Revised Temperament and Character Inventory factors predict neuropsychiatric symptoms and aging-related cognitive decline across 25 years.

Introduction: Personality traits and neuropsychiatric symptoms such as neuroticism and depression share genetic overlap and have both been identified as risks factors for development of aging-related neurocognitive decline and Alzheimer's disease (AD). This study aimed to examine revised personality factors derived from the Temperament and Character Inventory, previously shown to be associated with psychiatric disorders, as predictors of neuropsychiatric, cognitive, and brain trajectories of participants from a population-based aging study. Methods: Mixed-effect linear regression analyses were conducted on data for the full sample (Nmax = 1,286), and a healthy subsample not converting to AD-dementia during 25-year follow-up (Nmax = 1,145), complemented with Cox proportional regression models to determine risk factors for conversion to clinical AD. Results: Two personality factors, Closeness to Experience (CE: avoidance of new stimuli, high anxiety, pessimistic anticipation, low reward seeking) and Tendence to Liabilities (TL: inability to change, low autonomy, unaware of the value of their existence) were associated with higher levels of depressive symptoms, stress (CE), sleep disturbance (TL), as well as greater decline in memory, vocabulary and verbal fluency in the full sample. Higher CE was additionally associated with greater memory decline across 25 years in the healthy subsample, and faster right hippocampal volume reduction across 8 years in a neuroimaging subsample (N = 216). Most, but not all, personality-cognition associations persisted after controlling for diabetes, hypertension and cardiovascular disease. Concerning risks for conversion to AD, higher age, and APOE-ε4, but none of the personality measures, were significant predictors. Conclusion: The results indicate that personality traits associated with psychiatric symptoms predict accelerated age-related neurocognitive declines even in the absence of neurodegenerative disease. The attenuation of some personality effects on cognition after adjustment for health indicators suggests that those effects may be partly mediated by somatic health. Taken together, the results further emphasize the importance of personality traits in neurocognitive aging and underscore the need for an integrative (biopsychosocial) perspective of normal and pathological age-related cognitive decline.

Longitudinal brain structure changes in Parkinson's disease: A replication study.

CONTEXT: An existing major challenge in Parkinson's disease (PD) research is the identification of biomarkers of disease progression. While magnetic resonance imaging is a potential source of PD biomarkers, none of the magnetic resonance imaging measures of PD are robust enough to warrant their adoption in clinical research. This study is part of a project that aims to replicate 11 PD studies reviewed in a recent survey (JAMA neurology, 78(10) 2021) to investigate the robustness of PD neuroimaging findings to data and analytical variations. OBJECTIVE: This study attempts to replicate the results in Hanganu et al. (Brain, 137(4) 2014) using data from the Parkinson's Progression Markers Initiative (PPMI). METHODS: Using 25 PD subjects and 18 healthy controls, we analyzed the rate of change of cortical thickness and of the volume of subcortical structures, and we measured the relationship between structural changes and cognitive decline. We compared our findings to the results in the original study. RESULTS: (1) Similarly to the original study, PD patients with mild cognitive impairment (MCI) exhibited increased cortical thinning over time compared to patients without MCI in the right middle temporal gyrus, insula, and precuneus. (2) The rate of cortical thinning in the left inferior temporal and precentral gyri in PD patients correlated with the change in cognitive performance. (3) There were no group differences in the change of subcortical volumes. (4) We did not find a relationship between the change in subcortical volumes and the change in cognitive performance. CONCLUSION: Despite important differences in the dataset used in this replication study, and despite differences in sample size, we were able to partially replicate the original results. We produced a publicly available reproducible notebook allowing researchers to further investigate the reproducibility of the results in Hanganu et al. (2014) when more data is added to PPMI.

Prediction of cognitive decline in healthy aging based on neuropsychiatric symptoms and PET-biomarkers of Alzheimer's disease.

