Grey matter changes in cognitively impaired Parkinson's disease patients

Analysis of cognitive dysfunction in Parkinson's disease using voxel based morphometry and radiomics

Cognitive impairment in Parkinson's disease (PD) is associated with changes in the brain anatomical structures. The objective of this study, is to identify the atrophy patterns based on the severity of cognitive decline and evaluate the disease progression. In this study, gray matter alterations are analysed in 135 PD subjects under 3 cognitive domains (91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D)) by comparing them with 58 Healthy Control (HC) subjects. Voxel Based Morphometry (VBM) is used to segment the gray matter regions in magnetic resonance images and analyse the atrophy patterns statistically. Significant patterns of gray matter variations observed in the middle temporal and medial frontal region differentiate between HC and PD subject groups based on the severity of cognitive decline. Abnormalities in gray matter is substantiated through radiomic features extracted from the significant gray matter clusters. Significant radiomic features of the clusters are able to differentiate between the HC and PD-D subjects with an accuracy of 81.82%. Higher atrophy levels identified in PD-D subjects compared to NC-PD and PD-MCI group enables early diagnosis and treatment procedures. The combined and comprehensive analysis of gray matter alterations through VBM and radiomic features gives better assessment of cognitive impairment in PD.

Subcortical structure alteration in patients with drug-induced parkinsonism: Evidence from neuroimaging

Parkinson's Disease (PD) and Drug-induced parkinsonism (DIP) are the most common subtypes of parkinsonism, yet no studies have reported that the subcortical volume alterations in DIP patients. This study aimed to identify specific alterations of subcortical structures volume in DIP patients, and investigate association between the subcortical structure modifications and clinical symptoms. We recruited 27 PD patients, 25 DIP patients and 30 healthy controls (HCs). The clinical symptom-related parameters (Unified Parkinson's Disease Rating Scale, UPDRS) were evaluated. Structural imaging was performed on a 3.0 T scanner, and volumes of subcortical structures were obtained using FreeSurfer software. Analysis of covariance (ANCOVA) and partial correlation analysis were performed. DIP group had significantly smaller volume of the thalamus, pallidum, hippocampus and amygdala compared to HCs. ROC curve analysis demonstrated that the highest area under curve (AUC) value was in the right pallidum (AUC = 0.831) for evaluating the diagnostic efficacy in DIP from HCs. Moreover, the volumes of the putamen, hippocampus and amygdala were negatively correlated with UPDRSII in the DIP patients. The volume of the amygdala was negatively correlated with UPDRSIII. The present study provides novel information regarding neuroanatomical alteration of subcortical nuclei in DIP patients, suggesting that these methods might provide the basis for early diagnosis and differential diagnosis of DIP.

Cortical and subcortical functional connectivity and cognitive impairment in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disease with cognitive as well as motor impairments. While much is known about the brain networks leading to motor impairments in PD, less is known about the brain networks contributing to cognitive impairments. Here, we leveraged resting-state functional magnetic resonance imaging (rs-fMRI) data from the Parkinson's Progression Marker Initiative (PPMI) to examine network dysfunction in PD patients with cognitive impairment. We focus on canonical cortical networks linked to cognition, including the salience network (SAL), frontoparietal network (FPN), and default mode network (DMN), as well as a subcortical basal ganglia network (BGN). We used the Montreal Cognitive Assessment (MoCA) as a continuous index of coarse cognitive function in PD. In 82 PD patients, we found that lower MoCA scores were linked with lower intra-network connectivity of the FPN. We also found that lower MoCA scores were linked with lower inter-network connectivity between the SAL and the BGN, the SAL and the DMN, as well as the FPN and the DMN. These data elucidate the relationship of cortical and subcortical functional connectivity with cognitive impairments in PD.

Brain connectivity for subtypes of parkinson's disease using structural MRI

Objective. Delineating Parkinson's disease (PD) into distinct subtypes is a major challenge. Most studies use clinical symptoms to label PD subtypes while our work uses an imaging-based data-mining approach to subtype PD. Our study comprises two major objectives - firstly, subtyping Parkinson's patients based on grey matter information from structural magnetic resonance imaging scans of human brains; secondly, comparative structural brain connectivity analysis of PD subtypes derived from the former step.Approach. Source-based-morphometry decomposition was performed on 131 Parkinson's patients and 78 healthy controls from PPMI dataset, to derive at components (regions) with significance in disease and high effect size. The loading coefficients of significant components were thresholded for arriving at subtypes. Further, regional grey matter maps of subtype-specific subjects were separately parcellated and employed for construction of subtype-specific association matrices using Pearson correlation. These association matrices were binarized using sparsity threshold and leveraged for structural brain connectivity analysis using network metrics.Main results. Two distinct Parkinson's subtypes (namely A and B) were detected employing loadings of two components satisfying the selection criteria, and a third subtype (AB) was detected, common to these two components. Subtype A subjects were highly weighted in inferior, middle and superior frontal gyri while subtype B subjects in inferior, middle and superior temporal gyri. Network metrics analyses through permutation test revealed significant inter-subtype differences (p < 0.05) in clustering coefficient, local efficiency, participation coefficient and betweenness centrality. Moreover, hubs were obtained using betweenness centrality and mean network degree.Significance. MRI-based data-driven subtypes show frontal and temporal lobes playing a key role in PD. Graph theory-driven brain network analyses could untangle subtype-specific differences in structural brain connections showing differential network architecture. Replication of these initial results in other Parkinson's datasets may be explored in future. Clinical Relevance- Investigating structural brain connections in Parkinson's disease may provide subtype-specific treatment.

Functional neural networks stratify Parkinson's disease patients across the spectrum of cognitive impairment

INTRODUCTION

Cognitive impairment (CI) is a significant non-motor symptoms in Parkinson's disease (PD) that often precedes the emergence of motor symptoms by several years. Patients with PD hypothetically progress from stages without CI (PD-normal cognition [NC]) to stages with Mild CI (PD-MCI) and PD dementia (PDD). CI symptoms in PD are linked to different brain regions and neural pathways, in addition to being the result of dysfunctional subcortical regions. However, it is still unknown how functional dysregulation correlates to progression during the CI. Neuroimaging techniques hold promise in discriminating CI stages of PD and further contribute to the biomarker formation of CI in PD. In this study, we explore disparities in the clinical assessments and resting-state functional connectivity (FC) among three CI stages of PD.

METHODS

We enrolled 88 patients with PD and 26 healthy controls (HC) for a cross sectional clinical study and performed intra- and inter-network FC analysis in conjunction with comprehensive clinical cognitive assessment.

RESULTS

Our findings underscore the significance of several neural networks, namely, the default mode network (DMN), frontoparietal network (FPN), dorsal attention network, and visual network (VN) and their inter-intra-network FC in differentiating between PD-MCI and PDD. Additionally, our results showed the importance of sensory motor network, VN, DMN, and salience network (SN) in the discriminating PD-NC from PDD. Finally, in comparison to HC, we found DMN, FPN, VN, and SN as pivotal networks for further differential diagnosis of CI stages of PD.

CONCLUSION

We propose that resting-state networks (RSN) can be a discriminating factor in distinguishing the CI stages of PD and progressing from PD-NC to MCI or PDD. The integration of clinical and neuroimaging data may enhance the early detection of PD in clinical settings and potentially prevent the disease from advancing to more severe stages.

Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson's Disease

Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.

Structural connectivity from DTI to predict mild cognitive impairment in de novo Parkinson's disease

BACKGROUND

Early detection of Parkinson's disease (PD) patients at high risk for mild cognitive impairment (MCI) can help with timely intervention. White matter structural connectivity is considered an early and sensitive indicator of neurodegenerative disease.

OBJECTIVES

To investigate whether baseline white matter structural connectivity features from diffusion tensor imaging (DTI) of de novo PD patients can help predict PD-MCI conversion at an individual level using machine learning methods.

METHODS

We included 90 de novo PD patients who underwent DTI and 3D T1-weighted imaging. Elastic net-based feature consensus ranking (ENFCR) was used with 1000 random training sets to select clinical and structural connectivity features. Linear discrimination analysis (LDA), support vector machine (SVM), K-nearest neighbor (KNN) and naïve Bayes (NB) classifiers were trained based on features selected more than 500 times. The area under the ROC curve (AUC), accuracy (ACC), sensitivity (SEN) and specificity (SPE) were used to evaluate model performance.

