Fiber-specific white matter reductions in Parkinson hallucinations and visual dysfunction

Fixel-Based Analysis Reveals Tau-Related White Matter Changes in Early Stages of Alzheimer's Disease

Several studies have shown white matter (WM) abnormalities in Alzheimer's disease (AD) using diffusion tensor imaging (DTI). Nonetheless, robust characterization of WM changes has been challenging due to the methodological limitations of DTI. We applied fixel-based analyses (FBA) to examine microscopic differences in fiber density (FD) and macroscopic changes in fiber cross-section (FC) in early stages of AD (N = 393, 212 females). FBA was also compared with DTI, free-water corrected (FW)-DTI and diffusion kurtosis imaging (DKI). We further investigated the correlation of FBA and tensor-derived metrics with AD pathology and cognition. FBA metrics were decreased in the entire cingulum bundle, uncinate fasciculus and anterior thalamic radiations in Aβ-positive patients with mild cognitive impairment compared to control groups. Metrics derived from DKI, and FW-DTI showed similar alterations whereas WM degeneration detected by DTI was more widespread. Tau-PET uptake in medial temporal regions was only correlated with reduced FC mainly in the parahippocampal cingulum in Aβ-positive individuals. This tau-related WM alteration was also associated with impaired memory. Despite the spatially extensive between-group differences in DTI-metrics, the link between WM and tau aggregation was only revealed using FBA metrics implying high sensitivity but low specificity of DTI-based measures in identifying subtle tau-related WM degeneration. No relationship was found between amyloid load and any diffusion-MRI measures. Our results indicate that early tau-related WM alterations in AD are due to macrostructural changes specifically captured by FBA metrics. Thus, future studies assessing the effects of AD pathology in WM tracts should consider using FBA metrics.

Machine Learning Analysis Classifies Patients with Primary Angle-Closure Glaucoma Using Abnormal Brain White Matter Function

Objective

Primary angle-closure glaucoma (PACG) is a globally prevalent, irreversible eye disease leading to blindness. Previous neuroimaging studies demonstrated that PACG patients were associated with gray matter function changes. However, whether the white matter(WM) function changes in PACG patients remains unknown. The purpose of the study is to investigate WM function changes in the PACG patients.

Methods

In total, 40 PACG patients and 40 well-matched HCs participated in our study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. We compared between-group differences between PACG patients and HC in the WM function using amplitude of low-frequency fluctuations (ALFF). In addition, the SVM method was applied to the construction of the PACG classification model.

Results

Compared with the HC group, ALFF was attenuated in right posterior thalamic radiation (include optic radiation), splenium of corpus callosum, and left tapetum in the PACG group, the results are statistically significant (GRF correction, voxel-level P < 0.001, cluster-level P < 0.05). Furthermore, the SVM classification had an accuracy of 80.0% and an area under the curve (AUC) of 0.86 for distinguishing patients with PACG from HC.

Conclusion

The findings of our study uncover abnormal WM functional alterations in PACG patients and mainly involves vision-related regions. These findings provide new insights into widespread brain damage in PACG from an alternative WM functional perspective.

Parkinson disease psychosis: from phenomenology to neurobiological mechanisms

Parkinson disease (PD) psychosis (PDP) is a spectrum of illusions, hallucinations and delusions that are associated with PD throughout its disease course. Psychotic phenomena can manifest from the earliest stages of PD and might follow a continuum from minor hallucinations to structured hallucinations and delusions. Initially, PDP was considered to be a complication associated with dopaminergic drug use. However, subsequent research has provided evidence that PDP arises from the progression of brain alterations caused by PD itself, coupled with the use of dopaminergic drugs. The combined dysfunction of attentional control systems, sensory processing, limbic structures, the default mode network and thalamocortical connections provides a conceptual framework to explain how new incoming stimuli are incorrectly categorized, and how aberrant hierarchical predictive processing can produce false percepts that intrude into the stream of consciousness. The past decade has seen the publication of new data on the phenomenology and neurobiological basis of PDP from the initial stages of the disease, as well as the neurotransmitter systems involved in PDP initiation and progression. In this Review, we discuss the latest clinical, neuroimaging and neurochemical evidence that could aid early identification of psychotic phenomena in PD and inform the discovery of new therapeutic targets and strategies.

Microstructural integrity of the locus coeruleus and its tracts reflect noradrenergic degeneration in Alzheimer's disease and Parkinson's disease

BACKGROUND

Degeneration of the locus coeruleus (LC) noradrenergic system contributes to clinical symptoms in Alzheimer's disease (AD) and Parkinson's disease (PD). Diffusion magnetic resonance imaging (MRI) has the potential to evaluate the integrity of the LC noradrenergic system. The aim of the current study was to determine whether the diffusion MRI-measured integrity of the LC and its tracts are sensitive to noradrenergic degeneration in AD and PD.

METHODS

Post-mortem in situ T1-weighted and multi-shell diffusion MRI was performed for 9 AD, 14 PD, and 8 control brain donors. Fractional anisotropy (FA) and mean diffusivity were derived from the LC, and from tracts between the LC and the anterior cingulate cortex, the dorsolateral prefrontal cortex (DLPFC), the primary motor cortex (M1) or the hippocampus. Brain tissue sections of the LC and cortical regions were obtained and immunostained for dopamine-beta hydroxylase (DBH) to quantify noradrenergic cell density and fiber load. Group comparisons and correlations between outcome measures were performed using linear regression and partial correlations.

RESULTS

The AD and PD cases showed loss of LC noradrenergic cells and fibers. In the cortex, the AD cases showed increased DBH + immunoreactivity in the DLPFC compared to PD cases and controls, while PD cases showed reduced DBH + immunoreactivity in the M1 compared to controls. Higher FA within the LC was found for AD, which was correlated with loss of noradrenergic cells and fibers in the LC. Increased FA of the LC-DLPFC tract was correlated with LC noradrenergic fiber loss in the combined AD and control group, whereas the increased FA of the LC-M1 tract was correlated with LC noradrenergic neuronal loss in the combined PD and control group. The tract alterations were not correlated with cortical DBH + immunoreactivity.

CONCLUSIONS

In AD and PD, the diffusion MRI-detected alterations within the LC and its tracts to the DLPFC and the M1 were associated with local noradrenergic neuronal loss within the LC, rather than noradrenergic changes in the cortex.