Neuropsychiatric symptoms (NPS) have been associated with a risk of accelerated cognitive decline or conversion to dementia of the Alzheimer's Disease (AD) type. Moreover, the NPS were also associated with higher AD biomarkers (brain tau and amyloid burden) even in non-demented patients. But the effect of the relationship between NPS and biomarkers on cognitive decline has not yet been studied. This work aims to assess the relationship between longitudinal cognitive changes and NPS, specifically depression and anxiety, in association with AD biomarkers in healthy middle-aged to older participants. The cohort consisted of 101 healthy participants aged 50-70 years, 66 of whom had neuropsychological assessments of memory, executive functions, and global cognition at a 2-year follow-up. At baseline, NPS were assessed using the Beck Depression and Anxiety Inventories while brain tau and amyloid loads were measured using positron emission topography. For tau burden, THK5351 uptake is used as a proxy of tau and neuroinflammation. Participants, declining or remaining stable at follow-up, were categorized into groups for each cognitive domain. Group classification was investigated using binary logistic regressions based on combined AD biomarkers and the two NPS. The results showed that an association between anxiety and prefrontal amyloid burden significantly classified episodic memory decline, while the classification of global cognitive decline involved temporal and occipital amyloid burden but not NPS. Moreover, depression together with prefrontal and hippocampal tau burden were associated with a decline in memory. The classification of participants based on executive decline was related to depression and mainly prefrontal tau burden. These findings suggest that the combination of NPS and brain biomarkers of AD predicts the occurrence of cognitive decline in aging.

Associations Between Hyperactive Neuropsychiatric Symptoms and Brain Morphology in Mild Cognitive Impairment and Alzheimer's Disease.

BACKGROUND: Hyperactive neuropsychiatric symptoms (NPS) (i.e., agitation, disinhibition, and irritability) are among the most challenging symptoms to manage in Alzheimer's disease (AD). However, their underlying brain correlates have been poorly studied. OBJECTIVE: We aimed to investigate the associations between the total score of hyperactive NPS and brain structures in participants with AD, mild cognitive impairment (MCI), and cognitively normal older adults (CN). METHODS: Neuropsychiatric and 3T MRI data from 216 AD, 564 MCI, and 660 CN participants were extracted from the Alzheimer's Disease Neuroimaging Initiative database. To define NPS and brain structures' associations, we fitted a general linear model (GLM) in two ways: 1) an overall GLM including all three groups (AD, MCI, CN) and 2) three pair-wise GLMs (AD versus MCI, MCI versus CN, AD versus CN). The cortical changes as a function of NPS total score were investigated using multiple regression analyses. RESULTS: Results from the overall GLM include associations between 1) agitation and the right parietal supramarginal surface area in the MCI-CN contrast, 2) disinhibition and the cortical thickness of the right frontal pars opercularis and temporal inferior in the AD-MCI contrast, and 3) irritability and the right frontal pars opercularis, frontal superior, and temporal superior volumes in the MCI-CN contrast. CONCLUSIONS: Our study shows that each hyperactive NPS is associated with distinct brain regions in AD, MCI, and CN (groups with different levels of cognitive performance). This suggests that each NPS is associated with a unique signature of brain morphology, including variations in volume, thickness, or area.

Machine learning-based prediction of longitudinal cognitive decline in early Parkinson's disease using multimodal features.

Patients with Parkinson's Disease (PD) often suffer from cognitive decline. Accurate prediction of cognitive decline is essential for early treatment of at-risk patients. The aim of this study was to develop and evaluate a multimodal machine learning model for the prediction of continuous cognitive decline in patients with early PD. We included 213 PD patients from the Parkinson's Progression Markers Initiative (PPMI) database. Machine learning was used to predict change in Montreal Cognitive Assessment (MoCA) score using the difference between baseline and 4-years follow-up data as outcome. Input features were categorized into four sets: clinical test scores, cerebrospinal fluid (CSF) biomarkers, brain volumes, and genetic variants. All combinations of input feature sets were added to a basic model, which consisted of demographics and baseline cognition. An iterative scheme using RReliefF-based feature ranking and support vector regression in combination with tenfold cross validation was used to determine the optimal number of predictive features and to evaluate model performance for each combination of input feature sets. Our best performing model consisted of a combination of the basic model, clinical test scores and CSF-based biomarkers. This model had 12 features, which included baseline cognition, CSF phosphorylated tau, CSF total tau, CSF amyloid-beta1-42, geriatric depression scale (GDS) scores, and anxiety scores. Interestingly, many of the predictive features in our model have previously been associated with Alzheimer's disease, showing the importance of assessing Alzheimer's disease pathology in patients with Parkinson's disease.