RESULTS

A total of 57 PD patients were classified as PD-MCI nonconverters, and 33 PD patients were classified as PD-MCI converters. The models trained with clinical data showed moderate performance (AUC range: 0.62-0.68; ACC range: 0.63-0.77; SEN range: 0.45-0.66; SPE range: 0.64-0.84). Models trained with structural connectivity (AUC range, 0.81-0.84; ACC range, 0.75-0.86; SEN range, 0.77-0.91; SPE range, 0.71-0.88) performed similar to models that were trained with both clinical and structural connectivity data (AUC range, 0.81-0.85; ACC range, 0.74-0.85; SEN range, 0.79-0.91; SPE range, 0.70-0.89).

CONCLUSIONS

Baseline white matter structural connectivity from DTI is helpful in predicting future MCI conversion in de novo PD patients.

Voxel-based morphometry of grey matter structures in Parkinson's Disease with wearing-off

Our study aimed to investigate the grey matter (GM) changes using voxel-based morphometry (VBM) in Parkinson's disease (PD) patients with wearing-off (WO). 3D-T1-weighted imaging was performed on 48 PD patients without wearing-off (PD-nWO), 39 PD patients with wearing-off (PD-WO) and 47 age and sex-matched healthy controls (HCs). 3D structural images were analyzed by VBM procedure with Statistical Parametric Mapping (SPM12) to detect grey matter volume. Widespread areas of grey matter changes were found in patients among three groups (in bilateral frontal, temporal lobes, lingual gyrus, inferior occipital gyrus, right precuneus, right superior parietal gyrus and right cerebellum). Grey matter reductions were found in frontal lobe (right middle frontal gyrus, superior frontal gyrus and precentral gyrus), right parietal lobe (precuneus, superior parietal gyrus, postcentral gyrus), right temporal lobe (superior temporal gyrus, middle temporal gyrus), bilateral lingual gyrus and inferior occipital gyrus in PD-WO group compared with the PD-nWO group. Our results suggesting that wearing-off may be associated with grey matter atrophy in the cortical areas. These findings may aid in a better understanding of the brain degeneration process in PD with wearing-off.

Visual Dysfunction in Parkinson's Disease

Non-motor symptoms in Parkinson's disease (PD) include ocular, visuoperceptive, and visuospatial impairments, which can occur as a result of the underlying neurodegenerative process. Ocular impairments can affect various aspects of vision and eye movement. Thus, patients can show dry eyes, blepharospasm, reduced blink rate, saccadic eye movement abnormalities, smooth pursuit deficits, and impaired voluntary and reflexive eye movements. Furthermore, visuoperceptive impairments affect the ability to perceive and recognize visual stimuli accurately, including impaired contrast sensitivity and reduced visual acuity, color discrimination, and object recognition. Visuospatial impairments are also remarkable, including difficulties perceiving and interpreting spatial relationships between objects and difficulties judging distances or navigating through the environment. Moreover, PD patients can present visuospatial attention problems, with difficulties attending to visual stimuli in a spatially organized manner. Moreover, PD patients also show perceptual disturbances affecting their ability to interpret and determine meaning from visual stimuli. And, for instance, visual hallucinations are common in PD patients. Nevertheless, the neurobiological bases of visual-related disorders in PD are complex and not fully understood. This review intends to provide a comprehensive description of visual disturbances in PD, from sensory to perceptual alterations, addressing their neuroanatomical, functional, and neurochemical correlates. Structural changes, particularly in posterior cortical regions, are described, as well as functional alterations, both in cortical and subcortical regions, which are shown in relation to specific neuropsychological results. Similarly, although the involvement of different neurotransmitter systems is controversial, data about neurochemical alterations related to visual impairments are presented, especially dopaminergic, cholinergic, and serotoninergic systems.

Regional homogeneity and functional connectivity of freezing of gait conversion in Parkinson's disease

Background

Freezing of gait (FOG) is common in the late stage of Parkinson's disease (PD), which can lead to disability and impacts the quality of life. Therefore, early recognition is crucial for therapeutic intervention. We aimed to explore the abnormal regional homogeneity (ReHo) and functional connectivity (FC) in FOG converters and evaluate their diagnostic values.

Methods

The data downloaded from the Parkinson's Disease Progression Markers Project (PPMI) cohort was subdivided into PD-FOG converters (n = 16) and non-converters (n = 17) based on whether FOG appeared during the 3-year follow-up; 16 healthy controls were well-matched. ReHo and FC analyses were used to explore the variations in spontaneous activity and interactions between significant regions among three groups of baseline data. Correlations between clinical variables and the altered ReHo values were assessed in FOG converter group. Last, logistic regression and receiver operating characteristic curve (ROC) were used to predict diagnostic value.

Results

Compared with the non-converters, FOG converters had reduced ReHo in the bilateral medial superior frontal gyrus (SFGmed), which was negatively correlated with the postural instability and gait difficulty (PIGD) score. ReHo within left amygdala/olfactory cortex/putamen (AMYG/OLF/PUT) was decreased, which was correlated with anxiety and autonomic dysfunction. Also, increased ReHo in the left supplementary motor area/paracentral lobule was positively correlated with the rapid eye movement sleep behavior disorder screening questionnaire. FOG converters exhibited diminished FC in the basal ganglia, limbic area, and cognitive control cortex, as compared with non-converters. The prediction model combined ReHo of basal ganglia and limbic area, with PIGD score was the best predictor of FOG conversion.

Conclusion

The current results suggested that abnormal ReHo and FC in the basal ganglia, limbic area, and cognitive control cortex may occur in the early stage of FOG. Basal ganglia and limbic area dysfunction combined with higher PIGD score are useful for the early recognition of FOG conversion.

Unleashing the potential of dance: a neuroplasticity-based approach bridging from older adults to Parkinson's disease patients

Parkinson's disease (PD) is a neurodegenerative disorder that affects >1% of individuals worldwide and is manifested by motor symptoms such as tremor, rigidity, and bradykinesia, as well as non-motor symptoms such as cognitive impairment and depression. Non-pharmacological interventions such as dance therapy are becoming increasingly popular as complementary therapies for PD, in addition to pharmacological treatments that are currently widely available. Dance as a sensorimotor activity stimulates multiple layers of the neural system, including those involved in motor planning and execution, sensory integration, and cognitive processing. Dance interventions in healthy older people have been associated with increased activation of the prefrontal cortex, as well as enhanced functional connectivity between the basal ganglia, cerebellum, and prefrontal cortex. Overall, the evidence suggests that dance interventions can induce neuroplastic changes in healthy older participants, leading to improvements in both motor and cognitive functions. Dance interventions involving patients with PD show better quality of life and improved mobility, whereas the literature on dance-induced neuroplasticity in PD is sparse. Nevertheless, this review argues that similar neuroplastic mechanisms may be at work in patients with PD, provides insight into the potential mechanisms underlying dance efficacy, and highlights the potential of dance therapy as a non-pharmacological intervention in PD. Further research is warranted to determine the optimal dance style, intensity, and duration for maximum therapeutic benefit and to determine the long-term effects of dance intervention on PD progression.