One-shot segmentation of novel white matter tracts via extensive data augmentation and adaptive knowledge transfer

The use of convolutional neural networks (CNNs) has allowed accurate white matter (WM) tract segmentation on diffusion magnetic resonance imaging (dMRI). To train the CNN-based segmentation models, a large number of scans on which WM tracts are annotated need to be collected, and these annotated scans can be accumulated over a long period of time. However, when novel WM tracts that are different from existing annotated WM tracts are of interest, additional annotations are required for their segmentation. Due to the cost of manual annotations, methods have been developed for few-shot segmentation of novel WM tracts, where the segmentation knowledge is transferred from existing WM tracts to novel WM tracts and the amount of annotated data for novel WM tracts is reduced. Despite these developments, it is desirable to further reduce the amount of annotated data to the one-shot setting with a single annotated image. To address this problem, we develop an approach to one-shot segmentation of novel WM tracts. Our method follows the existing pretraining/fine-tuning framework that transfers segmentation knowledge from existing to novel WM tracts. First, as there is extremely scarce annotated data in the one-shot setting, we design several different data augmentation strategies so that extensive data augmentation can be performed to obtain extra synthetic training data. The data augmentation strategies are based on image masking and thus applicable to the one-shot setting. Second, to address overfitting and knowledge forgetting in the fine-tuning stage that can be more severe given limited training data, we propose an adaptive knowledge transfer strategy that selects the network weights to be updated. The data augmentation and adaptive knowledge transfer strategies are combined to train the segmentation model. Considering that the different data augmentation strategies can generate synthetic data that contain potentially conflicting information, we apply the data augmentation strategies separately, each leading to a different segmentation model. The results predicted by the different models are fused to produce the final segmentation. We validated our method on two brain dMRI datasets, including a public dataset and an in-house dataset. Different settings were considered for the validation, and the results show that the proposed method improves the one-shot segmentation of novel WM tracts.

Fibre density and fibre-bundle cross-section of the corticospinal tract are distinctly linked to psychosis-specific symptoms in antipsychotic-naïve patients with first-episode schizophrenia

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia.

Segmental disturbance of white matter microstructure in predicting mild cognitive impairment in idiopathic Parkinson's disease: An individualized study based on automated fiber quantification tractography

PURPOSE

The neurobiological mechanisms and an early identification of MCI in idiopathic Parkinson's disease (IPD) remain unclear. To investigate the abnormalities of types of white matter (WM) fiber tracts segmentally and establish reliable indicator in IPD-MCI.

METHODS

Forty IPD with normal cognition (IPD-NCI), thirty IPD-MCI, and thirty healthy controls were included. Automated fiber quantification was applied to extract the fractional anisotropy (FA) and mean diffusivity (MD) values at 100 locations along the major fibers. Partial correlation was performed between diffusion values and cognitive performance. Furthermore, machine learning analyses were conducted to determine the imaging biomarker of MCI. Permutation tests were performed to evaluate the pointwise differences under the FWE correction.

RESULTS

IPD-MCI had similar but more severe and widespread WM degeneration in the association, projection, and commissural fibers compared with IPD-NCI. Meanwhile, IPD-MCI showed distinct degeneration pattern in the association fibers. The FA of the anterior segment of right inferior fronto-occipital fasciculus (IFOF) was positively correlated with MoCA (P < 0.05) and executive function (P < 0.05). The MD of the middle and posterior segment of left superior longitudinal fasciculus (SLF) was negatively correlated with MoCA P < 0.05), executive (P < 0.05), visuospatial function (P < 0.05). Furthermore, the AUC of support vector machine model was 0.80 in the validation dataset. The FA of anterior segment of right IFOF contribute the most.

CONCLUSION

This study demonstrated that regional tract-specific microstructural degeneration, especially the association fibers, can be used to predict MCI in IPD. Especially, the right IFOF may be a significant imaging biomarker in predicting IPD with MCI.

Nigral Pathology Contributes to Microstructural Integrity of Striatal and Frontal Tracts in Parkinson's Disease

BACKGROUND

Motor and cognitive impairment in Parkinson's disease (PD) is associated with dopaminergic dysfunction that stems from substantia nigra (SN) degeneration and concomitant α-synuclein accumulation. Diffusion magnetic resonance imaging (MRI) can detect microstructural alterations of the SN and its tracts to (sub)cortical regions, but their pathological sensitivity is still poorly understood.

OBJECTIVE

To unravel the pathological substrate(s) underlying microstructural alterations of SN, and its tracts to the dorsal striatum and dorsolateral prefrontal cortex (DLPFC) in PD.

METHODS

Combining post-mortem in situ MRI and histopathology, T1-weighted and diffusion MRI, and neuropathological samples of nine PD, six PD with dementia (PDD), five dementia with Lewy bodies (DLB), and 10 control donors were collected. From diffusion MRI, mean diffusivity (MD) and fractional anisotropy (FA) were derived from the SN, and tracts between the SN and caudate nucleus, putamen, and DLPFC. Phosphorylated-Ser129-α-synuclein and tyrosine hydroxylase immunohistochemistry was included to quantify nigral Lewy pathology and dopaminergic degeneration, respectively.

RESULTS

Compared to controls, PD and PDD/DLB showed increased MD of the SN and SN-DLPFC tract, as well as increased FA of the SN-caudate nucleus tract. Both PD and PDD/DLB showed nigral Lewy pathology and dopaminergic loss compared to controls. Increased MD of the SN and FA of SN-caudate nucleus tract were associated with SN dopaminergic loss. Whereas increased MD of the SN-DLPFC tract was associated with increased SN Lewy neurite load.

CONCLUSIONS

In PD and PDD/DLB, diffusion MRI captures microstructural alterations of the SN and tracts to the dorsal striatum and DLPFC, which differentially associates with SN dopaminergic degeneration and Lewy neurite pathology. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Structural and Functional Imaging Correlates of Visual Hallucinations in Parkinson's Disease

PURPOSE OF REVIEW

To review recent structural and functional MRI studies of visual hallucinations in Parkinson's disease.

RECENT FINDINGS

Previously, neuroimaging had shown inconsistent findings in patients with Parkinson's hallucinations, especially in studies examining grey matter volume. However, recent advances in structural and functional MRI techniques allow better estimates of structural connections, as well as the direction of connectivity in functional MRI. These provide more sensitive measures of changes in structural connectivity and allow models of the changes in directional functional connectivity to be tested. We identified 27 relevant studies and found that grey matter imaging continues to show heterogeneous findings in Parkinson's patients with visual hallucinations. Newer approaches in diffusion imaging and functional MRI are consistent with emerging models of Parkinson's hallucinations, suggesting shifts in attentional networks. In particular, reduced bottom-up, incoming sensory information, and over-weighting of top-down signals appear to be important drivers of visual hallucinations in Parkinson's disease.