Associations between neuropsychiatric symptoms of affective and vegetative domains and brain morphology in aging people with mild cognitive impairment and Alzheimer's disease.

OBJECTIVE: Neuropsychiatric symptoms (NPS) are common in mild cognitive impairment (MCI) and even more in Alzheimer's disease (AD). The symptom-based cluster including nighttime disturbances, depression, appetite changes, anxiety, and apathy (affective and vegetative symptoms) was associated with an increased risk of dementia in MCI and has common neuroanatomical associations. Our objective was to investigate the differences in brain morphology associations with affective and vegetative symptoms between three groups: cognitively normal older adults (CN), MCI and AD. MATERIAL AND METHODS: Alzheimer's Disease Neuroimaging Initiative data of 223 CN, 367 MCI and 175 AD, including cortical volumes, surface areas and thicknesses and severity scores of the five NPS were analyzed. A whole-brain vertex-wise general linear model was performed to test for intergroup differences (CN-MCI, CN-AD, AD-MCI) in brain morphology associations with five NPS. Multiple regressions were conducted to investigate cortical change as a function of NPS severity in the AD-MCI contrast. RESULTS: We found (1) signature differences in nighttime disturbances associations with prefrontal regions in AD-MCI, (2) signature differences in NPS associations with temporal regions in AD-MCI for depression and in CN-AD for anxiety, (3) decreased temporal metrics in MCI as nighttime disturbances and depression severity increased, (4) decreased pars triangularis metrics in AD as nighttime disturbances and apathy severity increased. CONCLUSION: Each NPS seems to have a signature on brain morphology. Affective and vegetative NPS were primarily associated with prefrontal and temporal regions. These signatures open the possibility of potential future assessments of links between brain morphology and NPS on an individual level.

Motor symptoms in Parkinson's disease are related to the interplay between cortical curvature and thickness.

INTRODUCTION: Brain atrophy in Parkinson's disease occurs to varying degrees in different brain regions, even at the early stage of the disease. While cortical morphological features are often considered independently in structural brain imaging studies, research on the co-progression of different cortical morphological measurements could provide new insights regarding the progression of PD. This study's aim was to examine the interplay between cortical curvature and thickness as a function of PD diagnosis, motor symptoms, and cognitive performance. METHODS: A total of 359 de novo PD patients and 159 healthy controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) database were included in this study. Additionally, an independent cohort from four databases (182 PD, 132 HC) with longer disease durations was included to assess the effects of PD diagnosis in more advanced cases. Pearson correlation was used to determine subject-specific associations between cortical curvature and thickness estimated from T1-weighted MRI images. General linear modeling (GLM) was then used to assess the effect of PD diagnosis, motor symptoms, and cognitive performance on the curvature-thickness association. Next, longitudinal changes in the curvature-thickness correlation as well as the predictive effect of the cortical curvature-thickness association on changes in motor symptoms and cognitive performance across four years were investigated. Finally, Akaike information criterion (AIC) was used to build a GLM to model PD motor symptom severity cross-sectionally. RESULTS: A significant interaction effect between PD motor symptoms and age on the curvature-thickness correlation was found (ßstandardized = 0.11; t(350) = 2.12; p = 0.03). This interaction effect showed that motor symptoms in older patients were related to an attenuated curvature-thickness association. No significant effect of PD diagnosis was observed for the PPMI database (ß = 0.03; t(510) = 0.35; p = 0.72). However, in patients with a longer disease duration, a significant effect of diagnosis on the curvature-thickness association was found (ßstandardized = 0.31; t(306.7) = 3.49; p = 0.0006). Moreover, rigidity, but not tremor, in PD was significantly related to the curvature-thickness correlation (ßstandardized = 0.11, t(350) = 2.24, p = 0.03; ßstandardized = -0.03, t(350) = -0.58, p = 0.56, respectively). The curvature-thickness association was attenuated over time in both PD and HC, but the two groups did not show a significantly different effect (ßstandardized = 0.03, t(184.7) = 0.78, p = 0.44). No predictive effects of the CC-CT correlation on longitudinal changes in cognitive performance or motor symptoms were observed (all p-values > 0.05). The best cross-sectional model for PD motor symptoms included the curvature-thickness correlation, cognitive performance, and putamen dopamine transporter (DAT) binding, which together explained 14 % of variance. CONCLUSION: The association between cortical curvature and thickness is related to PD motor symptoms and age. This research shows the potential of modeling the curvature-thickness interplay in PD.