Large-scale activation likelihood estimation meta-analysis of parkinsonian disorders

Parkinsonism is a feature of several neurodegenerative disorders, including Parkinson's disease, progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy. Neuroimaging studies have yielded insights into parkinsonian disorders; however, due to variability in results, the brain regions consistently implicated in these disorders remain to be characterized. The aim of this meta-analysis was to identify consistent brain abnormalities in individual parkinsonian disorders (Parkinson's disease, progressive supranuclear palsy, corticobasal syndrome and multiple system atrophy) and to investigate any shared abnormalities across disorders. A total of 44 591 studies were systematically screened following searches of two databases. A series of whole-brain activation likelihood estimation meta-analyses were performed on 132 neuroimaging studies (69 Parkinson's disease; 23 progressive supranuclear palsy; 17 corticobasal syndrome; and 23 multiple system atrophy) utilizing anatomical MRI, perfusion or metabolism PET and single-photon emission computed tomography. Meta-analyses were performed in each parkinsonian disorder within each imaging modality, as well as across all included disorders. Results in progressive supranuclear palsy and multiple system atrophy aligned with current imaging markers for diagnosis, encompassing the midbrain, and brainstem and putamen, respectively. PET imaging studies of patients with Parkinson's disease most consistently reported abnormality of the middle temporal gyrus. No significant clusters were identified in corticobasal syndrome. When examining abnormalities shared across all four disorders, the caudate was consistently reported in MRI studies, whilst the thalamus, inferior frontal gyrus and middle temporal gyri were commonly implicated by PET. To our knowledge, this is the largest meta-analysis of neuroimaging studies in parkinsonian disorders and the first to characterize brain regions implicated across parkinsonian disorders.

Neuroanatomical correlates of individual differences in the object choice task in chimpanzees (Pan troglodytes)

Declarative and imperative joint attention or joint engagement are important milestones in human infant development. These have been shown to be a significant predictor of later language development and are impaired in some individuals with, or at risk for, a diagnosis of autism spectrum disorder. Comparatively, while chimpanzees and other great apes have been reported to engage in imperative joint attention, evidence of declarative joint attention remains unclear based on existing studies. Some have suggested that differences in methods of assessing joint attention may have an influence on performance in nonhuman primates. Here, we report data on a measure of receptive joint attention (object choice task) in a sample of captive chimpanzees. Chimpanzees, as a group, performed significantly better than chance. By contrast, when considering individual performance, there was no significant difference in the number of those who passed and those who failed. Using quantitative genetic analyses, we found that performance on the object choice task was not significantly heritable nor were there any significant effects of sex, rearing history, or colony. Lastly, we found significant differences in gray matter covariation, between those who passed or failed the task. Those who passed contributed more to gray matter covariation in several brain regions within the social brain network, consistent with hypotheses regarding the importance of these regions in human and nonhuman primate social cognition.

Neuroanatomical correlates of screening for aphasia in NeuroDegeneration (SAND) battery in non-fluent/agrammatic variant of primary progressive aphasia

Background

Non-fluent/agrammatic variant of Primary Progressive Aphasia (avPPA) is primarily characterized by language impairment due to atrophy of the inferior frontal gyrus and the insula cortex in the dominant hemisphere. The Screening for Aphasia in NeuroDegeneration (SAND) battery has been recently proposed as a screening tool for PPA, with several tasks designed to be specific for different language features. Applying multivariate approaches to neuroimaging data and verbal fluency tasks, Aachener Aphasie Test (AAT) naming subtest and SAND data may help in elucidating the neuroanatomical correlates of language deficits in avPPA.

Objective

To investigate the neuroanatomical correlates of language deficits in avPPA using verbal fluency tasks, AAT naming subtest and SAND scores as proxies of brain structural imaging abnormalities.

Methods

Thirty-one avPPA patients were consecutively enrolled and underwent extensive neuropsychological assessment and MRI scan. Raw scores of verbal fluency tasks, AAT naming subtest, and SAND subtests, namely living and non-living picture naming, auditory sentence comprehension, single-word comprehension, words and non-words repetition and sentence repetition, were used as proxies to explore structural (gray matter volume) neuroanatomical correlates. We assessed univariate (voxel-based morphometry, VBM) as well as multivariate (source-based morphometry, SBM) approaches. Age, gender, educational level, and disease severity were considered nuisance variables.

Results

SAND picture naming (total, living and non-living scores) and AAT naming scores showed a direct correlation with the left temporal network derived from SBM. At univariate analysis, the left middle temporal gyrus was directly correlated with SAND picture naming (total and non-living scores) and AAT naming score. When words and non-words repetition (total score) was considered, a direct correlation with the left temporal network (SBM) and with the left fusiform gyrus (VBM) was also evident.

Conclusion

Naming impairments that characterize avPPA are related to specific network-based involvement of the left temporal network, potentially expanding our knowledge on the neuroanatomical basis of this neurodegenerative condition.

The reduction of hippocampal volume in Parkinson's disease

The volume of the hippocampus decreases more slowly than the volume of the cortex during normal aging. We explored changes in the hippocampus-to-cortex volume (HV:CTV) ratio with increasing age in non-demented Parkinson's disease (PD) patients as compared to healthy controls (HC). We also evaluated the association between the HV:CTV ratio and cognitive outcomes. Altogether 130 participants without dementia aged 51-88 years were consecutively enrolled, including 54 PD patients (mean age 67, standard deviation (SD) 8 years) and 76 HC (mean age 69, SD 7 years). All participants underwent structural magnetic resonance examination and psychological evaluation. Hippocampal and cortex volumes were determined from T1 and FLAIR scans using FreeSurfer software, and the HV:CTV ratio was calculated. Regression lines for age-dependence of the HV:CTV ratio for PD and HC groups were calculated. We further assessed the association between the HV:CTV ratio and cognitive tests examining hippocampus-related cognitive functions. PD patients and age-matched HC showed a significant difference in age-dependence of HV:CTV ratio (p value = 0.012), with a decreasing slope in PD and increasing slope in HC. In the PD group, a significant correlation (R = 0.561, p = 0.024) was observed between the HV:CTV ratio and the Digit Symbol-Coding test. The reduction of HV:CTV ratio is accelerated in pathological aging due to PD pathology. The HV:CTV ratio was associated with impaired processing speed, i.e., the cognitive function that is linked to subcortical alterations of both associated basal ganglia circuitry and the hippocampus.

Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson's disease using multi-atlas based segmentation

Cognitive impairment in Parkinson's Disease (PD) is the most prevalent non-motor symptom that requires analysis of anatomical associations to cognitive decline in PD. The objective of this study is to analyse the morphological variations of the subcortical structures to assess cognitive dysfunction in PD. In this study, T1 MR images of 58 Healthy Control (HC) and 135 PD subjects categorised as 91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D) subjects, based on cognitive scores are utilised. The 132 anatomical regions are segmented using spatially localized multi-atlas model and volumetric analysis is carried out. The morphological alterations through textural features are captured to differentiate among the HC and PD subjects under different cognitive domains. The volumetric differences in the segmented subcortical structures of accumbens, amygdala, caudate, putamen and thalamus are able to predict cognitive impairment in PD. The volumetric distribution of the subcortical structures in PD-MCI subjects exhibit an overlap with the HC group due to lack of spatial specificity in their atrophy levels. The 3D GLCM features extracted from the significant subcortical structures could discriminate HC, NC-PD, PD-MCI and PD-D subjects with better classification accuracies. The disease related atrophy levels of the subcortical structures captured through morphological analysis provide sensitive evaluation of cognitive impairment in PD.

Structural Covariance of Depth-Dependent Intracortical Myelination in the Human Brain and Its Application to Drug-Naïve Schizophrenia: A T1w/T2w MRI Study

Aberrations in intracortical myelination are increasingly being considered as a cardinal feature in the pathophysiology of schizophrenia. We investigated the network-level distribution of intracortical myelination across various cortex depths. We enrolled 126 healthy subjects and 106 first-episode drug-naïve schizophrenia patients. We used T1w/T2w ratio as a proxy of intracortical myelination, parcellated cortex into several equivolumetric surfaces based on cortical depths and mapped T1w/T2w ratios to each surface. Non-negative matrix factorization was used to generate depth-dependent structural covariance networks (dSCNs) of intracortical myelination from 2 healthy controls datasets-one from our study and another from 100-unrelated dataset of the Human Connectome Project. For patient versus control comparisons, partial least squares approach was used; we also related myelination to clinical features of schizophrenia. We found that dSCNs were highly reproducible in 2 independent samples. Network-level myelination was reduced in prefrontal and cingulate cortex and increased in perisylvian cortex in schizophrenia. The abnormal network-level myelination had a canonical correlation with symptom burden in schizophrenia. Moreover, myelination of prefrontal cortex correlated with duration of untreated psychosis. In conclusion, we offer a feasible and sensitive framework to study depth-dependent myelination and its relationship with clinical features.