Hiccups, Hypersalivation, Hallucinations in Parkinson's Disease: New Insights, Mechanisms, Pathophysiology, and Management

Parkinson's disease (PD) is a chronic, progressive neurological disorder and the second most common neurodegenerative condition. We report three common but overlooked symptoms in PD-hiccups, hypersalivation, and hallucinations-in terms of their prevalence, pathophysiology, and up-to-date evidence-based treatment strategies. Whilst all these three symptoms do occur in many other neurological and non-neurological conditions, early recognition and treatment are paramount. Whilst hiccups affect 3% of healthy people, their rate of occurrence is higher (20%) in patients with PD. Hypersalivation (Sialorrhea) is another common neurological manifestation of many neurological and other neurodegenerative conditions such as motor neuron disease (MND), with a median prevalence rate of 56% (range: 32-74%). A 42% prevalence of sialorrhea is also reported in sub-optimally treated patients with PD. Hallucinations, especially visual hallucinations, are commonly reported, with a prevalence of 32-63% in PD, and a 55-78% prevalence is noted in patients with dementia with Lewy bodies (DLB), followed by tactile hallucinations, which are indicated by a sensation of crawling bugs or imaginary creatures across the skin surface. Whilst mainstay and primary management strategies for all these three symptoms are carried out through history taking, it is also essential to identify and treat possible potential triggers such as infection, minimise or avoid causative (such as drug-induced) factors, and especially carry out patient education before considering more definitive treatment strategies, such as botulinum toxin therapies for hypersalivation, to improve the quality of life of patients. This original review paper aims to provide a comprehensive overview of the disease mechanisms, pathophysiology, and management of hiccups, hypersalivation, and hallucinations in Parkinson's disease.

Baseline free water within the visual processing system predicts future psychosis in Parkinson disease

BACKGROUND AND PURPOSE

As psychosis is associated with decreased quality of life, increased institutionalization, and mortality in Parkinson disease (PD), it is essential to identify individuals at risk for future psychosis. This longitudinal study aimed to investigate whether diffusion tensor imaging (DTI) metrics of white matter hold independent utility for predicting future psychosis in PD, and whether they could be combined with clinical predictors to improve the prognostication of PD psychosis.

METHODS

This study included 123 newly diagnosed PD patients collected in the Parkinson's Progression Markers Initiative. Tract-based spatial statistics were used to compare baseline DTI metrics between PD patients who developed psychosis and those who did not during follow-up. Binary logistic regression analyses were performed to identify the clinical and white matter markers predictive of psychosis.

RESULTS

Among DTI measures, both higher baseline whole brain (odds ratio [OR] = 1.711, p = 0.016) free water (FW) and visual processing system (OR = 1.680, p < 0.001) FW were associated with an increased risk of future psychosis. Baseline FW remained a significant indicator of future psychosis in PD after controlling for clinical predictors. Moreover, the accuracy of prediction of psychosis using clinical predictors alone (area under the curve [AUC] = 0.742, 95% confidence interval [CI] = 0.655-0.816) was significantly improved by the addition of the visual processing system FW (AUC = 0.856, 95% CI = 0.781-0.912; Delong method, p = 0.022).

CONCLUSIONS

Baseline FW of the visual processing system incurs an independent risk of future psychosis in PD, thus providing an opportunity for multiple-modality marker models to include a white matter marker.

MYELIN, AGING, AND PHYSICAL EXERCISE

Myelin sheath is a structure in neurons fabricated by oligodendrocytes and Schwann cells responsible for increasing the efficiency of neural synapsis, impulse transmission, and providing metabolic support to the axon. They present morpho-functional changes during health aging as deformities of the sheath and its fragmentation, causing an increased load on microglial phagocytosis, with Alzheimer's disease aggravating. Physical exercise has been studied as a possible protective agent for the nervous system, offering benefits to neuroplasticity. In this regard, studies in animal models for Alzheimer's and depression reported the efficiency of physical exercise in protecting against myelin degeneration. A reduction of myelin damage during aging has also been observed in healthy humans. Physical activity promotes oligodendrocyte proliferation and myelin preservation during old age, although some controversies remain. In this review, we will address how effective physical exercise can be as a protective agent of the myelin sheath against the effects of aging in physiological and pathological conditions.

Emerging role of psychosis in Parkinson's disease: From clinical relevance to molecular mechanisms

Parkinson’s disease (PD) is the second most common neurodegenerative disease. Psychosis is one of the common psychiatric presentations in the natural course of PD. PD psychosis is an important non-motor symptom, which is strongly correlated with a poor prognosis. Increasing attention is being given to PD psychosis. In this opinion review, we summarized and analyzed the identification, screening, epidemiology, mechanisms, risk factors, and therapeutic approaches of PD psychosis based on the current clinical evidence. PD psychosis tends to have a negative effect on patients' quality of life and increases the burden of family caregiving. Screening and identification in the early stage of disease is crucial for establishing tailored therapeutic strategies and predicting the long-term outcome. Development of PD psychosis is believed to involve a combination of exogenous and endogenous mechanisms including imbalance of neurotransmitters, structural and network changes, genetic profiles, cognitive impairment, and antiparkinsonian medications. The therapeutic strategy for PD psychosis includes reducing or ceasing the use of dopaminergic drug, antipsychotics, cholinesterase inhibitors, and non-pharmacological interventions. Ongoing clinical trials are expected to provide new insights for tailoring therapy for PD psychosis. Future research based on novel biomarkers and genetic factors may help inform individualized therapeutic strategies.

Changes in dynamic transitions between integrated and segregated states underlie visual hallucinations in Parkinson's disease

Hallucinations are a core feature of psychosis and common in Parkinson's. Their transient, unexpected nature suggests a change in dynamic brain states, but underlying causes are unknown. Here, we examine temporal dynamics and underlying structural connectivity in Parkinson's-hallucinations using a combination of functional and structural MRI, network control theory, neurotransmitter density and genetic analyses. We show that Parkinson's-hallucinators spent more time in a predominantly Segregated functional state with fewer between-state transitions. The transition from integrated-to-segregated state had lower energy cost in Parkinson's-hallucinators; and was therefore potentially preferable. The regional energy needed for this transition was correlated with regional neurotransmitter density and gene expression for serotoninergic, GABAergic, noradrenergic and cholinergic, but not dopaminergic, receptors. We show how the combination of neurochemistry and brain structure jointly shape functional brain dynamics leading to hallucinations and highlight potential therapeutic targets by linking these changes to neurotransmitter systems involved in early sensory and complex visual processing.