Establishing an individualized model of conversion from normal cognition to Alzheimer's disease after 4 years, based on cognitive, brain morphology and neuropsychiatric characteristics.

OBJECTIVES: The impact of neuropsychiatric symptoms (NPS) on cognitive performance has been reported, and this impact was better defined in the aging population. Yet the potential of using the impact of NPS on brain and cognitive performance in a longitudinal setting, as prediction of conversion - have remained questionable. This study proposes to establish a predictive model of conversion to Alzheimer's disease (AD) and mild cognitive impairment (MCI) based on current cognitive performance, NPS and their associations with brain morphology. METHODS: 156 participants with MCI from the Alzheimer's Disease Neuroimaging Initiative database cognitively stable after a 4-year follow-up were compared to 119 MCI participants who converted to AD. Each participant underwent a neuropsychological assessment evaluating verbal memory, language, executive and visuospatial functions, a neuropsychiatric inventory evaluation and a 3 Tesla MRI. The statistical analyses consisted of 1) baseline comparison between the groups; 2) analysis of covariance model (controlling demographic parameters including functional abilities) to specify the variables that distinguish the two subgroups and; 3) used the significant ANCOVA variables to construct a binary logistic regression model that generates a probability equation to convert to a lower cognitive performance state. RESULTS: Results showed that MCI who converted to AD in comparison to stable MCI, exhibited a higher NPS prevalence, a lower cognitive performance and a higher number of involved brain structures. Functional abilities, memory performance and the sizes of inferior temporal, hippocampal and amygdala sizes were significant predictors of MCI to AD conversion. We also report two models of conversion that can be implemented on an individual basis for calculating the percentage risk of conversion after 4 years. CONCLUSION: These analytical methods might be a good way to anticipate cognitive and brain declines.

Action fluency identifies different sex, age, global cognition, executive function and brain activation profile in non-demented patients with Parkinson's disease.

Patients with Parkinson's disease (PD) have difficulties processing action words, which could be related to early cognitive decline. The action fluency test can be used to quickly and easily assess the processing of action words in PD. The goal of this study was to characterize how the action fluency test relates to personal characteristics, disease factors, cognition, and neural activity in PD. Forty-eight participants with PD (34 male, 14 female) and 35 control participants (16 male, 19 female) completed functional neuroimaging using a set-shifting task and a neuropsychological assessment including the action fluency test. PD participants with a score one standard deviation below the norm or lower on the action fluency test were identified. All PD participants with poor performance (PD-P, n = 15) were male. They were compared to male PD participants with scores within the normal range (PD-N, n = 19) and male healthy controls (HC, n = 16). PD-P were older, had lower global cognition scores, lower executive functions scores, and decreased activity in fronto-temporal regions compared with PD-N. There was no difference between the two PD groups in terms of the duration of the disease, dose of dopaminergic medication, and severity of motor symptoms. PD-N were younger than HC, but there was no other significant difference between these groups. The action fluency test identified a subgroup of PD patients with distinct sex, age, global cognition, executive functions, and brain activity characteristics. Implications for the evaluation of cognition are discussed.

Theta-Burst Stimulation for Cognitive Enhancement in Parkinson's Disease With Mild Cognitive Impairment: A Randomized, Double-Blind, Sham-Controlled Trial.