Neuroplasticity mediated by motor rehabilitation in Parkinson's disease: a systematic review on structural and functional MRI markers

Parkinson's disease (PD) is the second most common neurological disease affecting the elderly population. Pharmacological and surgical interventions usually employed for PD treatment show transient effectiveness and are associated with the insurgence of side effects. Therefore, motor rehabilitation has been proposed as a promising supplement in the treatment of PD, reducing the global burden of the disease and improving patients quality of life. The present systematic review aimed to critically analyse the literature concerning MRI markers of brain functional and structural response to motor rehabilitation in PD. Fourteen out of 1313 studies were selected according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. Despite the limited number of retrieved studies coupled with their heterogeneity prevent ultimate conclusions from being drawn, motor rehabilitation seems to have beneficial effects on PD as measured both with clinical outcomes and MRI derived indices. Interestingly, consistent results seem to indicate that motor rehabilitation acts via a dual mechanism of strengthening cortico-subcortical pathways, restoring movements automaticity, or activating compensatory networks such as the fronto-parietal one. The employment of more advanced and quantitative MRI methods is warranted to establish and validate standardized metrics capable of reliably determining the changes induced by rehabilitative intervention.

Aberrant cerebral perfusion pattern in amnestic mild cognitive impairment and Parkinson's disease with mild cognitive impairment: a comparative arterial spin labeling study

Background

Mild cognitive impairment (MCI) has been defined as the prodromal stage of Alzheimer's disease and Parkinson's disease (PD) with dementia. We investigated the differences in regional perfusion properties among MCI subtypes and healthy control (HC) subjects by using arterial spin labeling (ASL).

Methods

Regional normalized CBF (z-CBF) and CBF-connectivity were analyzed from ASL data in 44 amnestic MCI (aMCI) patients, 42 PD-MCI patients, and 50 matched HC participants. The correlations between these significant regions and clinical performance were investigated separately using Spearman correlation analysis. Receiver operating characteristic analysis was generated to determine the differentiating ability of z-CBF values. z-CBF values in disease-related specific regions were extracted for group comparison.

Results

MCI subgroups showed overlapped impaired regions, aMCI group seemed more extensive than the PD-MCI group. PD-MCI patients had reduced z-CBF in the bilateral putamen, left precentral gyrus, left middle cingulate gyrus, and right middle frontal gyrus compared to aMCI group. Correlations to executive performance and motor severity were found in PD-MCI group, and correlations were to memory performance found in aMCI group. CBF-connectivity in left precentral gyrus, left middle cingulate gyrus, and right middle frontal gyrus were significantly altered. All of the significant clusters had good discriminatory ability.

Conclusions

Normalized CBF as measured by ASL revealed different patterns of perfusion between aMCI and PD-MCI, which were probably linked to distinct neural mechanisms. The present study indicates that z-CBF can provide specific perfusion information for further pathological and neuropsychological studies.

Subcortical grey matter changes associated with motor symptoms evaluated by the Unified Parkinson's disease Rating Scale (part III): A longitudinal study in Parkinson's disease

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Decreased grey matter volume over time suggests a subcortical alteration in PD.

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Decreased volume in the thalamus may be related to the decline in motor skills.

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Increased volume in the pallidum may contribute to motor impairment.

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Structural changes in line with the model of basal ganglia-thalamocortical circuits.

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VBM and volumetry might capture complementary aspects of structural changes in PD.

Parkinson disease (PD) is characterized by motor deficits related to structural changes in the basal ganglia-thalamocortical circuits. However, it is still unclear the exact nature of the association between grey matter alterations and motor symptoms.

Therefore, the aim of our investigation was to identify the subcortical modifications associated with motor symptoms of PD over time - adopting voxel-based morphometry (VBM) and automated volumetry methods.

We selected fifty subjects with PD from the Parkinson’s Progression Markers Initiative (PPMI) database, who performed an MRI session at two time points: at baseline (i.e. at maximum 2 years after clinical diagnosis of PD) and after 48 months. Motor symptoms were assessed using the part III of the Unified Parkinson’s Disease Rating Scale at the two time points.

Our VBM and volumetric analyses showed a general atrophy in all subcortical regions when comparing baseline with 48 months. These findings confirmed previous observations indicating a subcortical alteration over time in PD. Furthermore, our findings supported the idea that a reduced volume in the thalamus and an increased volume in pallidum may be related to the decline in motor skills. These structural modifications are in accordance with the functional model of the basal ganglia-thalamocortical circuits controlling movements. Moreover, VBM and volumetry provided partially overlapping results, suggesting that these methods might capture complementary aspects of brain degeneration in PD.

Meta-Analysis of Cognition in Parkinson's Disease Mild Cognitive Impairment and Dementia Progression

Mild cognitive changes, including executive dysfunction, are seen in Parkinson's Disease (PD). Approximately 30% of individuals with PD develop Parkinson's disease dementia (PDD). Mild cognitive impairment (MCI) has been identified as a transitional state between normal cognition and dementia. Although PD-MCI and its cognitive correlates have been increasingly studied as a risk indicator for development of PDD, investigations into the PD-MCI construct have yielded heterogeneous findings. Thus, a typical PD-MCI cognitive profile remains undefined. The present meta-analysis examined published cross-sectional studies of PD-MCI and cognitively normal PD (PD-CN) groups to provide aggregated effect sizes of group test performance by cognitive domain. Subsequently, longitudinal studies examining PD-MCI to PDD progression were meta-analyzed. Ninety-two cross-sectional articles of PD-MCI vs. PD-CN were included; 5 longitudinal studies of PD-MCI conversion to PDD were included. Random effects meta-analytic models were constructed resulting in effect sizes (Hedges' g) for cognitive domains. Overall performance across all measures produced a large effect size (g = 0.83, 95% CI [0.79, 0.86], t² = 0.18) in cross-sectional analyses, with cognitive screeners producing the largest effect (g = 1.09, 95% CI [1.00, 1.17], t² = 0.19). Longitudinally, overall measures produced a moderate effect (g = 0.47, 95% CI [0.40, 0.53], t² = 0.01), with measures of executive functioning exhibiting the largest effect (g = 0.70, 95% CI [0.51, 0.89], t² = 0.01). Longitudinal effects were made more robust by low heterogeneity. This report provides the first comprehensive meta-analysis of PD-MCI cognitive outcomes and predictors in PD-MCI conversion to PDD. Limitations include heterogeneity of cross-sectional effect sizes and the potential impact of small-study effects. Areas for continued research include visuospatial skills and visual memory in PD-MCI and longitudinal examination of executive dysfunction in PD-MCI.

The Human Hippocampus in Parkinson's Disease: An Integrative Stereological and Proteomic Study

BACKGROUND

Parkinson's disease (PD) is a prevalent neurodegenerative disease that is pathologically described as a six-stage α-synucleinopathy. In stage 4, α-synuclein reaches the hippocampus, inducing cognitive deficits, from which it progresses to the isocortex, leading to dementia. Among hippocampal fields, cornu ammonis 2 is particularly affected by this α-synucleinopathy and critical for cognitive decline. Volumetric studies using magnetic resonance imaging have produced controversial results, with only some reporting volume loss, whereas stereological data obtained using nonspecific markers do not reveal volume changes, neural or glial loss. Proteomic analysis has not been carried out in the hippocampus of patients with PD.

OBJECTIVE

This study aims to explain hippocampal changes in patients with PD at the cellular and proteomic levels.

METHODS

α-Synuclein inclusions, volume and neural (NeuN), microglial (Iba-1) and astroglial (GFAP) populations were stereologically analyzed. SWATH-MS quantitative proteomic analysis was also conducted.

RESULTS

Area fraction fractionator probe revealed a higher area fraction α-synucleinopathy in cornu ammonis 2. No volume change, neurodegeneration, microgliosis or astrogliosis was detected. Proteomic analysis identified 1,634 proteins, of which 83 were particularly useful for defining differences among PD and non-PD groups. Among them, upregulated (PHYIP, CTND2, AHSA1 and SNTA1) and downregulated (TM163, REEP2 and CSKI1) proteins were related to synaptic structures in the diseased hippocampus.

