior regions showing abnormalities. SUMMARY: Due to the similarities in diffusion tensor imaging findings in both mild cognitive impairment and Alzheimer's disease, it is likely that diffusion tensor imaging has the potential to emerge as a useful clinical tool for early detection and monitoring of disease progression and treatment response in mild cognitive impairment/Alzheimer's disease patients.     

The Role of Diffusion Tensor Imaging in Detecting Microstructural Changes in Prodromal Alzheimer's Disease

The MRI technique diffusion tensor imaging (DTI) is reviewed along with microstructural changes associated with prodromal Alzheimer's disease (AD) as a potential biomarker for clinical applications. The prodromal stage of AD is characterized by mild cognitive impairment (MCI), representing a transitional state between normal aging and AD. Microstructural abnormalities on DTI are promising in vivo biomarkers of gray and white matter changes associated with the progression of AD pathology. Elevated mean diffusivity and decreased fractional anisotropy are consistently found in prodromal AD, and even in cognitively normal elderly who progress to MCI. However, quality of parameter maps may be affected by artifacts of motion, susceptibility, and eddy current‐induced distortions. The DTI maps are typically analyzed by region‐of‐interest or voxel‐based analytic techniques such as tract‐based spatial statistics. DTI‐based index of diffusivity is complementary to macrostructural gray matter changes in the hippocampus in detecting prodromal AD. Breakdown of structural connectivity measured with DTI may impact cognitive performance during early AD. Furthermore, assessment of hippocampal connections may help in understanding the cerebral organization and remodeling associated with treatment response.     

The role of MRI in dementia

Neuroimaging techniques aimed at studying structural changes of the brain may provide useful information for the diagnosis and the clinical management of patients with dementia. Magnetic resonance imaging (MRI) may show abnormalities amenable to surgical treatment in a significant percentage of patients with cognitive impairment. MRI may also assist the differential diagnosis in dementia associated with metabolic or inflammatory diseases.MRI has the potential to detect focal signal abnormalities which may assist the clinical differentiation between Alzheimer's disease (AD) and vascular dementia (VaD). Severe temporal atrophy, hyperintensities involving the hippocampal or insular cortex, and gyral hypointense bands are more frequently noted in AD. Basal ganglionic/thalamic hyperintense foci, thromboembolic infarctions, confluent white matter and irregular periventricular hyperintensities are more common in VaD.The high sensitivity of MRI in detecting T2 hyperintense lesions and the low specificity off white matter lesions have resulted in a poor correlation between MRI findings and both neuropathological and clinical manifestations. In particular, MRI has disclosed a series of white matter focal changes in the elderly population, which are not necessarily associated with cognitive dysfunction.The recent advent of a new MRI method sensitive to the microstructural changes of white matter, the so-called diffusion tensor imaging, may be helpful in correlating clinical manifestations with white matter abnormalities.     

Amyloid burden accelerates white matter degradation in cognitively normal elderly individuals

Alterations in parietal and temporal white matter microstructure derived from diffusion tensor imaging occur in preclinical and clinical Alzheimer's disease. Amyloid beta (Aβ) deposition and such white matter alterations are two pathological hallmarks of Alzheimer's disease. However, the relationship between these pathologies is not yet understood, partly since conventional diffusion MRI methods cannot distinguish between cellular and extracellular processes. Thus, we studied Aβ‐associated longitudinal diffusion MRI changes in Aβ‐positive (N = 21) and Aβ‐negative (N = 51) cognitively normal elderly obtained from the Alzheimer's Disease Neuroimaging Initiative dataset using linear mixed models. Aβ‐positivity was based on Alzheimer's Disease Neuroimaging Initiative amyloid‐PET recommendations using a standardized uptake value ratio cut‐off of 1.11. We used free‐water imaging to distinguish cellular and extracellular changes. We found that Aβ‐positive subjects had increased baseline right uncinate fasciculus free‐water fraction (FW), associated with worse baseline Alzheimer's disease assessment scale scores. Furthermore, Aβ‐positive subjects showed faster decrease in fractional anisotropy (FW‐corrected) in the right uncinate fasciculus and faster age‐dependent right inferior longitudinal fasciculus FW increases over time. Right inferior longitudinal fasciculus FW increases were associated with greater memory decline. Importantly, these results remained significant after controlling for gray and white matter volume and hippocampal volume. This is the first study to illustrate the influence of Aβ burden on early longitudinal (in addition to baseline) white matter changes in cognitively normal elderly individuals at‐risk of Alzheimer's disease, thus underscoring the importance of longitudinal studies in assessing microstructural alterations in individuals at risk of Alzheimer's disease prior to symptoms onset.     

