fMRI resting state networks and their association with cognitive fluctuations in dementia with Lewy bodies

Understanding REM Sleep Behavior Disorder through Functional MRI: A Systematic Review

Neuroimaging studies in rapid eye movement sleep behavior disorder (RBD) can inform fundamental questions about the pathogenesis of Parkinson's disease (PD). Across modalities, functional magnetic resonance imaging (fMRI) may be better suited to identify changes between neural networks in the earliest stages of Lewy body diseases when structural changes may be subtle or absent. This review synthesizes the findings from all fMRI studies of RBD to gain further insight into the pathophysiology and progression of Lewy body diseases. A total of 32 studies were identified using a systematic review conducted according to PRISMA guidelines between January 2000 to February 2024 for original fMRI studies in patients with either isolated RBD (iRBD) or RBD secondary to PD. Common functional alterations were detectable in iRBD patients compared with healthy controls across brainstem nuclei, basal ganglia, frontal and occipital lobes, and whole brain network measures. Patients with established PD and RBD demonstrated decreased functional connectivity across the whole brain and brainstem nuclei, but increased functional connectivity in the cerebellum and frontal lobe compared with those PD patients without RBD. Finally, longitudinal changes in resting state functional connectivity were found to track with disease progression. Currently, fMRI studies in RBD have demonstrated early signatures of neurodegeneration across both motor and non-motor pathways. Although more work is needed, such findings have the potential to inform our understanding of disease, help to distinguish between prodromal PD and prodromal dementia with Lewy bodies, and support the development of fMRI-based outcome measures of phenoconversion and progression in future disease modifying trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission

PURPOSE

Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA).

METHODS

FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level.

RESULTS

Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912).

CONCLUSION

Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.

A systematic literature review of fMRI and EEG resting-state functional connectivity in Dementia with Lewy Bodies: Underlying mechanisms, clinical manifestation, and methodological considerations

Previous studies suggest that there may be important links between functional connectivity, disease mechanisms underpinning the Dementia with Lewy Body (DLB) and the key clinical symptoms, but the exact relationship remains unclear. We performed a systematic literature review to address this gap by summarising the research findings while critically considering the impact of methodological differences on findings. The main methodological choices of fMRI articles included data-driven, seed-based or regions of interest approaches, or their combinations. Most studies focused on examining large-scale resting-state networks, which revealed a consistent decrease in connectivity and some associations with non-cognitive symptoms. Although the inter-network connectivity showed mixed results, the main finding is consistent with theories positing disconnection between visual and attentional areas of the brain implicated in the aetiology of psychotic symptoms in the DLB. The primary methodological choice of EEG studies was implementing the phase lag index and using graph theory. The EEG studies revealed a consistent decrease in connectivity on alpha and beta frequency bands. While the overall trend of findings showed decreased connectivity, more subtle changes in the directionality of connectivity were observed when using a hypothesis-driven approach. Problems with cognition were also linked with greater functional connectivity disturbances. In summary, connectivity measures can capture brain disturbances in the DLB and remain crucial in uncovering the causal relationship between the networks' disorganisation and underlying mechanisms resulting in psychotic, motor, and cognitive symptoms of the DLB.

Mild cognitive impairment in dementia with Lewy bodies: an update and outlook

Dementia with Lewy bodies (DLB), the second most common degenerative neurocognitive disorder after Alzheimer disease (AD), is frequently preceded by a period of mild cognitive impairment (MCI), in which cognitive decline is associated with impairment of executive functions/attention, visuospatial deficits, or other cognitive domains and a variety of noncognitive and neuropsychiatric symptoms, many of which are similar but less severe than in prodromal AD. While 36-38% remain in the MCI state, at least the same will convert to dementia. Biomarkers are slowing of the EEG rhythms, atrophy of hippocampus and nucleus basalis of Meynert, temporoparietal hypoperfusion, signs of degeneration of the nigrostriatal dopaminergic, cholinergic and other neurotransmitter systems, and inflammation. Functional neuroimaging studies revealed disturbed connectivity of frontal and limbic networks associated with attention and cognitive controls, dopaminergic and cholinergic circuits manifested prior to overt brain atrophy. Sparse neuropathological data showed varying Lewy body and AD-related stages associated with atrophy of entorhinal, hippocampal, and mediotemporal cortices. Putative pathomechanisms of MCI are degeneration of limbic, dopaminergic, and cholinergic systems with Lewy pathology affecting specific neuroanatomical pathways associated with progressing AD-related lesions, but many pathobiological mechanisms involved in the development of MCI in LBD remain to be elucidated as a basis for early diagnosis and future adequate treatment modalities to prevent progression of this debilitating disorder.

Characterizing the spatiotemporal features of functional connectivity across the white matter and gray matter during the naturalistic condition

Introduction

The naturalistic stimuli due to its ease of operability has attracted many researchers in recent years. However, the influence of the naturalistic stimuli for whole-brain functions compared with the resting state is still unclear.

Methods

In this study, we clustered gray matter (GM) and white matter (WM) masks both at the ROI- and network-levels. Functional connectivity (FC) and inter-subject functional connectivity (ISFC) were calculated in GM, WM, and between GM and WM under the movie-watching and the resting-state conditions. Furthermore, intra-class correlation coefficients (ICC) of FC and ISFC were estimated on different runs of fMRI data to denote the reliability of them during the two conditions. In addition, static and dynamic connectivity indices were calculated with Pearson correlation coefficient to demonstrate the associations between the movie-watching and the resting-state.

Results

As the results, we found that the movie-watching significantly affected FC in whole-brain compared with the resting-state, but ISFC did not show significant connectivity induced by the naturalistic condition. ICC of FC and ISFC was generally higher during movie-watching compared with the resting-state, demonstrating that naturalistic stimuli could promote the reliability of connectivity. The associations between static and dynamic ISFC were weakly negative correlations in the naturalistic stimuli while there is no correlation between them under resting-state condition.