Background: Mild cognitive impairment is a common non-motor symptom of Parkinson's disease (PD-MCI) and has minimal treatment options. Objective: In this double-blind, randomized, sham-controlled trial, we assessed the effect of repeated sessions of intermittent theta-burst stimulation over the left dorsolateral prefrontal cortex on cognition and brain connectivity in subjects with PD-MCI. Methods: Forty-one subjects were randomized to receive real (n = 21) or sham stimulation (n = 20). All subjects underwent neuropsychological assessments before, 1 day, and 1 month after stimulation. Subjects also underwent resting-state functional magnetic resonance imaging before and 48 h after stimulation. The primary outcome was the change in the cognitive domain (executive function, attention, memory, language, and visuospatial abilities) z-scores across time. Results: There was an insignificant effect on cognitive domain z-scores across time when comparing real with sham stimulation and correcting for multiple comparisons across cognitive domains (p > 0.05 Bonferroni correction). However, the real stimulation group demonstrated a trend toward improved executive functioning scores at the 1-month follow-up compared with sham (p < 0.05 uncorrected). After real stimulation, the connectivity of the stimulation site showed decreased connectivity to the left caudate head. There was no change in connectivity within or between the stimulation network (a network of cortical regions connected to the stimulation site) and the striatal network. However, higher baseline connectivity between the stimulation network and the striatal network was associated with improved executive function scores at 1 month. Conclusions: These results suggest that intermittent theta-burst stimulation over the dorsolateral prefrontal cortex in subjects with PD-MCI has minimal effect on cognition compared with sham, although there were trends toward improved executive function. This intervention may be more effective in subjects with higher baseline connectivity between the stimulation network and the striatal network. This trial supports further investigation focusing on executive function and incorporating connectivity-based targeting. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03243214.

Mild behavioral impairment is linked to worse cognition and brain atrophy in Parkinson disease.

OBJECTIVE: To evaluate the associations of mild behavioral impairment (MBI) with cognitive deficits and patterns of gray matter changes in Parkinson disease (PD). METHODS: Sixty patients with PD without dementia and 29 healthy controls underwent a cognitive neuropsychological evaluation and structural MRI scan. MBI was evaluated with the MBI Checklist (MBI-C), a rating scale designed to elicit emergent neuropsychiatric symptoms in accordance with MBI criteria. We divided the patients with PD into 2 groups: 1 group with high MBI-C scores (PD-MBI) and the other with low MBI-C scores (PD-noMBI). RESULTS: Among 60 patients with PD, 20 were categorized as having PD-MBI (33.33%). In healthy controls, no participants met the MBI cut-point threshold. The PD-MBI group had significantly lower Montreal Cognitive Assessment and z scores in all 5 domains and the global score compared to healthy controls and those with PD-noMBI. In addition, all cognitive domains except language and global cognition negatively correlated with the MBI-C total score in all patients with PD. For cortical structures, the PD-MBI group revealed middle temporal cortex thinning and decreased volume compared with the PD-noMBI group, and decreased volume in this area negatively correlated with the MBI-C total score. CONCLUSIONS: The impaired cognitive function over all domains and atrophy in the temporal area in the PD-MBI group are in line with posterior cortical circuit deficits in PD, which have been associated with a faster rate of progression to dementia. These initial results suggest that MBI might be an early and important marker for incident cognitive decline and dementia in patients with PD.

Transcranial magnetic stimulation improves cognition over time in Parkinson's disease.