Neuroimaging tools to rate cognitive impairment

Various neuroimaging techniques have been employed to detect the subtle brain changes related to mild cognitive impairment (MCI) and Alzheimer's disease (AD). Current areas of interest in neuroimaging include the detection of predictive indicators, prognostic values and the effects of treatment, as well as the features of disease. In this article, the findings of structural studies, functional imagings and white matter lesions in MCI are reviewed. Several cases of MCI are presented, and the usefulness of neuroimaging in the prediction of the treatment course and prognosis of MCI is evaluated.     

血管性认知障碍的结构影像学研究进展

血管性认知障碍(vascular cognitive impairment,VCI)是一类由脑血管病危险因素或脑血管病引起的从轻度认知障碍到痴呆的综合征,脑血管病本身可以出现相应的脑影像学改变,这些病变和认知损伤的关系研究结论尚不统一。VCI的结构影像学研究主要采用结构磁共振成像(magnetic resonance imaging,MRI)、弥散加权成像和弥散张量成像技术,分别从卒中位置、大脑形态学及大脑白质结构等方面研究VCI引起的大脑微观结构变化及其与认知之间的关系。本文回顾了利用结构影像学对VCI的研究进展。     

卒中后轻度认知功能障碍与脑白质病变的研究

脑白质病变,在影像学中又称为脑白质疏松症,是脑微血管病变的一种重要类型。有大量研究表明,卒中后轻度认知功能障碍与脑白质病变存在明显的相关性。弥散张量成像对白质纤维的显示具有一定的优势,成为卒中后认知功能障碍研究的重要工具。本文对近年来卒中后认知功能障碍与脑白质病变的相关研究予以综述。     

Color discrimination deficits in Parkinson's disease are related to cognitive impairment and white‐matter alterations

Color discrimination deficit is a common nonmotor manifestation of Parkinson's disease (PD). However, the pathophysiology of this dysfunction remains poorly understood. Although retinal structure changes found in PD have been suggested to cause color discrimination deficits, the impact of cognitive impairment and cortical alterations remains to be determined. We investigated the contribution of cognitive impairment to color discrimination deficits in PD and correlated them with cortical anomalies. Sixty‐six PD patients without dementia and 20 healthy controls performed the Farnsworth–Munsell 100 hue test and underwent a comprehensive neuropsychological assessment for mild cognitive impairment diagnosis. In a subgroup of 26 PD patients, we also used high‐definition neuroanatomical magnetic resonance imaging for cortical thickness and diffusion tensor analysis. PD patients with mild cognitive impairment performed poorly on the Farnsworth–Munsell 100 hue test compared with PD patients without mild cognitive impairment and controls. In PD patients, performance on the Farnsworth–Munsell 100 hue test was correlated with measures of visuospatial abilities and executive functions. Neuroimaging analysis revealed higher mean and radial diffusivity values in right posterior white‐matter structures that correlated with poor performance on the Farnsworth–Munsell 100 hue test. No cortical thickness correlation reached significance. This study showed that cognitive impairment makes a major contribution to the color discrimination deficits reported in PD. Thus, performance on the Farnsworth–Munsell 100 hue test may reflect cognitive impairment more than color discrimination deficits in PD. Poor performance on the Farnsworth–Munsell 100 hue test was also associated with white‐matter alterations in right posterior brain regions. © 2012 Movement Disorder Society