Discussion

Our findings confirmed that compared to resting-state condition, the connectivity indices under the naturalistic stimuli were more reliable and stable to investigate the normal functional activities of the human brain, and might promote the applications of FC in the cerebral dysfunction in various mental disorders.

The use of neuroimaging techniques in the early and differential diagnosis of dementia

Dementia is a leading cause of disability and death worldwide. At present there is no disease modifying treatment for any of the most common types of dementia such as Alzheimer's disease (AD), Vascular dementia, Lewy Body Dementia (LBD) and Frontotemporal dementia (FTD). Early and accurate diagnosis of dementia subtype is critical to improving clinical care and developing better treatments. Structural and molecular imaging has contributed to a better understanding of the pathophysiology of neurodegenerative dementias and is increasingly being adopted into clinical practice for early and accurate diagnosis. In this review we summarise the contribution imaging has made with particular focus on multimodal magnetic resonance imaging (MRI) and positron emission tomography imaging (PET). Structural MRI is widely used in clinical practice and can help exclude reversible causes of memory problems but has relatively low sensitivity for the early and differential diagnosis of dementia subtypes. 18F-fluorodeoxyglucose PET has high sensitivity and specificity for AD and FTD, while PET with ligands for amyloid and tau can improve the differential diagnosis of AD and non-AD dementias, including recognition at prodromal stages. Dopaminergic imaging can assist with the diagnosis of LBD. The lack of a validated tracer for α-synuclein or TAR DNA-binding protein 43 (TDP-43) imaging remain notable gaps, though work is ongoing. Emerging PET tracers such as 11C-UCB-J for synaptic imaging may be sensitive early markers but overall larger longitudinal multi-centre cross diagnostic imaging studies are needed.

Resting state EEG rhythms in different stages of chronic kidney disease with mild cognitive impairment

Here, we tested that standard eyes-closed resting-state electroencephalographic (rsEEG) rhythms may characterize patients with mild cognitive impairment due to chronic kidney disease at stages 3-4 (CKDMCI-3&4) in relation to CKDMCI patients under hemodialysis (CKDMCI-H) and mild cognitive impairment (MCI) patients with cerebrovascular disease (CVMCI). Clinical and rsEEG data in 22 CKDMCI-3&4, 15 CKDMCI-H, 18 CVMCI, and 30 matched healthy control (HC) participants were available in a national archive. Spectral rsEEG power density was calculated from delta to gamma frequency bands at scalp electrodes. Results showed that (1) all MCI groups over the HC group showed decreased occipital rsEEG alpha power density; (2) compared to the HC and CVMCI groups, the 2 CKDMCI groups had higher rsEEG delta-theta power density; and (3) the CKDMCI-3&4 group showed the lowest parietal rsEEG alpha power density. The present rsEEG measures may be useful to monitor the impact of circulating uremic toxins on brain regulation of cortical arousal for quiet vigilance in CKDMCI patients.

Subject-specific whole-brain parcellations of nodes and boundaries are modulated differently under 10 Hz rTMS

Repetitive transcranial magnetic stimulation (rTMS) has gained considerable importance in the treatment of neuropsychiatric disorders, including major depression. However, it is not yet understood how rTMS alters brain's functional connectivity. Here we report changes in functional connectivity captured by resting state functional magnetic resonance imaging (rsfMRI) within the first hour after 10 Hz rTMS. We apply subject-specific parcellation schemes to detect changes (1) in network nodes, where the strongest functional connectivity of regions is observed, and (2) in network boundaries, where functional transitions between regions occur. We use support vector machine (SVM), a widely used machine learning algorithm that is robust and effective, for the classification and characterization of time intervals of changes in node and boundary maps. Our results reveal that changes in connectivity at the boundaries are slower and more complex than in those observed in the nodes, but of similar magnitude according to accuracy confidence intervals. These results were strongest in the posterior cingulate cortex and precuneus. As network boundaries are indeed under-investigated in comparison to nodes in connectomics research, our results highlight their contribution to functional adjustments to rTMS.

Longitudinal evolution of cortical thickness signature reflecting Lewy body dementia in isolated REM sleep behavior disorder: a prospective cohort study

BACKGROUND

The isolated rapid-eye-movement sleep behavior disorder (iRBD) is a prodromal condition of Lewy body disease including Parkinson's disease and dementia with Lewy bodies (DLB). We aim to investigate the longitudinal evolution of DLB-related cortical thickness signature in a prospective iRBD cohort and evaluate the possible predictive value of the cortical signature index in predicting dementia-first phenoconversion in individuals with iRBD.

METHODS

We enrolled 22 DLB patients, 44 healthy controls, and 50 video polysomnography-proven iRBD patients. Participants underwent 3-T magnetic resonance imaging (MRI) and clinical/neuropsychological evaluations. We characterized DLB-related whole-brain cortical thickness spatial covariance pattern (DLB-pattern) using scaled subprofile model of principal components analysis that best differentiated DLB patients from age-matched controls. We analyzed clinical and neuropsychological correlates of the DLB-pattern expression scores and the mean values of the whole-brain cortical thickness in DLB and iRBD patients. With repeated MRI data during the follow-up in our prospective iRBD cohort, we investigated the longitudinal evolution of the cortical thickness signature toward Lewy body dementia. Finally, we analyzed the potential predictive value of cortical thickness signature as a biomarker of phenoconversion in iRBD cohort.