INTRODUCTION: Cognitive impairment can occur in the early phase of Parkinson's disease and increases the risk of developing dementia. Cognitive deficits were shown to be associated with functional alterations in the dorsolateral prefrontal cortex (DLPFC) and caudate nucleus. Two previous transcranial magnetic stimulation studies over the left DLPFC showed short-term improvement in cognitive performance and focused on specific task. METHODS: 28 patients with idiopathic Parkinson's disease and mild cognitive impairment received intermittent "theta burst" stimulation (iTBS) (active, N = 14; or sham, N = 14) over the left DLPFC, twice a day for three days with 1-2 days in between. Detailed neuropsychological assessment of five cognitive domains was performed before iTBS and on days 1, 10, and 30 after the last iTBS session. Composite Z-scores were calculated for each domain and for overall cognition. RESULTS: Our results showed an increase in overall cognition up to one month in both groups but this effect was only significant in the active group. Improvements were seen in the attention domain for both groups and in the visuospatial domain in the active group only. No significant differences were found between the groups. CONCLUSION: These preliminary findings suggest that active iTBS might improve overall cognitive performance in patients with Parkinson's disease with mild cognitive impairment and that this effect can last up to one month. This cognitive improvement, is likely mediated by improvement on visuospatial abilities. Further studies are needed to explore the potential of iTBS as a therapeutical tool to slow cognitive decline in patients with Parkinson's disease.

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.

Network basis of the dysexecutive and posterior cortical cognitive profiles in Parkinson's disease.

BACKGROUND: The dual syndrome hypothesis of cognitive impairment in PD suggests that two cognitive profiles exist with distinct pathological mechanisms and a differential risk for further cognitive decline. How these profiles relate to network dysfunction has never been explicitly characterized. OBJECTIVE: First, to assess intranetwork functional connectivity while considering global connectivity, and second, to relate network connectivity with measures of the dysexecutive and posterior cortical profiles. METHODS: Eighty-two subjects with idiopathic PD and 37 age-matched controls underwent resting-state functional MRI and comprehensive neuropsychological assessment. Intranetwork and global connectivity was compared between groups. Measures of the dysexecutive and posterior cortical profiles were related to network connectivity while considering demographic and disease-related covariates. RESULTS: PD subjects show decreased connectivity within several cortical networks. However, only the sensorimotor network displayed a loss of connectivity independent of the observed decreased global connectivity. The dysexecutive factor was independently related to increased motor severity, less education, and decreased connectivity in the sensorimotor network. The posterior cortical factor was related to increased age, less education, decreased connectivity in the central executive network, as well as increased connectivity in the temporal network. CONCLUSIONS: Our results provide evidence supporting a network-specific process of degeneration in the sensorimotor network which contributes to the dysexecutive cognitive profile. In contrast, connectivity of the temporal and central executive network is related to the posterior cortical profile, representing a distinct network signature of this syndrome. © 2019 International Parkinson and Movement Disorder Society.

Interaction Between Neuropsychiatric Symptoms and Cognitive Performance in Parkinson's Disease: What Do Clinical and Neuroimaging Studies Tell Us?

PURPOSE OF REVIEW: Parkinson's disease was studied for a long time from the prism of a motor impairment. Recent advances have outlined the importance of cognitive and neuropsychiatric symptoms (NPS) in the PD equation. This review concentrates on the present possibilities of using neuroimaging techniques in order to quantify the cognitive performance and NPS in PD patients. RECENT FINDINGS: Mild cognitive impairment as well as many NPS have been acknowledged as important criteria for assessing the quality of life in patients with Parkinson's disease and have been shown as potential factors in predicting further evolution of PD from a clinical perspective. Some NPS strongly influence cognition (depression, REM sleep behavior disorder), while others are less specifically associated with it (impulse control disorders). Neuroimaging techniques reported specific structural, functional, and metabolic brain changes that might be specific for each NPS type. Recent neuroimaging advances report a strong interrelation between NPS and cognitive performance in PD. A special place for consideration is given to REM sleep behavior disorder, depression, and hallucinations. Nevertheless, some studies report distinct results, outlining that the neuroimaging acquisition and analysis techniques still have limitations and also likely represent the complexity of the manifestation of NPS in PD.

White matter degeneration profile in the cognitive cortico-subcortical tracts in Parkinson's disease.