CONCLUSION

The distribution of α-synuclein in the hippocampus is not associated with volumetric, neural or glial changes. Proteomic analysis, however, reveals a series of changes in proteins associated with synaptic structures, suggesting that hippocampal changes occur at the synapse level during PD.

The genetic architecture of human brainstem structures and their involvement in common brain disorders

Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders.

The genetic architecture underlying brainstem regions and how this links to common brain disorders is not well understood. Here, the authors use MRI and GWAS data from 27,034 individuals to identify genetic and morphological brainstem features that influence common brain disorders.

Cortical thinning in dementia with Lewy bodies and Parkinson disease dementia

BACKGROUND

We investigated the structural changes associated with Alzheimer's disease, dementia with Lewy bodies and Parkinson disease dementia by means of cortical thickness analysis.

METHODS

Two hundred and forty-five participants: 76 Alzheimer's disease, 65 dementia with Lewy bodies, 29 Parkinson disease dementia and 76 cognitively normal controls underwent 3-T T1-weighted magnetic resonance imaging and clinical and cognitive assessments. We implemented FreeSurfer to obtain cortical thickness estimates to contrast patterns of cortical thinning across groups and their clinical correlates.

RESULTS

In Alzheimer's disease and dementia with Lewy bodies, a largely similar pattern of regional cortical thinning was observed relative to controls apart from a more severe loss within the entorhinal and parahippocampal structures in Alzheimer's disease. In Parkinson disease dementia, regional cortical thickness was indistinguishable from controls and dementia with Lewy bodies, suggesting an 'intermediate' pattern of regional cortical change. In terms of global cortical thickness, group profiles were controls > Parkinson disease dementia > dementia with Lewy bodies > Alzheimer's disease (F_{3, 241} ⩽ 123.2, p < 0.001), where percentage wise, the average difference compared to controls were -1.8%, -5.5% and -6.4%, respectively. In these samples, cortical thinning was also associated with cognitive decline in dementia with Lewy bodies but not in Parkinson disease dementia and Alzheimer's disease.

CONCLUSION

In a large and well-characterised cohort of people with dementia, regional cortical thinning in dementia with Lewy bodies was broadly similar to Alzheimer's disease. There was preservation of the medial temporal lobe structures in dementia with Lewy bodies compared with Alzheimer's disease, supporting its inclusion as a supportive biomarker in the revised clinical criteria for dementia with Lewy bodies. However, there was less global cortical thinning in Parkinson disease dementia, with no significant regional difference between Parkinson disease dementia and controls. These findings highlight the overlap across the Alzheimer's disease/Parkinson disease dementia spectrum and the potential for differing mechanisms underlying neurodegeneration and cognition in dementia with Lewy bodies and Parkinson disease dementia.

Exercise and Parkinson's Disease

Parkinson's disease (PD) is an aging-related neurodegenerative disorder characterized by progressive motor impairment.The etiology of PD is poorly understood but likely involves both genetic and environmental factors; the management of the disease is still with symptomatic therapy without any interference on the progression of neurodegeneration. In the past two decades, the results of a series of prospective cohort studies suggested that lifestyle factors likely modify the risk of developing PD. Among these, physical activity is known to reduce the risk of a wide range of diseases and conditions, including cardiovascular disease, stroke, and diabetes.Recently, a growing body of evidence has suggested that increased physical activity may also reduce the risk of PD and partly improve motor and non-motor symptoms during the disease course.Here we report the main findings on the effect of physical activity on both mobility and cognition either in animal models of PD or in people with PD. We also highlighted the structural and functional links between gait and cognition by reporting evidence from neuroimaging studies.

Entorhinal Cortex Atrophy in Early, Drug-naive Parkinson's Disease with Mild Cognitive Impairment

Patients with Parkinson's disease (PD) generally have a higher proportion of suffering from mild cognitive impairment (MCI) than normal aged adults. This study aimed to identify the specific neuroanatomical alterations in early, drug-naive PD with MCI (PD-MCI) by comparing to those PD with normal cognition (PD-NC) and healthy controls (HCs), which could help to elucidate the underlying neuropathology and facilitate the development of early therapeutic strategies for treating this disease. Structural MRI data of 237 early, drug-naive non-demented PD patients (classified as 61 PD-MCI and 176 PD-NC) and 69 HCs were included from Parkinson's Progression Markers Initiative (PPMI) database after data quality control. Within these data, a subset of 61 HCs and a subset of 61 PD-NC who were matched to the 61 PD-MCI group for age, gender, and education-level were selected to further eliminate the sample size effect. The gray matter (GM) volume changes between groups were analyzed using voxel-based morphometry (VBM). Furthermore, correlations between GM volume alterations and neuropsychological performances and non-cognitive assessments (including olfactory performance) were further examined. Compared to HC, patients with PD-NC and PD-MCI commonly exhibited atrophies in the bilateral amygdala (AM) and the left primary motor cortex (M1). Patients with PD-MCI exclusively exhibited atrophy in the right entorhinal cortex (ENT) compared to PD-NC. Significantly negative correlations were found between GM loss in the bilateral AM and olfactory performance in all PD patients, and between ENT loss and memory performance in PD-MCI. The findings suggest that the right ENT atrophy may subserve as a biomarker in early, drug-naive PD-MCI, which shed light on the neural underpinnings of the disease and provide new evidence on differentiating the neuroanatomical states between PD-MCI and PD-NC.

Associations between brain structural networks and neurological soft signs in healthy adults

Neurological soft signs (NSS), as minor neurological deficits, have been identified in several psychiatric disorders, especially in schizophrenia. However, it's unclear how the neuropathological processes of the disease affect NSS related brain morphological changes and whether it is confounded by the use of medication. As NSS also exist in healthy people, the potential confounding effects of psychopathology or medication will be excluded if NSS are investigated in healthy people. Therefore, we applied a novel multivariate approach, source-based morphometry (SBM), to study structural networks in relation to NSS in healthy adults based on structural magnetic resonance imaging (MRI) data. The Heidelberg Scale was applied to evaluate NSS. Using SBM, we constructed structural networks and investigated their associations with NSS in healthy adults. Six grey matter (GM) structural networks were identified. Sensory integration subscores were associated with the cerebellar component and the cortico-basal ganglia-thalamic component. Motor coordination subscores and total NSS scores were associated with the sensorimotor component. The present findings indicated that structural network abnormalities in cerebellar, subcortical and cortical sensorimotor areas contribute to NSS performance in healthy adults.

Gray Matter Changes in Parkinson's and Alzheimer's Disease and Relation to Cognition

PURPOSE OF REVIEW

We summarize structural (s)MRI findings of gray matter (GM) atrophy related to cognitive impairment in Alzheimer's disease (AD) and Parkinson's disease (PD) in light of new analytical approaches and recent longitudinal studies results.

RECENT FINDINGS

The hippocampus-to-cortex ratio seems to be the best sMRI biomarker to discriminate between various AD subtypes, following the spatial distribution of tau pathology, and predict rate of cognitive decline. PD is clinically far more variable than AD, with heterogeneous underlying brain pathology. Novel multivariate approaches have been used to describe patterns of early subcortical and cortical changes that relate to more malignant courses of PD. New emerging analytical approaches that combine structural MRI data with clinical and other biomarker outcomes hold promise for detecting specific GM changes in the early stages of PD and preclinical AD that may predict mild cognitive impairment and dementia conversion.

Heritability of Gray Matter Structural Covariation and Tool Use Skills in Chimpanzees (Pan troglodytes): A Source-Based Morphometry and Quantitative Genetic Analysis

Nonhuman primates, and great apes in particular, possess a variety of cognitive abilities thought to underlie human brain and cognitive evolution, most notably, the manufacture and use of tools. In a relatively large sample (N = 226) of captive chimpanzees (Pan troglodytes) for whom pedigrees are well known, the overarching aim of the current study was to investigate the source of heritable variation in brain structure underlying tool use skills. Specifically, using source-based morphometry (SBM), a multivariate analysis of naturally occurring patterns of covariation in gray matter across the brain, we investigated (1) the genetic contributions to variation in SBM components, (2) sex and age effects for each component, and (3) phenotypic and genetic associations between SBM components and tool use skill. Results revealed important sex- and age-related differences across largely heritable SBM components and associations between structural covariation and tool use skill. Further, shared genetic mechanisms appear to account for a heritable link between variation in both the capacity to use tools and variation in morphology of the superior limb of the superior temporal sulcus and adjacent parietal cortex. Findings represent the first evidence of heritability of structural covariation in gray matter among nonhuman primates.