RESULTS

The DLB-pattern was characterized by thinning of the temporal, orbitofrontal, and insular cortices and relative preservation of the precentral and inferior parietal cortices. The DLB-pattern expression scores correlated with attentional and frontal executive dysfunction (Trail Making Test-A and B: R = - 0.55, P = 0.024 and R = - 0.56, P = 0.036, respectively) as well as visuospatial impairment (Rey-figure copy test: R = - 0.54, P = 0.0047). The longitudinal trajectory of DLB-pattern revealed an increasing pattern above the cut-off in the dementia-first phenoconverters (Pearson's correlation, R = 0.74, P = 6.8 × 10^-4) but no significant change in parkinsonism-first phenoconverters (R = 0.0063, P = 0.98). The mean value of the whole-brain cortical thickness predicted phenoconversion in iRBD patients with hazard ratio of 9.33 [1.16-74.12]. The increase in DLB-pattern expression score discriminated dementia-first from parkinsonism-first phenoconversions with 88.2% accuracy.

CONCLUSION

Cortical thickness signature can effectively reflect the longitudinal evolution of Lewy body dementia in the iRBD population. Replication studies would further validate the utility of this imaging marker in iRBD.

Sex differences in brain metabolic connectivity architecture in probable dementia with Lewy bodies

We investigated how sex modulates metabolic connectivity alterations in probable dementia with Lewy bodies (pDLB). We included 131 pDLB patients (males/females: 58/73) and similarly aged healthy controls (HC) (male/female: 59/75) with available (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans. We assessed (1) sex differences in the whole-brain connectivity, identifying pathological hubs, (2) connectivity alterations in functional pathways of the neurotransmitter systems, (3) Resting State Networks (RSNs) integrity. Both pDLB_M (males) and pDLB_F (females) shared dysfunctional hubs in the insula, Rolandic operculum, and inferior parietal lobule, but the pDLB_M group showed more severe and diffuse whole-brain connectivity alterations. Neurotransmitters connectivity analysis revealed common alterations in dopaminergic and noradrenergic pathways. Sex differences emerged particularly in the Ch4-perisylvian division, with pDLB_M showing more severe alterations than pDLB_F. The RSNs analysis showed no sex differences, with decreased connectivity strength in the primary visual, posterior default mode, and attention networks in both groups. Extensive connectivity changes characterize both males and females in the dementia stage, with a major vulnerability of cholinergic neurotransmitter systems in males, possibly contributing to the observed different clinical phenotypes.

Brain Degeneration in Synucleinopathies Based on Analysis of Cognition and Other Nonmotor Features: A Multimodal Imaging Study

BACKGROUND

We aimed to characterize subtypes of synucleinopathies using a clustering approach based on cognitive and other nonmotor data and to explore structural and functional magnetic resonance imaging (MRI) brain differences between identified clusters.

METHODS

Sixty-two patients (n = 6 E46K-SNCA, n = 8 dementia with Lewy bodies (DLB) and n = 48 idiopathic Parkinson's disease (PD)) and 37 normal controls underwent nonmotor evaluation with extensive cognitive assessment. Hierarchical cluster analysis (HCA) was performed on patients' samples based on nonmotor variables. T1, diffusion-weighted, and resting-state functional MRI data were acquired. Whole-brain comparisons were performed.

RESULTS

HCA revealed two subtypes, the mild subtype (n = 29) and the severe subtype (n = 33). The mild subtype patients were slightly impaired in some nonmotor domains (fatigue, depression, olfaction, and orthostatic hypotension) with no detectable cognitive impairment; the severe subtype patients (PD patients, all DLB, and the symptomatic E46K-SNCA carriers) were severely impaired in motor and nonmotor domains with marked cognitive, visual and bradykinesia alterations. Multimodal MRI analyses suggested that the severe subtype exhibits widespread brain alterations in both structure and function, whereas the mild subtype shows relatively mild disruptions in occipital brain structure and function.

CONCLUSIONS

These findings support the potential value of incorporating an extensive nonmotor evaluation to characterize specific clinical patterns and brain degeneration patterns of synucleinopathies.

Sex differences in grey matter networks in dementia with Lewy bodies

Objectives

Sex differences permeate many aspects of dementia with Lewy bodies (DLB), including epidemiology, pathogenesis, disease progression, and symptom manifestation. However, less is known about potential sex differences in patterns of neurodegeneration in DLB. Here, we test whether grey matter networks also differ between female and male DLB patients. To assess the specificity of these sex differences to DLB, we additionally investigate sex differences in healthy controls (HCs).

Methods

A total of 119 (68.7 ± 8.4 years) male and 45 female (69.9 ± 9.1 years) DLB patients from three European centres and the Mayo Clinic were included in this study. Additionally, we included 119 male and 45 female age-matched HCs from the Mayo Clinic. Grey matter volumes of 58 cortical, subcortical, cerebellar, and pontine brain regions derived from structural magnetic resonance images were corrected for age, intracranial volume, and centre. Sex-specific grey matter networks for DLB patients and HCs were constructed by correlating each pair of brain regions. Network properties of the correlation matrices were compared between sexes and groups. Additional analyses were conducted on W-scored data to identify DLB-specific findings.

Results

Networks of male HCs and male DLB patients were characterised by a lower nodal strength compared to their respective female counterparts. In comparison to female HCs, the grey matter networks of male HCs showed a higher global efficiency, modularity, and a lower number of modules. None of the global and nodal network measures showed significant sex differences in DLB.

Conclusions

The disappearance of sex differences in the structural grey matter networks of DLB patients compared to HCs may indicate a sex-dependent network vulnerability to the alpha-synuclein pathology in DLB. Future studies might investigate whether the differences in structural network measures are associated with differences in cognitive scores and clinical symptoms between the sexes.