White matter fiber-specific degeneration in older adults with metabolic syndrome

OBJECTIVE

Metabolic syndrome (MetS) is defined as a complex of interrelated risk factors for type 2 diabetes and cardiovascular disease, including glucose intolerance, abdominal obesity, hypertension, and dyslipidemia. Studies using diffusion tensor imaging (DTI) have reported white matter (WM) microstructural abnormalities in MetS. However, interpretation of DTI metrics is limited primarily due to the challenges of modeling complex WM structures. The present study used fixel-based analysis (FBA) to assess the effect of MetS on the fiber tract-specific WM microstructure in older adults and its relationship with MetS-related measurements and cognitive and locomotor functions to better understand the pathophysiology of MetS.

METHODS

Fixel-based metrics, including microstructural fiber density (FD), macrostructural fiber-bundle cross-section (FC), and a combination of FD and FC (FDC), were evaluated in 16 healthy controls (no components of MetS; four men; mean age, 71.31 ± 5.06 years), 57 individuals with premetabolic syndrome (preMetS; one or two components of MetS; 29 men; mean age, 72.44 ± 5.82 years), and 46 individuals with MetS (three to five components of MetS; 27 men; mean age, 72.15 ± 4.97 years) using whole-brain exploratory FBA. Tract of interest (TOI) analysis was then performed using TractSeg across 14 selected WM tracts previously associated with MetS. The associations between fixel-based metrics and MetS-related measurements, neuropsychological, and locomotor function tests were also analyzed in individuals with preMetS and MetS combined. In addition, tensor-based metrics (i.e., fractional anisotropy [FA] and mean diffusivity [MD]) were compared among the groups using tract-based spatial statistics (TBSS) analysis.

RESULTS

In whole-brain FBA, individuals with MetS showed significantly lower FD, FC, and FDC compared with healthy controls in WM areas, such as the splenium of the corpus callosum (CC), corticospinal tract (CST), middle cerebellar peduncle (MCP), and superior cerebellar peduncle (SCP). Meanwhile, in fixel-based TOI, significantly reduced FD was observed in individuals with preMetS and MetS in the anterior thalamic radiation, CST, SCP, and splenium of the CC compared with healthy controls, with relatively greater effect sizes observed in individuals with MetS. Compared with healthy controls, significantly reduced FC and FDC were only demonstrated in individuals with MetS, including regions with loss of FD, inferior cerebellar peduncle, inferior fronto-occipital fasciculus, MCP, and superior longitudinal fasciculus part I. Furthermore, negative correlations were observed between FD and Brinkman index of cigarette consumption cumulative amount and between FC or FDC and the Trail Making Test (parts B-A), which is a measure of executive function, waist circumference, or low-density lipoprotein cholesterol. Finally, TBSS analysis revealed that FA and MD were not significantly different among all groups.

CONCLUSIONS

The FBA results demonstrate that substantial axonal loss and atrophy in individuals with MetS and early axonal loss without fiber-bundle morphological changes in those with preMetS within the WM tracts are crucial to cognitive and motor function. FBA also clarified the association between executive dysfunction, abdominal obesity, hyper-low-density lipoprotein cholesterolemia, smoking habit, and compromised WM neural tissue microstructure in MetS.

Investigation of structural brain changes in Charles Bonnet Syndrome

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Reduced grey matter in the occipital cortex in eye disease groups.

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Widespread altered diffusivity in eye disease groups.

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No cortical or white matter changes associated with presence of visual hallucinations.

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Negative association between hippocampal volume and Hallucination severity.

Background and objectives

In Charles Bonnet Syndrome (CBS), visual hallucinations (VH) are experienced by people with sight loss due to eye disease or lesional damage to early visual pathways. The aim of this cross-sectional study was to investigate structural brain changes using magnetic resonance imaging (MRI) in CBS.

Methods

Sixteen CBS patients, 17 with eye disease but no VH, and 19 normally sighted people took part. Participants were imaged on a 3T scanner, with 1 mm resolution T1 weighted structural imaging, and diffusion tensor imaging with 64 diffusion directions.

Results

The three groups were well matched for age, sex and cognitive scores (MMSE). The two eye disease groups were matched on visual acuity. Compared to the sighted controls, we found reduced grey matter in the occipital cortex in both eye disease groups. We also found reductions of fractional anisotropy and increased diffusivity in widespread areas, including occipital tracts, the corpus callosum, and the anterior thalamic radiation. We did not find any significant differences between the eye disease participants with VH versus without VH, but did observe a negative association between hippocampal volume and VH severity in the CBS group.

Discussion

Our findings suggest that although there are cortical and subcortical effects associated with sight loss, structural changes do not explain the occurrence of VHs. CBS may relate instead to connectivity or excitability changes in brain networks linked to vision.

Functional and structural brain network correlates of visual hallucinations in Lewy body dementia

Visual hallucinations are a common feature of Lewy body dementia. Previous studies have shown that visual hallucinations are highly specific in differentiating Lewy body dementia from Alzheimer’s disease dementia and Alzheimer–Lewy body mixed pathology cases. Computational models propose that impairment of visual and attentional networks is aetiologically key to the manifestation of visual hallucinations symptomatology. However, there is still a lack of experimental evidence on functional and structural brain network abnormalities associated with visual hallucinations in Lewy body dementia.

We used EEG source localization and network based statistics to assess differential topographical patterns in Lewy body dementia between 25 participants with visual hallucinations and 17 participants without hallucinations. Diffusion tensor imaging was used to assess structural connectivity between thalamus, basal forebrain and cortical regions belonging to the functionally affected network component in the hallucinating group, as assessed with network based statistics. The number of white matter streamlines within the cortex and between subcortical and cortical regions was compared between hallucinating and not hallucinating groups and correlated with average EEG source connectivity of the affected subnetwork. Moreover, modular organization of the EEG source network was obtained, compared between groups and tested for correlation with structural connectivity.

Network analysis showed that compared to non-hallucinating patients, those with hallucinations feature consistent weakened connectivity within the visual ventral network, and between this network and default mode and ventral attentional networks, but not between or within attentional networks. The occipital lobe was the most functionally disconnected region. Structural analysis yielded significantly affected white matter streamlines connecting the cortical regions to the nucleus basalis of Meynert and the thalamus in hallucinating compared to not hallucinating patients. The number of streamlines in the tract between the basal forebrain and the cortex correlated with cortical functional connectivity in non-hallucinating patients, while a correlation emerged for the white matter streamlines connecting the functionally affected cortical regions in the hallucinating group.