Alterations in White Matter Network and Microstructural Integrity Differentiate Parkinson's Disease Patients and Healthy Subjects

Parkinson’s disease (PD) is a neurodegenerative disease, neuropathologically characterized by progressive loss of neurons in distinct brain areas. We hypothesize that quantifiable network alterations are caused by neurodegeneration. The primary motivation of this study was to assess the specific network alterations in PD patients that are distinct but appear in conjunction with physiological aging. 178 subjects (130 females) stratified into PD patients, young, middle-aged and elderly healthy controls (age- and sex-matched with PD patients), were analyzed using 3D-T1 magnetization-prepared rapid gradient-echo (MPRAGE) and diffusion weighted images acquired in 3T MRI scanner. Diffusion modeling and probabilistic tractography analysis were applied for generating voxel-based connectivity index maps from each seed voxel. The obtained connectivity matrices were analyzed using graph theoretical tools for characterization of involved network. By network-based statistic (NBS) the interregional connectivity differences between the groups were assessed. Measures evaluating local diffusion properties for anisotropy and diffusivity were computed for characterization of white matter microstructural integrity. The graph theoretical analysis showed a significant decrease in distance measures – eccentricity and characteristic path length – in PD patients in comparison to healthy subjects. Both measures as well were lower in PD patients when compared to young and middle-aged healthy controls. NBS analysis demonstrated lowered structural connectivity in PD patients in comparison to young and middle-aged healthy subject groups, mainly in frontal, cingulate, olfactory, insula, thalamus, and parietal regions. These specific network differences were distinct for PD and were not observed between the healthy subject groups. Microstructural analysis revealed diffusivity alterations within the white matter tracts in PD patients, predominantly in the body, splenium and tapetum of corpus callosum, corticospinal tract, and corona radiata, which were absent in normal aging. The identified alterations of network connectivity presumably caused by neurodegeneration indicate the disruption in global network integration in PD patients. The microstructural changes identified within the white matter could endorse network reconfiguration. This study provides a clear distinction between the network changes occurring during aging and PD. This will facilitate a better understanding of PD pathophysiology and the direct link between white matter changes and their role in the restructured network topology.

Neuroimaging in Parkinson's disease dementia: connecting the dots

Dementia is a common and devastating symptom of Parkinson's disease but the anatomical substrate remains unclear. Some evidence points towards hippocampal involvement but neuroimaging abnormalities have been reported throughout the brain and are largely inconsistent across studies. Here, we test whether these disparate neuroimaging findings for Parkinson's disease dementia localize to a common brain network. We used a literature search to identify studies reporting neuroimaging correlates of Parkinson's dementia (11 studies, 385 patients). We restricted our search to studies of brain atrophy and hypometabolism that compared Parkinson's patients with dementia to those without cognitive involvement. We used a standard coordinate-based activation likelihood estimation meta-analysis to assess for consistency in the neuroimaging findings. We then used a new approach, coordinate-based network mapping, to test whether neuroimaging findings localized to a common brain network. This approach uses resting-state functional connectivity from a large cohort of normative subjects (n = 1000) to identify the network of regions connected to a reported neuroimaging coordinate. Activation likelihood estimation meta-analysis failed to identify any brain regions consistently associated with Parkinson's dementia, showing major heterogeneity across studies. In contrast, coordinate-based network mapping found that these heterogeneous neuroimaging findings localized to a specific brain network centred on the hippocampus. Next, we tested whether this network showed symptom specificity and stage specificity by performing two further analyses. We tested symptom specificity by examining studies of Parkinson's hallucinations (9 studies, 402 patients) that are frequently co-morbid with Parkinson's dementia. We tested for stage specificity by using studies of mild cognitive impairment in Parkinson's disease (15 studies, 844 patients). Coordinate-based network mapping revealed that correlates of visual hallucinations fell within a network centred on bilateral lateral geniculate nucleus and correlates of mild cognitive impairment in Parkinson's disease fell within a network centred on posterior default mode network. In both cases, the identified networks were distinct from the hippocampal network of Parkinson's dementia. Our results link heterogeneous neuroimaging findings in Parkinson's dementia to a common network centred on the hippocampus. This finding was symptom and stage-specific, with implications for understanding Parkinson's dementia and heterogeneity of neuroimaging findings in general.

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.

Biomarkers for Dementia, Fatigue, and Depression in Parkinson's Disease

Parkinson's disease is a common multisystem neurodegenerative disorder characterized by typical motor and non-motor symptoms. There is an urgent need for biomarkers for assessment of disease severity, complications and prognosis. In addition, biomarkers reporting the underlying pathophysiology assist in understanding the disease and developing neuroprotective therapies. Ultimately, biomarkers could be used to develop a more efficient personalized approach for clinical trials and treatment strategies. With the goal to improve quality of life in Parkinson's disease it is essential to understand and objectively monitor non-motor symptoms. This narrative review provides an overview of recent developments of biomarkers (biofluid samples and imaging) for three common neuropsychological syndromes in Parkinson's disease: dementia, fatigue, and depression.

Current treatment of behavioral and cognitive symptoms of Parkinson's disease

Cognitive and behavioral symptoms are common in Parkinson's disease, may occur even in the prodromal stages of the disease, worsen with disease progression, and surpass motor symptoms as the major factors affecting patient quality of life and caregiver burden. The symptoms may be caused by the disease pathology or they may represent adverse effects of treatment, or both etiological factors may contribute. Although many of these symptoms are related to dopaminergic dysfunction or dopaminergic medication, other neurotransmitters are involved as well. Behavioral symptoms including impulse control disorders, apathy, psychosis, as well as mild cognitive impairment and dementia are reviewed with a special focus on current treatment approaches.

Multimodal magnetic resonance imaging investigation of basal forebrain damage and cognitive deficits in Parkinson's disease

Background

Cognitive deficits in Parkinson's disease (PD) may result from damage in the cortex as well as in the dopaminergic, noradrenergic, and cholinergic inputs to the cortex. Cholinergic inputs to the cortex mainly originate from the basal forebrain and are clustered in several regions, called Ch1 to Ch4, that project to the hippocampus (Ch1‐2), the olfactory bulb (Ch3), and the cortex and amygdala (Ch4).

Objective

We investigated changes in basal forebrain and their role in cognitive deficits in PD.

Methods

We studied 52 nondemented patients with PD (Hoehn & Yahr 1‐2) and 25 age‐matched healthy controls using diffusion and resting state functional MRI.

Results

PD patients had a loss of structural integrity within the Ch1‐2 and Ch3‐4 nuclei of the basal forebrain as well as in the fornix. Tractography showed that the probability of anatomical connection was decreased in PD between Ch3‐4 and the associative prefrontal cortex, occipital cortex, and peri‐insular regions. There was a reduction in functional connectivity between Ch1‐2 and the bilateral hippocampi and parahippocampal gyri, the left middle and superior temporal gyri, and the left fusiform gyrus and between Ch3‐4 and the right inferior frontal gyrus and the right and left thalamus. In Ch1‐2, loss of structural integrity and connectivity correlated with scores at the memory tests, whereas changes in Ch3‐4 correlated with scores of global cognition and executive functions.