MRI data-driven clustering reveals different subtypes of Dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is a neurodegenerative disorder with a wide heterogeneity of symptoms, which suggests the existence of different subtypes. We used data-driven analysis of magnetic resonance imaging (MRI) data to investigate DLB subtypes. We included 165 DLB from the Mayo Clinic and 3 centers from the European DLB consortium and performed a hierarchical cluster analysis to identify subtypes based on gray matter (GM) volumes. To characterize the subtypes, we used demographic and clinical data, as well as β-amyloid, tau, and cerebrovascular biomarkers at baseline, and cognitive decline over three years. We identified 3 subtypes: an older subtype with reduced cortical GM volumes, worse cognition, and faster cognitive decline (n = 49, 30%); a subtype with low GM volumes in fronto-occipital regions (n = 76, 46%); and a subtype of younger patients with the highest cortical GM volumes, proportionally lower GM volumes in basal ganglia and the highest frequency of cognitive fluctuations (n = 40, 24%). This study shows the existence of MRI subtypes in DLB, which may have implications for clinical workout, research, and therapeutic decisions.

(Dis-)Connected Dots in Dementia with Lewy Bodies-A Systematic Review of Connectivity Studies

Studies on dementia with Lewy bodies (DLB) have mainly focused on the degeneration of distinct cortical and subcortical regions related to the deposition of Lewy bodies. In view of the proposed trans-synaptic spread of the α-synuclein pathology, investigating the disease only in this segregated fashion would be detrimental to our understanding of its progression. In this systematic review, we summarize findings on structural and functional brain connectivity in DLB, as connectivity measures may offer better insights on how the brain is affected by the spread of the pathology. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Web of Science, PubMed, and SCOPUS for relevant articles published up to November 1, 2021. Of 1215 identified records, we selected and systematically reviewed 53 articles that compared connectivity features between patients with DLB and healthy controls. Structural and functional magnetic resonance imaging, positron emission tomography, single-positron emission computer tomography, and electroencephalography assessments of patients revealed widespread abnormalities within and across brain networks in DLB. Frontoparietal, default mode, and visual networks and their connections to other brain regions featured the most consistent disruptions, which were also associated with core clinical features and cognitive impairments. Furthermore, graph theoretical measures revealed disease-related decreases in local and global network efficiency. This systematic review shows that structural and functional connectivity characteristics in DLB may be particularly valuable at early stages, before overt brain atrophy can be observed. This knowledge may help improve the diagnosis and prognosis in DLB as well as pinpoint targets for future disease-modifying treatments. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Alzheimer's Disease with Epileptiform EEG Activity: Abnormal Cortical Sources of Resting State Delta Rhythms in Patients with Amnesic Mild Cognitive Impairment

BACKGROUND

Patients with amnesic mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show a "slowing" of cortical resting-state eyes-closed electroencephalographic (rsEEG) rhythms. Some of them also show subclinical, non-convulsive, and epileptiform EEG activity (EEA) with an unclear relationship with that "slowing."

OBJECTIVE

Here we tested the hypothesis that the "slowing" of rsEEG rhythms is related to EEA in ADMCI patients.

METHODS

Clinical and instrumental datasets in 62 ADMCI patients and 38 normal elderly (Nold) subjects were available in a national archive. No participant had received a clinical diagnosis of epilepsy. The eLORETA freeware estimated rsEEG cortical sources. The area under the receiver operating characteristic curve (AUROCC) indexed the accuracy of eLORETA solutions in the classification between ADMCI-EEA and ADMCI-noEEA individuals.

RESULTS

EEA was observed in 15% (N = 8) of the ADMCI patients. The ADMCI-EEA group showed: 1) more abnormal Aβ 42 levels in the cerebrospinal fluid as compared to the ADMCI-noEEA group and 2) higher temporal and occipital delta (<4 Hz) rsEEG source activities as compared to the ADMCI-noEEA and Nold groups. Those source activities showed moderate accuracy (AUROCC = 0.70-0.75) in the discrimination between ADMCI-noEEA versus ADMCI-EEA individuals.

CONCLUSION

It can be speculated that in ADMCI-EEA patients, AD-related amyloid neuropathology may be related to an over-excitation in neurophysiological low-frequency (delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance.

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.

Fluid markers of synapse degeneration in synucleinopathies

The abnormal accumulation of α-synuclein in the brain is a common feature of Parkinson's disease (PD), PD dementia (PDD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA), and synucleinopathies that present with overlapping but distinct clinical symptoms that include motor and cognitive deficits. Synapse degeneration is the crucial neuropathological event in these synucleinopathies and the neuropathological correlate of connectome dysfunction. The cognitive and motor deficits resulting from the connectome dysfunction are currently measured by scalar systems that are limited in their sensitivity and largely subjective. Ideally, a marker of synapse degeneration would correlate with measures of cognitive or motor impairment, and could therefore be used as a more objective, surrogate biomarker of the core clinical features of these diseases. Furthermore, an objective surrogate biomarker that can detect and monitor the progression of synapse degeneration would improve patient management and clinical trial design, and could provide a measure of therapeutic response. Here, we review the published findings relating to candidate biomarkers of synapse degeneration in PD, PDD, DLB, and MSA patient-derived biofluids and discuss the findings in the context of the mechanisms associated with α-synuclein-mediated synapse degeneration. Understanding these mechanisms is essential not only for discovery of biomarkers, but also to improve our understanding of the earliest changes in disease pathogenesis of synucleinopathies.