This study proposes, for the first time, differential functional networks between hallucinating and not hallucinating Lewy body dementia patients, and provides empirical evidence for existing models of visual hallucinations. Specifically, the outcome of the present study shows that the hallucinating condition is associated with functional network segregation in Lewy body dementia and supports the involvement of the cholinergic system as proposed in the current literature.

R2* relaxometry analysis for mapping of white matter alteration in Parkinson's disease with mild cognitive impairment

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R2* relaxometry analysis combined with QSM revealed detail of WM alteration in PD-MCI.

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R2* relaxometry analysis can detect slight demyelination in PD-MCI.

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R2* value shows potential for early evaluation of cognitive decline in PD.

Background

R2* relaxometry analysis combined with quantitative susceptibility mapping (QSM), which has high sensitivity to iron deposition, can distinguish microstructural changes of the white matter (WM) and iron deposition, thereby providing a sensitive and biologically specific measure of the WM owing to the changes in myelin and its surrounding environment. This study aimed to explore the microstructural WM alterations associated with cognitive impairment in patients with Parkinson’s disease (PD) using R2* relaxometry analysis combined with QSM.

Materials and methods

We enrolled 24 patients with PD and mild cognitive impairment (PD-MCI), 22 patients with PD and normal cognition (PD-CN), and 19 age- and sex-matched healthy controls (HC). All participants underwent Montreal Cognitive Assessment (MoCA) and brain magnetic resonance imaging, including structural three-dimensional T1-weighted images and multiple spoiled gradient echo sequence (mGRE). The R2* and susceptibility maps were estimated from the multiple magnitude images of mGRE. The susceptibility maps were used for verifying iron deposition in the WM. The voxel-based R2* of the entire WM and its correlation with cognitive performance were analyzed.

Results

In the voxel-based group comparisons, the R2* in the PD-MCI group was lower in some WM regions, including the corpus callosum, than R2* in the PD-CN and HC groups. The mean susceptibility values in almost all brain regions were negative and close-to-zero values, indicating no detectable paramagnetic iron deposition in the WM of all subjects. There was a significant positive correlation between R2* and MoCA in some regions of the WM, mainly the corpus callosum and left hemisphere.

Conclusion

R2* relaxometry analysis for WM microstructural changes provided further biologic insights on demyelination and changes in the surrounding environment, supported by the QSM results demonstrating no iron existence. This analysis highlighted the potential for the early evaluation of cognitive decline in patients with PD.

Longitudinal thalamic white and grey matter changes associated with visual hallucinations in Parkinson's disease

OBJECTIVE

Visual hallucinations are common in Parkinson's disease (PD) and associated with worse outcomes. Large-scale network imbalance is seen in PD-associated hallucinations, but mechanisms remain unclear. As the thalamus is critical in controlling cortical networks, structural thalamic changes could underlie network dysfunction in PD hallucinations.

METHODS

We used whole-brain fixel-based analysis and cortical thickness measures to examine longitudinal white and grey matter changes in 76 patients with PD (15 hallucinators, 61 non-hallucinators) and 26 controls at baseline, and after 18 months. We compared white matter and cortical thickness, adjusting for age, gender, time-between-scans and intracranial volume. To assess thalamic changes, we extracted volumes for 50 thalamic subnuclei (25 each hemisphere) and mean fibre cross-section (FC) for white matter tracts originating in each subnucleus and examined longitudinal change in PD-hallucinators versus non-hallucinators.

RESULTS

PD hallucinators showed white matter changes within the corpus callosum at baseline and extensive posterior tract involvement over time. Less extensive cortical thickness changes were only seen after follow-up. White matter connections from the right medial mediodorsal magnocellular thalamic nucleus showed reduced FC in PD hallucinators at baseline followed by volume reductions longitudinally. After follow-up, almost all thalamic subnuclei showed tract losses in PD hallucinators compared with non-hallucinators.

INTERPRETATION

PD hallucinators show white matter loss particularly in posterior connections and in thalamic nuclei, over time with relatively preserved cortical thickness. The right medial mediodorsal thalamic nucleus shows both connectivity and volume loss in PD hallucinations. Our findings provide mechanistic insights into the drivers of network imbalance in PD hallucinations and potential therapeutic targets.

Mapping brain structural differences and neuroreceptor correlates in Parkinson's disease visual hallucinations

Parkinson's psychosis (PDP) describes a spectrum of symptoms that may arise in Parkinson's disease (PD) including visual hallucinations (VH). Imaging studies investigating the neural correlates of PDP have been inconsistent in their findings, due to differences in study design and limitations of scale. Here we use empirical Bayes harmonisation to pool together structural imaging data from multiple research groups into a large-scale mega-analysis, allowing us to identify cortical regions and networks involved in VH and their relation to receptor binding. Differences of morphometrics analysed show a wider cortical involvement underlying VH than previously recognised, including primary visual cortex and surrounding regions, and the hippocampus, independent of its role in cognitive decline. Structural covariance analyses point to the involvement of the attentional control networks in PD-VH, while associations with receptor density maps suggest neurotransmitter loss may be linked to the cortical changes.

Volumetric Segmentation of White Matter Tracts with Label Embedding

Convolutional neural networks have achieved state-of-the-art performance for white matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI). However, the segmentation can still be difficult for challenging WM tracts with thin bodies or complicated shapes; the segmentation is even more problematic in challenging scenarios with reduced data quality or domain shift between training and test data, which can be easily encountered in clinical settings. In this work, we seek to improve the segmentation of WM tracts, especially for challenging WM tracts in challenging scenarios. In particular, our method is based on volumetric WM tract segmentation, where voxels are directly labeled without performing tractography. To improve the segmentation, we exploit the characteristics of WM tracts that different tracts can cross or overlap and revise the network design accordingly. Specifically, because multiple tracts can co-exist in a voxel, we hypothesize that the different tract labels can be correlated. The tract labels at a single voxel are concatenated as a label vector, the length of which is the number of tract labels. Due to the tract correlation, this label vector can be projected into a lower-dimensional space-referred to as the embedded space-for each voxel, which allows the segmentation network to solve a simpler problem. By predicting the coordinate in the embedded space for the tracts at each voxel and subsequently mapping the coordinate to the label vector with a reconstruction module, the segmentation result can be achieved. To facilitate the learning of the embedded space, an auxiliary label reconstruction loss is integrated with the segmentation accuracy loss during network training, and network training and inference are end-to-end. Our method was validated on two dMRI datasets under various settings. The results show that the proposed method improves the accuracy of WM tract segmentation, and the improvement is more prominent for challenging tracts in challenging scenarios.