Conclusion

This study highlights the association between deficits of different cholinergic nuclei of the basal forebrain and the extent of cognitive impairments in nondemented PD patients. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Episodic recognition memory and the hippocampus in Parkinson's disease: A review

Parkinson's disease is a progressive neurodegenerative disorder of aging. The hallmark pathophysiology includes the development of neuronal Lewy bodies in the substantia nigra of the midbrain with subsequent loss of dopaminergic neurons. These neuronal losses lead to the characteristic motor symptoms of bradykinesia, rigidity, and rest tremor. In addition to these cardinal motor symptoms patients with PD experience a wide range of non-motor symptoms, the most important being cognitive impairments that in many circumstances lead to dementia. People with PD experience a wide range of cognitive impairments; in this review we will focus on memory impairment in PD and specifically episodic memory, which are memories of day-to-day events of life. Importantly, these memory impairments severely impact the lives of patients and caregivers alike. Traditionally episodic memory is considered to be markedly dependent on the hippocampus; therefore, it is important to understand the exact nature of PD episodic memory deficits in relation to hippocampal function and dysfunction. In this review, we discuss an aspect of episodic memory called recognition memory and its subcomponents called recollection and familiarity. Recognition memory is believed to be impaired in PD; thus, we discuss what aspects of the hippocampus are expected to be deficient in function as they relate to these recognition memory impairments. In addition to the hippocampus as a whole, we will discuss the role of hippocampal subfields in recognition memory impairments.

Exercise as a therapeutic intervention for motor and non-motor symptoms in Parkinson's disease: Evidence from rodent models

Parkinson's disease (PD) is characterised by degeneration of dopaminergic neurons of the nigrostriatal pathway, which leads to the cardinal motor symptoms of the disease - tremor, rigidity and postural instability. A number of non-motor symptoms are also associated with PD, including cognitive impairment, mood disturbances and dysfunction of gastrointestinal and autonomic systems. Current therapies provide symptomatic relief but do not halt the disease process, so there is an urgent need for preventative strategies. Lifestyle interventions such as aerobic exercise have shown potential to lower the risk of developing PD and to alleviate both motor and non-motor symptoms. However, there is a lack of large-scale randomised clinical trials that have employed exercise in PD patients. This review will focus on the evidence from studies on rodent models of PD, for employing exercise as an intervention for both motor and non-motor symptoms.

Patterns of Grey Matter Atrophy at Different Stages of Parkinson's and Alzheimer's Diseases and Relation to Cognition

Using MRI, a characteristic pattern of grey matter (GM) atrophy has been described in the early stages of Alzheimer's disease (AD); GM patterns at different stages of Parkinson's disease (PD) have been inconclusive. Few studies have directly compared structural changes in groups with mild cognitive impairment (MCI) caused by different pathologies (AD, PD). We used several analytical methods to determine GM changes at different stages of both PD and AD. We also evaluated associations between GM changes and cognitive measurements. Altogether 144 subjects were evaluated: PD with normal cognition (PD-NC; n = 23), PD with MCI (PD-MCI; n = 24), amnestic MCI (aMCI; n = 27), AD (n = 12), and age-matched healthy controls (HC; n = 58). All subjects underwent structural MRI and cognitive examination. GM volumes were analysed using two different techniques: voxel-based morphometry (VBM) and source-based morphometry (SBM), which is a multivariate method. In addition, cortical thickness (CT) was evaluated to assess between-group differences in GM. The cognitive domain z-scores were correlated with GM changes in individual patient groups. GM atrophy in the anterior and posterior cingulate, as measured by VBM, in the temporo-fronto-parietal component, as measured by SBM, and in the posterior cortical regions as well as in the anterior cingulate and frontal region, as measured by CT, differentiated aMCI from HC. Major hippocampal and temporal lobe atrophy (VBM, SBM) and to some extent occipital atrophy (SBM) differentiated AD from aMCI and from HC. Correlations with cognitive deficits were present only in the AD group. PD-MCI showed greater GM atrophy than PD-NC in the orbitofrontal regions (VBM), which was related to memory z-scores, and in the left superior parietal lobule (CT); more widespread limbic and fronto-parieto-occipital neocortical atrophy (all methods) differentiated this group from HC. Only CT revealed subtle GM atrophy in the anterior cingulate, precuneus, and temporal neocortex in PD-NC as compared to HC. None of the methods differentiated PD-MCI from aMCI. Both MCI groups showed distinct limbic and fronto-temporo-parietal neocortical atrophy compared to HC with no specific between-group differences. AD subjects displayed a typical pattern of major temporal lobe atrophy which was associated with deficits in all cognitive domains. VBM and CT were more sensitive than SBM in identifying frontal and posterior cortical atrophy in PD-MCI as compared to PD-NC. Our data support the notion that the results of studies using different analytical methods cannot be compared directly. Only CT measures revealed some subtle differences between HC and PD-NC.

Source-Based Morphometry Multivariate Approach to Analyze [123I]FP-CIT SPECT Imaging

PURPOSE

[¹²³I]FP-CIT (DaTSCAN®) single-photon emission computed tomography (SPECT) imaging is widely used to study neurodegenerative parkinsonism, by measuring presynaptic dopamine transporter (DAT) in striatal regions. Beyond DAT, [¹²³I]FP-CIT may be considered for other monoaminergic systems, in particular the serotonin transporter (SERT). Independent component analysis (ICA) implemented in source-based morphometry (SBM) could represent an alternative method to explore monoaminergic pathways, studying the relationship among voxels and grouping them into "neurotransmission" networks.

PROCEDURES

One hundred forty-three subjects [84 with Parkinson's disease (PD) and 59 control individuals (CG)] underwent DATSCAN® imaging. The [¹²³I]FP-CIT binding was evaluated by multivariate SBM approach, as well as by a whole-brain voxel-wise univariate (statistical parametric mapping, SPM) approach.

RESULTS

As compared to the univariate whole-brain approach (SPM) (only demonstrating striatal [¹²³I]FP-CIT binding reduction in PD group), SBM identified six sources of non-artefactual origin, including basal ganglia and cortical regions as well as brainstem. Among them, three sources (basal ganglia and cortical regions) presented loading scores (as index of [¹²³I]FP-CIT binding) significantly different between PD and CG. Notably, even if not significantly different between PD and CG, the remaining three non-artefactual sources were characterized by a predominant frontal, brainstem, and occipito-temporal involvement.

CONCLUSION

The concept of source blind separation by the application of ICA (as implemented in SBM) represents a feasible approach to be considered in [¹²³I]FP-CIT (DaTSCAN^®) SPECT imaging. Taking advantage of this multivariate analysis, specific patterns of variance can be identified (involving either striatal than extrastriatal regions) that could be useful in differentiating neurodegenerative parkinsonisms.

Are dementia with Lewy bodies and Parkinson's disease dementia the same disease?

BACKGROUND

Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), which share many clinical, neurochemical, and morphological features, have been incorporated into DSM-5 as two separate entities of major neurocognitive disorders with Lewy bodies. Despite clinical overlap, their diagnosis is based on an arbitrary distinction concerning the time of onset of motor and cognitive symptoms, namely as early cognitive impairment in DLB and later onset following that of motor symptoms in PDD. Their morphological hallmarks - cortical and subcortical α-synuclein/Lewy body plus β-amyloid and tau pathologies - are similar, but clinical differences at onset suggest some dissimilar profiles. Based on recent publications, including the fourth consensus report of the DLB Consortium, a critical overview is provided herein.

DISCUSSION

The clinical constellations of DLB and PDD include cognitive impairment, parkinsonism, visual hallucinations, and fluctuating attention. Intravitam PET and postmortem studies have revealed a more pronounced cortical atrophy, elevated cortical and limbic Lewy body pathologies, higher Aβ and tau loads in cortex and striatum in DLB compared to PDD, and earlier cognitive defects in DLB. Conversely, multitracer PET studies have shown no differences in cortical and striatal cholinergic and dopaminergic deficits. Clinical management of both DLB and PDD includes cholinesterase inhibitors and other pharmacologic and non-drug strategies, yet with only mild symptomatic effects. Currently, no disease-modifying therapies are available.

CONCLUSION

DLB and PDD are important dementia syndromes that overlap in many clinical features, genetics, neuropathology, and management. They are currently considered as subtypes of an α-synuclein-associated disease spectrum (Lewy body diseases), from incidental Lewy body disease and non-demented Parkinson's disease to PDD, DLB, and DLB with Alzheimer's disease at the most severe end. Cognitive impairment in these disorders is induced not only by α-synuclein-related neurodegeneration but by multiple regional pathological scores. Both DLB and PDD show heterogeneous pathology and neurochemistry, suggesting that they share important common underlying molecular pathogenesis with Alzheimer's disease and other proteinopathies. While we prefer to view DLB and PDD as extremes on a continuum, there remains a pressing need to more clearly differentiate these syndromes and to understand the synucleinopathy processes leading to either one.