Visual hallucinations in Lewy body disease: pathophysiological insights from phenomenology

Visual hallucinations (VH) in Lewy body disease (LBD) have a heterogenous phenomenology classified into minor phenomena (MVH) and complex hallucinations (CVH). Mechanisms underpinning VH and their temporal aspects are largely unknown. According to the hodotopic model, we investigated whether changes in distinct cognitive domains and neural networks in the hallucination trait underpin temporal aspects of MVH and CVH in the hallucination state. 35 LBD patients with VH underwent a complete neuropsychological evaluation and resting-state fMRI. North-East-Visual-Hallucinations-Interview was used to assess their typical VH content, duration, and frequency. We found that MVH was not associated with cognitive impairment, while CVH was associated with impairments in visuoperceptual processes, attention and visual abstract reasoning. In seed-to-seed functional connectivity (FC) analysis we identified functional couplings associated with MVH and CVH temporal severity (duration x frequency), duration and frequency. MVH severity was negatively associated with FC between early visual areas (EVA) and ventral-visual-stream regions, and negatively associated with FC between brainstem and EVA, which may be linked to LBD brainstem neuropathology. CVH duration was positively associated with FC between ventral-visual stream and salience network (SN). CVH frequency was negatively associated with FC between DMN and SN. Functional alterations in distinct visual and attentional networks and their dynamic interaction in trait LBD hallucinators are linked to both the phenomenology of state content and its temporal characteristics. Within a network, VH frequency and duration may be linked to different types of functional alterations: increased connectivity leading to sustained activity prolonging VH (duration) and decreased connectivity increasing dysregulated, spontaneous activity (frequency). These findings support the hodotopic hypothesis of VH and may reflect a link between VH phenomenology, LBD neuropathological progression and the involvement of specific neurotransmitter systems.

Reorganization of rich clubs in functional brain networks of dementia with Lewy bodies and Alzheimer's disease

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DLB and AD had the different functional reorganization patterns.

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Rich club nodes increased in frontal-parietal network in patients with DLB.

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The rich club nodes in temporal lobe decreased and those in cerebellum increased for AD.

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Compared with HC, rich club connectivity was enhanced in the DLB and AD groups.

The purpose of this study was to reveal the patterns of reorganization of rich club organization in brain functional networks in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). The study found that the rich club node shifts from sensory/somatomotor network to fronto-parietal network in DLB. For AD, the rich club nodes switch between the temporal lobe with obvious structural atrophy and the frontal lobe, parietal lobe and cerebellum with relatively preserved structure and function. In addition, compared with healthy controls, rich club connectivity was enhanced in the DLB and AD groups. The connection strength of DLB patients was related to cognitive assessment. In conclusion, we revealed the different functional reorganization patterns of DLB and AD. The conversion and redistribution of rich club members may play a causal role in disease-specific outcomes. It may be used as a potential biomarker to provide more accurate prevention and treatment strategies.

Neuroimaging alterations in dementia with Lewy bodies and neuroimaging differences between dementia with Lewy bodies and Alzheimer's disease: An activation likelihood estimation meta-analysis

Aims

The aim of this study was to identify brain regions with local, structural, and functional abnormalities in dementia with Lewy bodies (DLB) and uncover the differences between DLB and Alzheimer's disease (AD). The neural networks involved in the identified abnormal brain regions were further described.

Methods

PubMed, Web of Science, OVID, Science Direct, and Cochrane Library databases were used to identify neuroimaging studies that included DLB versus healthy controls (HCs) or DLB versus AD. The coordinate‐based meta‐analysis and functional meta‐analytic connectivity modeling were performed using the activation likelihood estimation algorithm.

Results

Eleven structural studies and fourteen functional studies were included in this quantitative meta‐analysis. DLB patients showed a dysfunction in the bilateral inferior parietal lobule and right lingual gyrus compared with HC patients. DLB patients showed a relative preservation of the medial temporal lobe and a tendency of lower metabolism in the right lingual gyrus compared with AD. The frontal‐parietal, salience, and visual networks were all abnormally co‐activated in DLB, but the default mode network remained normally co‐activated compared with AD.

Conclusions

The convergence of local brain regions and co‐activation neural networks might be potential specific imaging markers in the diagnosis of DLB. This might provide a pathway for the neural regulation in DLB patients, and it might contribute to the development of specific interventions for DLB and AD.

Dementia with Lewy bodies: association of Alzheimer pathology with functional connectivity networks

Dementia with Lewy bodies (DLB) is neuropathologically defined by the presence of α-synuclein aggregates, but many DLB cases show concurrent Alzheimer's disease pathology in the form of amyloid-β plaques and tau neurofibrillary tangles. The first objective of this study was to investigate the effect of Alzheimer's disease co-pathology on functional network changes within the default mode network (DMN) in DLB. Second, we studied how the distribution of tau pathology measured with PET relates to functional connectivity in DLB. Twenty-seven DLB, 26 Alzheimer's disease and 99 cognitively unimpaired participants (balanced on age and sex to the DLB group) underwent tau-PET with AV-1451 (flortaucipir), amyloid-β-PET with Pittsburgh compound-B (PiB) and resting-state functional MRI scans. The resing-state functional MRI data were used to assess functional connectivity within the posterior DMN. This was then correlated with overall cortical flortaucipir PET and PiB PET standardized uptake value ratio (SUVr). The strength of interregional functional connectivity was assessed using the Schaefer atlas. Tau-PET covariance was measured as the correlation in flortaucipir SUVr between any two regions across participants. The association between region-to-region functional connectivity and tau-PET covariance was assessed using linear regression. Additionally, we identified the region with highest and the region with lowest tau SUVrs (tau hot- and cold spots) and tested whether tau SUVr in all other brain regions was associated with the strength of functional connectivity to these tau hot and cold spots. A reduction in posterior DMN connectivity correlated with overall higher cortical tau- (r = -0.39, P = 0.04) and amyloid-PET uptake (r = -0.41, P = 0.03) in the DLB group, i.e. patients with DLB who have more concurrent Alzheimer's disease pathology showed a more severe loss of DMN connectivity. Higher functional connectivity between regions was associated with higher tau covariance in cognitively unimpaired, Alzheimer's disease and DLB. Furthermore, higher functional connectivity of a target region to the tau hotspot (i.e. inferior/medial temporal cortex) was related to higher flortaucipir SUVrs in the target region, whereas higher functional connectivity to the tau cold spot (i.e. sensory-motor cortex) was related to lower flortaucipir SUVr in the target region. Our findings suggest that a higher burden of Alzheimer's disease co-pathology in patients with DLB is associated with more Alzheimer's disease-like changes in functional connectivity. Furthermore, we found an association between the brain's functional network architecture and the distribution of tau pathology that has recently been described in Alzheimer's disease. We show that this relationship also exists in patients with DLB, indicating that similar mechanisms of connectivity-dependent occurrence of tau pathology might be at work in both diseases.