Thalamic white matter macrostructure and subnuclei volumes in Parkinson's disease depression

Depression is a common non-motor feature of Parkinson's disease (PD) which confers significant morbidity and is challenging to treat. The thalamus is a key component in the basal ganglia-thalamocortical network critical to the pathogenesis of PD and depression but the precise thalamic subnuclei involved in PD depression have not been identified. We performed structural and diffusion-weighted imaging (DWI) on 76 participants with PD to evaluate the relationship between PD depression and grey and white matter thalamic subnuclear changes. We used a thalamic segmentation method to divide the thalamus into its 50 constituent subnuclei (25 each hemisphere). Fixel-based analysis was used to calculate mean fibre cross-section (FC) for white matter tracts connected to each subnucleus. We assessed volume and FC at baseline and 14-20 months follow-up. A generalised linear mixed model was used to evaluate the relationship between depression, subnuclei volume and mean FC for each thalamic subnucleus. We found that depression scores in PD were associated with lower right pulvinar anterior (PuA) subnucleus volume. Antidepressant use was associated with higher right PuA volume suggesting a possible protective effect of treatment. After follow-up, depression scores were associated with reduced white matter tract macrostructure across almost all tracts connected to thalamic subnuclei. In conclusion, our work implicates the right PuA as a relevant neural structure in PD depression and future work should evaluate its potential as a therapeutic target for PD depression.

The neuropsychiatry of Parkinson's disease: advances and challenges

In people with Parkinson's disease, neuropsychiatric signs and symptoms are common throughout the disease course. These symptoms can be disabling and as clinically relevant as motor symptoms, and their presentation can be similar to, or distinct from, their counterparts in the general population. Correlates and risk factors for developing neuropsychiatric signs and symptoms include demographic, clinical, and psychosocial characteristics. The underlying neurobiology of these presentations is complex and not well understood, with the strongest evidence for neuropathological changes associated with Parkinson's disease, mechanisms linked to dopaminergic therapy, and effects not specific to Parkinson's disease. Assessment instruments and formal diagnostic criteria exist, but there is little routine screening of these signs and symptoms in clinical practice. Mounting evidence supports a range of pharmacological and non-pharmacological interventions, but relatively few efficacious treatment options exist. Optimising the management of neuropsychiatric presentations in people with Parkinson's disease will require additional research, raised awareness, specialised training, and development of innovative models of care.

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

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

Fixel-based evidence of microstructural damage in crossing pathways improves language mapping in Post-stroke aphasia

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FBA shows greater specificity in mapping injured fibers in post-stroke aphasia.

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Intra-axonal volume of axons in dual streams is reduced in post-stroke aphasia.

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FBA could locate more precise segments associated with language defects.

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FBA could attribute language subdomain scores to fiber density of distinct tracts.

Background

The complex crossing-fiber characteristics in the dual-stream system have been ignored by traditional diffusion tensor models regarding disconnections in post-stroke aphasia. It is valuable to identify microstructural damage of crossing-fiber pathways and reveal accurate fiber-specific language mapping in patients with aphasia.

Methods

This cross-sectional study collected magnetic resonance imaging data from 29 participants with post-stroke aphasia in the subacute stage and from 33 age- and sex-matched healthy controls. Fixel-based analysis was performed to examine microstructural fiber density (FD) and bundle cross-section alterations of specific fiber populations in crossing-fiber regions. Group comparisons were performed, and relationships with language scores were assessed.

Results

The aphasic group exhibited significant fixel-wise FD reductions in the dual-stream tracts, including the left inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus, and superior longitudinal fasciculus (SLF) III (family-wise-error-corrected p < 0.05). Voxel- and fixel-wise comparisons revealed mismatched distributions in regions with crossing-fiber nexuses. Fixel-wise correlation analyses revealed significant associations between comprehension impairment and reduced FD in the temporal and frontal segments of the left IFOF, and also mapped naming ability to the IFOF. Average features along the whole course of dominant tracts assessed with tract-wise analyses attributed word-level comprehension to the IFOF (r = 0.723, p < 0.001) and revealed a trend-level correlation between sentence-level comprehension and FD of the SLF III (r = 0.451, p = 0.021). The mean FD of the uncinate fasciculus (UF) and IFOF correlated with total and picture naming scores, and the IFOF also correlated with responsive naming subdomains (Bonferroni corrected p < 0.05).

Conclusions

FD reductions of dual streams suggest that intra-axonal volume reduction constitutes the microstructural damage of white matter integrity in post-stroke aphasia. Fixel-based analysis provides a complementary method of language mapping that identifies fiber-specific tracts in the left hemisphere language network with greater specificity than voxel-based analysis. It precisely locates the precise segments of the IFOF for comprehension, yields fiber-specific evidence for the debated UF-naming association, and reveals dissociative subdomain associations with distinct tracts.

Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities

Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "Fixel-Based Analysis" (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities.

Fiber-specific white matter alterations in early-stage tremor-dominant Parkinson's disease

Using a fixel-based analysis (FBA), we assessed the fiber-specific white matter (WM) alterations in nonmedicated patients with early-stage Parkinson's disease (PD) with tremor-dominant (TD; n = 53; mean age, 61.7 ± 8.7 years) and postural instability and gait disorder (PIGD; n = 27; mean age, 57.8 ± 8.1 years) motor subtypes and age- and sex-matched healthy controls (HC; n = 43; mean age, 61.6 ± 9.2 years) from Parkinson's Progression Markers Initiative dataset. FBA revealed significantly increased macrostructural fiber cross section and a combination of fiber density and cross section metrics within the corticospinal tract in patients with TD-PD compared with HC. Nonetheless, no significant changes in FBA-derived metrics were found in patients with PIGD-PD compared with HC or patients with TD-PD. Our results may provide evidence of WM neural compensation mechanisms in patients with TD-PD marked by increases in fiber bundle size and the ability to relay information between brain regions.

Characterizing white matter alterations subject to clinical laterality in drug-naïve de novo Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by a range of motor and nonmotor symptoms, often with the motor dysfunction initiated unilaterally. Knowledge regarding disease‐related alterations in white matter pathways can effectively help improve the understanding of the disease and propose targeted treatment strategies. Microstructural imaging techniques, including diffusion tensor imaging (DTI), allows inspection of white matter integrity to study the pathogenesis of various neurological conditions. Previous voxel‐based analyses with DTI measures, such as fractional anisotropy and mean diffusivity have uncovered changes in brain regions that are associated with PD, but the conclusions were inconsistent, partially due to small patient cohorts and the lack of consideration for clinical laterality onset, particularly in early PD. Fixel‐based analysis (FBA) is a recent framework that offers tract‐specific insights regarding white matter health, but very few FBA studies on PD exist. We present a study that reveals strengthened and weakened white matter integrity that is subject to symptom laterality in a large drug‐naïve de novo PD cohort using complementary DTI and FBA measures. The findings suggest that the disease gives rise to tissue degeneration and potential re‐organization in the early stage.