BACKGROUND: In Parkinson's disease cognitive impairment is an early nonmotor feature, but it is still unclear why some patients are able to maintain their cognitive performance at normal levels, as quantified by neuropsychological tests, whereas others cannot. The objectives of this study were to perform a cross-sectional study and analyze the white matter changes in the cognitive and motor bundles in patients with Parkinson's disease. METHODS: Sixteen Parkinson's disease patients with normal cognitive performance, 19 with mild cognitive impairment (based on their performance of 1.5 standard deviations below the healthy population mean), and 16 healthy controls were compared with respect to their tractography patterns between the cortical cognitive / motor regions and subcortical structures, using high angular resolution diffusion imaging and constrained spherical deconvolution computation. RESULTS: Motor bundles showed decreased apparent fiber density in both PD groups, associated with a significant increase in diffusivity metrics, number of reconstructed streamlines, and track volumes, compared with healthy controls. By contrast, in the cognitive bundles, decreased fiber density in both Parkinson's groups was compounded by the absence of changes in diffusivity in patients with normal cognition, whereas patients with cognitive impairment had increased diffusivity metrics, lower numbers of reconstructed streamlines, and lower track volumes. CONCLUSIONS: Both PD groups showed similar patterns of white matter neurodegeneration in the motor bundles, whereas cognitive bundles showed a distinct pattern: Parkinson's patients with normal cognition had white matter diffusivity metrics similar to healthy controls, whereas in patients with cognitive impairment white matter showed a neurodegeneration pattern. © 2018 International Parkinson and Movement Disorder Society.

Correction: Grey Matter Microstructural Integrity Alterations in Blepharospasm Are Partially Reversed by Botulinum Neurotoxin Therapy.

[This corrects the article DOI: 10.1371/journal.pone.0168652.].

Depressive symptoms in Parkinson's disease correlate with cortical atrophy over time.

INTRODUCTION: Depressive symptoms are very common in patients with Parkinson's disease (PD) and have a significant impact on the quality of life. METHODS: The present study analyzed the correlations between over-time changes in depressive symptoms and gray matter parameters of cortical thickness and subcortical volumes in non-demented PD patients. RESULTS: A significant correlation was observed, between increased scores for depression over time and lower cortical thickness over time in the right temporo-parietal junction, right occipital medial region, right dorsolateral prefrontal cortex, right posterior cingulate region, left middle temporal as well as left supplementary motor area. Furthermore, the presence of depressive symptoms at baseline predicted increased cortical thinning over time in the left middle temporal, left anterior cingulate, right posterior cingulate and right parahippocampal cortices. Finally, a statistically significant negative correlation has been revealed between the thalamus' volume changes over time and the change in depressive symptoms scores. All other analyzed subcortical structures didn't reveal any significant correlations. CONCLUSION: These results suggest that depressive symptoms in PD patients are associated with gray matter cortical thinning and thalamus volume shrinkage over time and higher scores of depressive symptoms at baseline correlate with a higher rate of cortical thinning longitudinally. The present study highlights the importance of addressing depressive symptoms in PD patients early in the disease.

A dataset of multiresolution functional brain parcellations in an elderly population with no or mild cognitive impairment.

We present group eight resolutions of brain parcellations for clusters generated from resting-state functional magnetic resonance images for 99 cognitively normal elderly persons and 129 patients with mild cognitive impairment, pooled from four independent datasets. This dataset was generated as part of the following study: Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies (Tam et al., 2015) [1]. The brain parcellations have been registered to both symmetric and asymmetric MNI brain templates and generated using a method called bootstrap analysis of stable clusters (BASC) (Bellec et al., 2010) [2]. We present two variants of these parcellations. One variant contains bihemisphereic parcels (4, 6, 12, 22, 33, 65, 111, and 208 total parcels across eight resolutions). The second variant contains spatially connected regions of interest (ROIs) that span only one hemisphere (10, 17, 30, 51, 77, 199, and 322 total ROIs across eight resolutions). We also present maps illustrating functional connectivity differences between patients and controls for four regions of interest (striatum, dorsal prefrontal cortex, middle temporal lobe, and medial frontal cortex). The brain parcels and associated statistical maps have been publicly released as 3D volumes, available in .mnc and .nii file formats on figshare and on Neurovault. Finally, the code used to generate this dataset is available on Github.