Vector Auto-Regressive Deep Neural Network: A Data-Driven Deep Learning-Based Directed Functional Connectivity Estimation Toolbox

An important goal in neuroscience is to elucidate the causal relationships between the brain's different regions. This can help reveal the brain's functional circuitry and diagnose lesions. Currently there are a lack of approaches to functional connectome estimation that leverage the state-of-the-art in deep learning architectures and training methodologies. Therefore, we propose a new framework based on a vector auto-regressive deep neural network (VARDNN) architecture. Our approach consists of a set of nodes, each with a deep neural network structure. These nodes can be mapped to any spatial sub-division based on the data to be analyzed, such as anatomical brain regions from which representative neural signals can be obtained. VARDNN learns to reproduce experimental time series data using modern deep learning training techniques. Based on this, we developed two novel directed functional connectivity (dFC) measures, namely VARDNN-DI and VARDNN-GC. We evaluated our measures against a number of existing functional connectome estimation measures, such as partial correlation and multivariate Granger causality combined with large dimensionality counter-measure techniques. Our measures outperformed them across various types of ground truth data, especially as the number of nodes increased. We applied VARDNN to fMRI data to compare the dFC between 41 healthy control vs. 32 Alzheimer's disease subjects. Our VARDNN-DI measure detected lesioned regions consistent with previous studies and separated the two groups well in a subject-wise evaluation framework. Summarily, the VARDNN framework has powerful capabilities for whole brain dFC estimation. We have implemented VARDNN as an open-source toolbox that can be freely downloaded for researchers who wish to carry out functional connectome analysis on their own data.

Intrinsic Alertness Is Impaired in Patients with Nigrostriatal Degeneration: A Prospective Study with Reference to [123I]FP-CIT SPECT and [18F]FDG PET

BACKGROUND

Variations in alertness and attention are common in Lewy body diseases (LBD) and among the core features of dementia with Lewy bodies (DLB). Dopamine transporter SPECT is an accurate biomarker of nigrostriatal degeneration (NSD) in LBD.

OBJECTIVE

The present study investigated performance on a computerized alertness test as a potential measure of attention in patients with NSD compared to patients without NSD.

METHODS

Thirty-six patients with cognitive impairment plus at least one core feature of DLB referred for [123I]FP-CIT SPECT imaging were prospectively recruited. Performance in a computerized test of intrinsic alertness was compared between patients with and those without NSD as assessed by [123I]FP-CIT SPECT.

RESULTS

Reaction times to auditory stimuli (adjusted for age, sex, and education) were significantly longer in patients with NSD compared to those with a normal [123I]FP-CIT SPECT scan (p < 0.05). Statistical analyses revealed no significant differences comparing reaction times to visual stimuli or dispersion of reaction times between groups. Exploratory analysis in a subgroup of patients with available [18F]FDG PET revealed that longer reaction times were associated with decreased glucose metabolism in the prefrontal cortex (statistical parametric mapping, adjusted for age and sex; p < 0.005, cluster extent > 50 voxels).

CONCLUSION

Computerized assessment of auditory reaction times is able to detect alertness deficits in patients with NSD and might help to measure alertness deficits in patients with LBD and NSD. Future studies in larger samples are needed to evaluate the diagnostic utility of computerized alertness assessment for the differential diagnosis of LBD.

Specific occupational profiles as proxies of cognitive reserve induce neuroprotection in dementia with Lewy bodies

Cognitive reserve (CR) delays cognitive decline due to neurodegeneration. Heterogeneous evidence suggests that education may act as CR in Dementia with Lewy Bodies (DLB). No data, however, are currently available on the role of occupation as proxy of CR in this neuropathology. Thirty-three patients with probable DLB were retrospectively included. We performed regression analyses models (TFCE p < 0.05) and seed-based interregional correlation analyses (p = 0.001, FWE-corrected at cluster-level) with brain metabolism. We aimed at exploring the relationship between brain metabolic connectivity, as assessed by FDG-PET, in the relevant resting-state networks and CR proxies (education, 6-levels occupation, and the specific O*Net occupational profiles). Education modulates executive (ECN), attentive (ATTN) and posterior default mode (PDMN) networks in the highly educated DLB subjects, as shown by an increased metabolic connectivity, acting as a compensatory mechanism. High scores of the 6-levels occupation scale were associated with a decreased connectivity in the anterior default mode (ADMN) and high visual network (HVN), suggesting brain reserve mechanisms. As for the specific O*Net occupational profiles, these modulated ADMN, PDMN, ATTN, ECN, HVN and primary visual network (PVN) connectivity according to different neuroprotection mechanisms, namely neural reserve and compensation against neurodegeneration. This study highlights the relevance of life-long occupational activities at individual level in the neural expression of compensatory and neuroprotective mechanisms in DLB.

Evidence and implications of abnormal predictive coding in dementia

The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of ‘memory centres’ or ‘language centres’, or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding framework may therefore also inform future therapeutic strategies.

Lewy Body Dementias: A Coin with Two Sides?