Altered modular organization of intrinsic brain functional networks in patients with Parkinson's disease

Although previous studies reported altered topology of brain functional networks in patients with Parkinson's disease (PD), the modular organization of brain functional networks in PD patients remains largely unknown. Using the resting-state functional MRI (R-fMRI) and graph theory, we examined the modular organization of brain functional networks in 32 unmedicated patients with early-to-mid motor stage PD and 31 healthy controls. Compared to the controls, the PD patients tended to show decreased integrity and segregation, both within and between modules. This was inferred by significantly increased intra-modular characteristic path length (L _p) within four modules: mPFC, SN, SMN, and FPN, decreased inter-modular functional connectivity (FC) between mPFC and SN, SMN, and VN, and decreased intra-modular clustering in the PD patients. Intra-modular characteristic path length within the mPFC showed significantly positive correlation with general cognitive ability in the PD group. Receiver operating characteristic (ROC) analysis revealed that FC between mPFC and SN had the highest significant accuracy in differentiating the patients from the controls. Our findings may provide new insight in understanding the pathological changes that underlie impairment in cognition and movement in Parkinson's disease.

Multimodal neuroimaging and behavioral assessment of α-synuclein polymorphism rs356219 in older adults

The single-nucleotide polymorphism rs356219 in the α-synuclein (SNCA) gene has been shown to significantly contribute to an earlier age at onset of Parkinson's disease (PD), and regulates SNCA expression in PD brain regions, blood, and plasma. Here, we used multimodal magnetic resonance imaging (MRI) to study healthy adults with and without the rs356219 risk genotype. Motor and cognitive tests were administered, and all participants underwent functional and structural MRI. Imaging analyses included (1) task-based functional MRI; (2) task-based functional connectivity; (3) free-water diffusion MRI of the substantia nigra; (4) voxel-based morphometry; and (5) surface-based morphometry. There were no differences between the 2 groups in motor and cognitive performance, or brain structure. However, carrying a PD risk variant was associated with reduced functional activity in the posterior putamen and primary motor cortex. Moreover, the posterior putamen had reduced functional connectivity with the motor cortex during motor control in those with a risk genotype compared to those without. These findings point to functional abnormalities in the striatocortical circuit of rs356219 risk genotype carriers.

Association of grey matter changes with stability and flexibility of prediction in akinetic-rigid Parkinson's disease

Parkinson's disease (PD), which is caused by degeneration of dopaminergic neurons in the midbrain, results in a heterogeneous clinical picture including cognitive decline. Since the phasic signal of dopamine neurons is proposed to guide learning by signifying mismatches between subjects' expectations and external events, we here investigated whether akinetic-rigid PD patients without mild cognitive impairment exhibit difficulties in dealing with either relevant (requiring flexibility) or irrelevant (requiring stability) prediction errors. Following our previous study on flexibility and stability in prediction (Trempler et al. J Cogn Neurosci 29(2):298-309, 2017), we then assessed whether deficits would correspond with specific structural alterations in dopaminergic regions as well as in inferior frontal cortex, medial prefrontal cortex, and the hippocampus. Twenty-one healthy controls and twenty-one akinetic-rigid PD patients on and off medication performed a task which required to serially predict upcoming items. Switches between predictable sequences had to be indicated via button press, whereas sequence omissions had to be ignored. Independent of the disease, midbrain volume was related to a general response bias to unexpected events, whereas right putamen volume correlated with the ability to discriminate between relevant and irrelevant prediction errors. However, patients compared with healthy participants showed deficits in stabilisation against irrelevant prediction errors, associated with thickness of right inferior frontal gyrus and left medial prefrontal cortex. Flexible updating due to relevant prediction errors was also affected in patients compared with controls and associated with right hippocampus volume. Dopaminergic medication influenced behavioural performance across, but not within the patients. Our exploratory study warrants further research on deficient prediction error processing and its structural correlates as a core of cognitive symptoms occurring already in early stages of the disease.

White matter alterations in Parkinson's disease with normal cognition precede grey matter atrophy

INTRODUCTION

While progressive MRI brain changes characterize advanced Parkinson's disease (PD), little has been discovered about structural alterations in the earliest phase of the disease, i.e. in patients with motor symptoms and with normal cognition. Our study aimed to detect grey matter (GM) and white matter (WM) changes in PD patients without cognitive impairment.

METHODS

Twenty PD patients and twenty-one healthy controls (HC) were tested for attention, executive function, working memory, and visuospatial and language domains. High-resolution T1-weighted and 60 directional diffusion-weighted 3T MRI images were acquired. The cortical, deep GM and WM volumes and density, as well as the diffusion properties of WM, were calculated. Analyses were repeated on data flipped to the side of the disease origin.

RESULTS

PD patients did not show any significant differences from HC in cognitive functioning or in brain volumes. Decreased GM intensity was found in the left superior parietal lobe in the right (p<0.02) and left (p<0.01) flipped data. The analysis of original, un-flipped data demonstrated elevated axial diffusivity (p<0.01) in the superior and anterior corona radiata, internal capsule, and external capsule in the left hemisphere of PD relative to HC, while higher mean and radial diffusivity were discovered in the right (p<0.02 and p<0.03, respectively) and left (p<0.02 and p<0.02, respectively) in the fronto-temporal WM utilizing flipped data.

CONCLUSIONS

PD patients without cognitive impairment and GM atrophy demonstrated widespread alterations of WM microstructure. Thus, WM impairment in PD might be a sensitive sign preceding the neuronal loss in associated GM regions.

Dementia with Lewy bodies and Parkinson's disease-dementia: current concepts and controversies

Dementia with Lewy bodies (DLB) and Parkinson's disease-dementia (PDD), although sharing many clinical, neurochemical and morphological features, according to DSM-5, are two entities of major neurocognitive disorders with Lewy bodies of unknown etiology. Despite considerable clinical overlap, their diagnosis is based on an arbitrary distinction between the time of onset of motor and cognitive symptoms: dementia often preceding parkinsonism in DLB and onset of cognitive impairment after onset of motor symptoms in PDD. Both are characterized morphologically by widespread cortical and subcortical α-synuclein/Lewy body plus β-amyloid and tau pathologies. Based on recent publications, including the fourth consensus report of the DLB Consortium, a critical overview is given. The clinical features of DLB and PDD include cognitive impairment, parkinsonism, visual hallucinations, and fluctuating attention. Intravitam PET and post-mortem studies revealed more pronounced cortical atrophy, elevated cortical and limbic Lewy pathologies (with APOE ε4), apart from higher prevalence of Alzheimer pathology in DLB than PDD. These changes may account for earlier onset and greater severity of cognitive defects in DLB, while multitracer PET studies showed no differences in cholinergic and dopaminergic deficits. DLB and PDD sharing genetic, neurochemical, and morphologic factors are likely to represent two subtypes of an α-synuclein-associated disease spectrum (Lewy body diseases), beginning with incidental Lewy body disease-PD-nondemented-PDD-DLB (no parkinsonism)-DLB with Alzheimer's disease (DLB-AD) at the most severe end, although DLB does not begin with PD/PDD and does not always progress to DLB-AD, while others consider them as the same disease. Both DLB and PDD show heterogeneous pathology and neurochemistry, suggesting that they share important common underlying molecular pathogenesis with AD and other proteinopathies. Cognitive impairment is not only induced by α-synuclein-caused neurodegeneration but by multiple regional pathological scores. Recent animal models and human post-mortem studies have provided important insights into the pathophysiology of DLB/PDD showing some differences, e.g., different spreading patterns of α-synuclein pathology, but the basic pathogenic mechanisms leading to the heterogeneity between both disorders deserve further elucidation. In view of the controversies about the nosology and pathogenesis of both syndromes, there remains a pressing need to differentiate them more clearly and to understand the processes leading these synucleinopathies to cause one disorder or the other. Clinical management of both disorders includes cholinesterase inhibitors, other pharmacologic and nonpharmacologic strategies, but these have only a mild symptomatic effect. Currently, no disease-modifying therapies are available.