Visual Dysfunction Predicts Cognitive Impairment and White Matter Degeneration in Parkinson's Disease

BACKGROUND

Visual dysfunction predicts dementia in Parkinson's disease (PD), but whether this translates to structural change is not known. The objectives of this study were to identify longitudinal white matter changes in patients with Parkinson's disease and low visual function and also in those who developed mild cognitive impairment.

METHODS

We used fixel-based analysis to examine longitudinal white matter change in PD. Diffusion MRI and clinical assessments were performed in 77 patients at baseline (22 low visual function/55 intact vision and 13 PD-mild cognitive impairment/51 normal cognition) and 25 controls and again after 18 months. We compared microstructural changes in fiber density, macrostructural changes in fiber bundle cross-section and combined fiber density and cross-section, across white matter, adjusting for age, sex, and intracranial volume.

RESULTS

Patients with PD and visual dysfunction showed worse cognitive performance at follow-up and were more likely to develop mild cognitive impairment compared with those with normal vision (P = 0.008). Parkinson's with poor visual function showed diffuse microstructural and macrostructural changes at baseline, whereas those with mild cognitive impairment showed fewer baseline changes. At follow-up, Parkinson's with low visual function showed widespread macrostructural changes, involving the fronto-occipital fasciculi, external capsules, and middle cerebellar peduncles bilaterally. No longitudinal change was seen in those with mild cognitive impairment at baseline or converters, even when the 2 groups were combined.

CONCLUSION

Parkinson's patients with poor visual function show increased white matter damage over time, providing further evidence for visual function as a marker of imminent cognitive decline. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Volumetric white matter tract segmentation with nested self-supervised learning using sequential pretext tasks

White matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI) provides an important tool for the analysis of brain development, function, and disease. Deep learning based methods of WM tract segmentation have been proposed, which greatly improve the accuracy of the segmentation. However, the training of the deep networks usually requires a large number of manual delineations of WM tracts, which can be especially difficult to obtain and unavailable in many scenarios. Therefore, in this work, we explore how to perform deep learning based WM tract segmentation when annotated training data is scarce. To this end, we seek to exploit the abundant unannotated dMRI data in the self-supervised learning framework. From the unannotated data, knowledge about image context can be learned with pretext tasks that do not require manual annotations. Specifically, a deep network can be pretrained for the pretext task, and the knowledge learned from the pretext task is then transferred to the subsequent WM tract segmentation task with only a small number of annotated scans via fine-tuning. We explore two designs of pretext tasks that are related to WM tracts. The first pretext task predicts the density map of fiber streamlines, which are representations of generic WM pathways, and the training data can be obtained automatically with tractography. The second pretext task learns to mimic the results of registration-based WM tract segmentation, which, although inaccurate, is more relevant to WM tract segmentation and provides a good target for learning context knowledge. Then, we combine the two pretext tasks and develop a nested self-supervised learning strategy. In the nested self-supervised learning strategy, the first pretext task provides initial knowledge for the second pretext task, and the knowledge learned from the second pretext task with the initial knowledge is transferred to the target WM tract segmentation task via fine-tuning. To evaluate the proposed method, experiments were performed on brain dMRI scans from the Human Connectome Project dataset with various experimental settings. The results show that the proposed method improves the performance of WM tract segmentation when tract annotations are scarce.

Sequence of clinical and neurodegeneration events in Parkinson's disease progression

Dementia is one of the most debilitating aspects of Parkinson's disease. There are no validated biomarkers that can track Parkinson's disease progression, nor accurately identify patients who will develop dementia and when. Understanding the sequence of observable changes in Parkinson's disease in people at elevated risk for developing dementia could provide an integrated biomarker for identifying and managing individuals who will develop Parkinson's dementia. We aimed to estimate the sequence of clinical and neurodegeneration events, and variability in this sequence, using data-driven statistical modelling in two separate Parkinson's cohorts, focusing on patients at elevated risk for dementia due to their age at symptom onset. We updated a novel version of an event-based model that has only recently been extended to cope naturally with clinical data, enabling its application in Parkinson's disease for the first time. The observational cohorts included healthy control subjects and patients with Parkinson's disease, of whom those diagnosed at age 65 or older were classified as having high risk of dementia. The model estimates that Parkinson's progression in patients at elevated risk for dementia starts with classic prodromal features of Parkinson's disease (olfaction, sleep), followed by early deficits in visual cognition and increased brain iron content, followed later by a less certain ordering of neurodegeneration in the substantia nigra and cortex, neuropsychological cognitive deficits, retinal thinning in dopamine layers, and further deficits in visual cognition. Importantly, we also characterize variation in the sequence. We found consistent, cross-validated results within cohorts, and agreement between cohorts on the subset of features available in both cohorts. Our sequencing results add powerful support to the increasing body of evidence suggesting that visual processing specifically is affected early in patients with Parkinson's disease at elevated risk of dementia. This opens a route to earlier and more precise detection, as well as a more detailed understanding of the pathological mechanisms underpinning Parkinson's dementia.

White matter abnormalities of right hemisphere attention networks contribute to visual hallucinations in dementia with Lewy bodies

OBJECTIVE

Functional alterations of the visual attention networks in a setting of impaired visual information processing have a role in the genesis of visual hallucinations (VH) in dementia with Lewy bodies (DLB). This multimodal MRI study aims at exploring structural and functional basis of VH.

METHODS

23 DLB patients (10 with and 13 without VH) and 13 healthy controls were studied. They underwent MRI with T1-w sequences to measure cortical thickness, DTI for whole-brain and single tract microstructural properties and rs-fMRI of the default mode, dorsal and ventral attention, and visual networks.

RESULTS

In DLB with VH, whole-brain DTI revealed a lower fractional anisotropy and a greater mean diffusivity in the right frontal and temporo-parietal white matter tracts. Tracts dissection showed lower fractional anisotropy in the right inferior and superior (ventral part) longitudinal fasciculi (ILF and SLF) (p < .05, corrected), and greater mean diffusivity (p < .05). The extent of white matter microstructural alterations involving the right ILF and SLF correlated with the severity of VH (r = .55, p < .01; r = .42, p < .05, respectively), and with performance in the visual attention task (r = -.56 and r = -.61; p < .01, respectively). Cortical thickness in the projection areas of the right SLF was significantly reduced (p < .05). Patients with VH also showed an altered functional connectivity in the ventral attention network, connected by the ventral portion of the SLF (p < .05).