Lewy body dementias (LBDs) consist of dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), which are clinically similar syndromes that share neuropathological findings with widespread cortical Lewy body deposition, often with a variable degree of concomitant Alzheimer pathology. The objective of this article is to provide an overview of the neuropathological and clinical features, current diagnostic criteria, biomarkers, and management of LBD. Literature research was performed using the PubMed database, and the most pertinent articles were read and are discussed in this paper. The diagnostic criteria for DLB have recently been updated, with the addition of indicative and supportive biomarker information. The time interval of dementia onset relative to parkinsonism remains the major distinction between DLB and PDD, underpinning controversy about whether they are the same illness in a different spectrum of the disease or two separate neurodegenerative disorders. The treatment for LBD is only symptomatic, but the expected progression and prognosis differ between the two entities. Diagnosis in prodromal stages should be of the utmost importance, because implementing early treatment might change the course of the illness if disease-modifying therapies are developed in the future. Thus, the identification of novel biomarkers constitutes an area of active research, with a special focus on α-synuclein markers.

Functional connectivity in mild cognitive impairment with Lewy bodies

Previous resting-state fMRI studies in dementia with Lewy bodies have described changes in functional connectivity in networks related to cognition, motor function, and attention as well as alterations in connectivity dynamics. However, whether these changes occur early in the course of the disease and are already evident at the stage of mild cognitive impairment is not clear. We studied resting-state fMRI data from 31 patients with mild cognitive impairment with Lewy bodies compared to 28 patients with mild cognitive impairment due to Alzheimer’s disease and 24 age-matched controls. We compared the groups with respect to within- and between-network functional connectivity. Additionally, we applied two different approaches to study dynamic functional connectivity (sliding-window analysis and leading eigenvector dynamic analysis). We did not find any significant changes in the mild cognitive impairment groups compared to controls and no differences between the two mild cognitive impairment groups, using static as well as dynamic connectivity measures. While patients with mild cognitive impairment with Lewy bodies already show clear functional abnormalities on EEG measures, the fMRI analyses presented here do not appear to be sensitive enough to detect such early and subtle changes in brain function in these patients.

Altered structural connectivity networks in dementia with lewy bodies

The impairment of large-scale brain networks has been observed in dementia with Lewy bodies (DLB) using functional connectivity, but the potential for an analogous effect on structural covariance patterns has not been determined. Twenty-four probable DLB subjects (mean age 74.3 ± 6.7 years, 16.7% female) and 23 similarly aged Controls were included. All participants underwent 3T MRI imaging with high-resolution T1-weighted magnetization-prepared rapid gradient echo (MPRAGE) sequence. Graph theoretical analyses were performed using variation in regional cortical thickness to construct a structural association matrix with pairwise Pearson correlations. Global and nodal graph parameters were computed to assess between-group differences and community structure was studied in order to quantify large-scale brain networks in both groups. In comparison to Controls, DLB subjects had decreased global efficiency, clustering, modularity and small-worldness of structural networks (all p < 0.05). Nodal measures showed that DLB subjects also had decreased clustering in bilateral temporal regions and decreased closeness centrality in extensive areas including right middle frontal, left cingulate and bilateral occipital lobe (all false-discovery rate (FDR)-corrected q < 0.05). Whereas four distinct modules could be clearly identified in Controls, DLB showed extensively disorganized modules, including default-mode network and dorsal attentional network. Our results suggest a marked impairment in large-scale brain structural networks in DLB, mirroring functional connectivity networks disruption.

Differentiating dementia with Lewy bodies from Alzheimer's disease and Parkinson's disease dementia: an update on imaging modalities

Dementia with Lewy bodies is the second most common cause of neurodegenerative dementia after Alzheimer's disease. Dementia with Lewy bodies can provide a diagnostic challenge due to the frequent overlap of clinical signs with other neurodegenerative conditions, namely Parkinson's disease dementia, and Alzheimer's disease. Part of this clinical overlap is due to the neuropathological overlap. Dementia with Lewy bodies is characterized by the accumulation of aggregated α-synuclein protein in Lewy bodies, similar to Parkinson's disease and Parkinson's disease dementia. However, it is also frequently accompanied by aggregation of amyloid-beta and tau, the pathological hallmarks of Alzheimer's disease. Neuroimaging is central to the diagnostic process. This review is an overview of both established and evolving imaging methods that can improve diagnostic accuracy and improve management of this disorder.

[Fluctuation of cognitive functions in dementia with Lewy bodies]

Fluctuations of cognitive function (FCF) is one of the core diagnostic features of dementia with Lewy bodies (DLB). However, identification, pathophysiology, management of this unusual phenomena remain poor understood. The review presents modern ideas about phenomenology, causes, systematization, clinical significance and current methods of diagnosis and treatment of FCF in patients with DLB.

Evaluating the Sustained Attention Response Task to Quantify Cognitive Fluctuations in Dementia With Lewy Bodies

Cognitive fluctuations (CFs) are a core diagnostic feature of dementia with Lewy bodies (DLB). Detection of CF is still mostly based on subjective reports from the patient or informant; more quantitative measures are likely to improve the accuracy for the diagnosis of DLB. The purpose of the current study is to test whether performance on the Sustained Attention Response Task (SART) could distinguish those patients with DLB with and without CF. Twenty-four patients with DLB were tested on the SART and performance was related to scores on the Clinical Assessment of Fluctuations (CAFs) and One Day Fluctuation Assessment Scale (ODFAS). The number of "misses" made was a significant predictor of their fluctuation severity, attentional performance, disorganized thinking, and language production ratings on the ODFAS. However, measures on the SART did not correlate with measures on the CAF scale. In conclusion, these findings suggest that SART is a feasible measure of sustained attention in this population and has clinical and diagnostic relevance to the measurement of CF, particularly those aspects measured by the ODFAS.