CONCLUSIONS

Our findings suggest that a combination of microstructural and functional alterations involving the attention networks in the right hemisphere may be important in the genesis of VH.

Organisational and neuromodulatory underpinnings of structural-functional connectivity decoupling in patients with Parkinson's disease

Parkinson's dementia is characterised by changes in perception and thought, and preceded by visual dysfunction, making this a useful surrogate for dementia risk. Structural and functional connectivity changes are seen in humans with Parkinson's disease, but the organisational principles are not known. We used resting-state fMRI and diffusion-weighted imaging to examine changes in structural-functional connectivity coupling in patients with Parkinson's disease, and those at risk of dementia. We identified two organisational gradients to structural-functional connectivity decoupling: anterior-to-posterior and unimodal-to-transmodal, with stronger structural-functional connectivity coupling in anterior, unimodal areas and weakened towards posterior, transmodal regions. Next, we related spatial patterns of decoupling to expression of neurotransmitter receptors. We found that dopaminergic and serotonergic transmission relates to decoupling in Parkinson's overall, but instead, serotonergic, cholinergic and noradrenergic transmission relates to decoupling in patients with visual dysfunction. Our findings provide a framework to explain the specific disorders of consciousness in Parkinson's dementia, and the neurotransmitter systems that underlie these.

Differences in network controllability and regional gene expression underlie hallucinations in Parkinson's disease

Visual hallucinations are common in Parkinson's disease and are associated with poorer prognosis. Imaging studies show white matter loss and functional connectivity changes with Parkinson's visual hallucinations, but the biological factors underlying selective vulnerability of affected parts of the brain network are unknown. Recent models for Parkinson's disease hallucinations suggest they arise due to a shift in the relative effects of different networks. Understanding how structural connectivity affects the interplay between networks will provide important mechanistic insights. To address this, we investigated the structural connectivity changes that accompany visual hallucinations in Parkinson's disease and the organizational and gene expression characteristics of the preferentially affected areas of the network. We performed diffusion-weighted imaging in 100 patients with Parkinson's disease (81 without hallucinations, 19 with visual hallucinations) and 34 healthy age-matched controls. We used network-based statistics to identify changes in structural connectivity in Parkinson's disease patients with hallucinations and performed an analysis of controllability, an emerging technique that allows quantification of the influence a brain region has across the rest of the network. Using these techniques, we identified a subnetwork of reduced connectivity in Parkinson's disease hallucinations. We then used the Allen Institute for Brain Sciences human transcriptome atlas to identify regional gene expression patterns associated with affected areas of the network. Within this network, Parkinson's disease patients with hallucinations showed reduced controllability (less influence over other brain regions), than Parkinson's disease patients without hallucinations and controls. This subnetwork appears to be critical for overall brain integration, as even in controls, nodes with high controllability were more likely to be within the subnetwork. Gene expression analysis of gene modules related to the affected subnetwork revealed that down-weighted genes were most significantly enriched in genes related to mRNA and chromosome metabolic processes (with enrichment in oligodendrocytes) and upweighted genes to protein localization (with enrichment in neuronal cells). Our findings provide insights into how hallucinations are generated, with breakdown of a key structural subnetwork that exerts control across distributed brain regions. Expression of genes related to mRNA metabolism and membrane localization may be implicated, providing potential therapeutic targets.

Visual hallucinations and inferior longitudinal fasciculus in Parkinson's disease

INTRODUCTION

We investigated whether disruption of the inferior longitudinal fasciculus and inferior fronto-occipital fasciculus are associated with visual hallucinations in Parkinson's disease (PD).

METHODS

Sixty consecutive right-handed patients with PD with and without visual hallucinations were enrolled in this cross-sectional study. Diffusion tensor imaging was acquired by 3.0 T magnetic resonance imaging. We measured fractional anisotropy and mean diffusivity of the bilateral inferior longitudinal fasciculus and inferior fronto-occipital fasciculus using diffusion tensor tractography analysis software.

RESULTS

Seventeen patients with PD had visual hallucinations; these patients tended to have lower fractional anisotropy and higher mean diffusivity values in all fasciculi than did patients without visual hallucinations. A univariate logistic analysis showed that the presence of visual hallucinations was significantly associated with lower fractional anisotropy and higher mean diffusivity of the left inferior longitudinal fasciculus, and lower Mini-Mental State Examination (MMSE) scores. A multivariable logistic analysis adjusted by MMSE scores and disease duration showed a significant association between the presence of visual hallucinations and fractional anisotropy and mean diffusivity values of the left inferior longitudinal fasciculus.

CONCLUSIONS

Our results suggest that disruption of left inferior longitudinal fasciculus integrity is associated with visual hallucinations in patients with PD, independent of cognitive impairment and disease duration.

Dementia risk in Parkinson's disease is associated with interhemispheric connectivity loss and determined by regional gene expression

Parkinson's dementia is a common and devastating part of Parkinson's disease. Whilst timing and severity vary, dementia in Parkinson's is often preceded by visual dysfunction. White matter changes, representing axonal loss, occur early in the disease process. Clarifying which white matter connections are affected in Parkinson's with visual dysfunction and why specific connections are vulnerable will provide important mechanistic insights. Here, we use diffusion tractography in 100 Parkinson's patients (33 low visual performers) and 34 controls to identify patterns of connectivity loss in Parkinson's with visual dysfunction. We examine the relationship between regional transcription and connectivity loss, using the Allen Institute for Brain Science transcriptome atlas. We show that interhemispheric connections are preferentially affected in Parkinson's low visual performers. Interhemispheric connection loss was associated with downweighted genes related to the smoothened signalling pathway (enriched in glutamatergic neurons) and upweighted metabolic genes. Risk genes for Parkinson's but not Alzheimer's or Dementia with Lewy bodies were over-represented in upweighted genes associated with interhemispheric connection loss. Our findings suggest selective vulnerability in Parkinson's patients at highest risk of dementia (those with visual dysfunction), where differences in gene expression and metabolic dysfunction, affecting longer connections with higher metabolic burden, drive connectivity loss.

Hallucinations in Parkinson's disease: new insights into mechanisms and treatments

Hallucinations are common in Parkinson's disease and can be distressing to patients and their families. They are associated with higher rates of nursing home placement and with increased mortality. Their underlying mechanisms have been elusive, but recent advances in network imaging provides some intriguing insights into possible underlying drivers. Treatment is complicated by risk of worsening Parkinson's motor symptoms and by higher rates of mortality with antipsychotics, but new therapeutic avenues are emerging that offer potential hope.