Cholinergic muscarinic M1/M4 receptor networks in dementia with Lewy bodies

Cholinergic dysfunction is central in dementia with Lewy bodies, possibly contributing to the cognitive and psychiatric phenotypes of this condition. We investigated baseline muscarinic M₁/M₄ receptor spatial covariance patterns in dementia with Lewy bodies and their association with changes in cognition and neuropsychiatric symptoms after 12 weeks of treatment with the cholinesterase inhibitor donepezil. Thirty-eight participants (14 cholinesterase inhibitor naive patients, 24 healthy older individuals) underwent ¹²³I-iodo-quinuclidinyl-benzilate (M₁/M₄ receptor assessment) and ^99mTc-exametazime (perfusion) single-photon emission computed tomography scanning. We implemented voxel principal components analysis, producing a series of images representing patterns of inter-correlated voxels across individuals. Linear regression analyses derived specific M₁/M₄ and perfusion spatial covariance patterns associated with patients. A discreet M₁/M₄ pattern that distinguished patients from controls (W_1,19.7 = 16.7, P = 0.001), showed relative decreased binding in right lateral temporal and insula, as well as relative preserved/increased binding in frontal, precuneus, lingual and cuneal regions, implicating nodes within attention and dorsal visual networks. We then derived from patients an M₁/M₄ pattern that correlated with a positive change in mini-mental state examination (r = 0.52, P = 0.05), showing relative preserved/increased uptake in prefrontal, temporal pole and anterior cingulate, elements of attention-related networks. We also generated from patients an M₁/M₄ pattern that correlated with a positive change in neuropsychiatric inventory score (r = 0.77, P = 0.002), revealing relative preserved/increased uptake within a bilateral temporal-precuneal-striatal system. Although in a small sample and therefore tentative, we posit that optimal response of donepezil on cognitive and neuropsychiatric signs in patients with dementia with Lewy bodies were associated with a maintenance of muscarinic M₁/M₄ receptor expression within attentional/executive and ventral visual network hubs, respectively.

Fluctuating cognition in the Lewy body dementias

Fluctuating cognition is a core diagnostic feature of dementia with Lewy bodies and is also a key clinical feature of Parkinson's disease dementia. These dementias share common pathological features and are referred to as Lewy body dementias. Whilst highly prevalent in Lewy body dementia, with up to 90% of patients experiencing the symptom at some point in the disease trajectory, clinical identification of fluctuating cognition is often challenging. Furthermore, its underlying pathophysiological processes remain unclear. However, neuroimaging and neurophysiological techniques have recently provided insight into potential drivers of the phenomenon. In this update, we review data pertaining to clinical features and underlying mechanisms of fluctuating cognition in Lewy body dementia. We collate evidence for different proposed aetiologies: fluctuating cognition as an attentional disorder, as a consequence of loss of cholinergic drive, as a manifestation of failure in neuronal efficiency and synchrony, and as a disorder of sleep/arousal. We also review data relating to putative mechanisms that have received less attention to date. Increased understanding of fluctuating cognition may help to illuminate pathophysiological mechanisms in cognitive processing in Lewy body dementia, guide future research, and facilitate the design of targeted therapeutic approaches.

Bilateral nucleus basalis of Meynert deep brain stimulation for dementia with Lewy bodies: A randomised clinical trial

BACKGROUND

Dementia with Lewy bodies (DLB) is the second most common form of dementia. Current symptomatic treatment with medications remains inadequate. Deep brain stimulation of the nucleus basalis of Meynert (NBM DBS) has been proposed as a potential new treatment option in dementias.

OBJECTIVE

To assess the safety and tolerability of low frequency (20 Hz) NBM DBS in DLB patients and explore its potential effects on both clinical symptoms and functional connectivity in underlying cognitive networks.

METHODS

We conducted an exploratory randomised, double-blind, crossover trial of NBM DBS in six DLB patients recruited from two UK neuroscience centres. Patients were aged between 50 and 80 years, had mild-moderate dementia symptoms and were living with a carer-informant. Patients underwent image guided stereotactic implantation of bilateral DBS electrodes with the deepest contacts positioned in the Ch4i subsector of NBM. Patients were subsequently assigned to receive either active or sham stimulation for six weeks, followed by a two week washout period, then the opposite condition for six weeks. Safety and tolerability of both the surgery and stimulation were systematically evaluated throughout. Exploratory outcomes included the difference in scores on standardised measurements of cognitive, psychiatric and motor symptoms between the active and sham stimulation conditions, as well as differences in functional connectivity in discrete cognitive networks on resting state fMRI.

RESULTS

Surgery and stimulation were well tolerated by all six patients (five male, mean age 71.33 years). One serious adverse event occurred: one patient developed antibiotic-associated colitis, prolonging his hospital stay by two weeks. No consistent improvements were observed in exploratory clinical outcome measures, but the severity of neuropsychiatric symptoms reduced with NBM DBS in 3/5 patients. Active stimulation was associated with functional connectivity changes in both the default mode network and the frontoparietal network.

CONCLUSION

Low frequency NBM DBS can be safely conducted in DLB patients. This should encourage further exploration of the possible effects of stimulation on neuropsychiatric symptoms and corresponding changes in functional connectivity in cognitive networks.

TRIAL REGISTRATION NUMBER

NCT02263937.

Changes in gray matter volume and functional connectivity in dementia with Lewy bodies compared to Alzheimer's disease and normal aging: implications for fluctuations

BACKGROUND

Fluctuations are one of the core clinical features characterizing dementia with Lewy bodies (DLB). They represent a determining factor for its diagnosis and strongly impact the quality of life of patients and their caregivers. However, the neural correlates of this complex symptom remain poorly understood. This study aimed to investigate the structural and functional changes in DLB patients, compared to Alzheimer's disease (AD) patients and healthy elderly subjects, and their potential links with fluctuations.

METHODS

Structural and resting-state functional MRI data were collected from 92 DLB patients, 70 AD patients, and 22 control subjects, who also underwent a detailed clinical examination including the Mayo Clinic Fluctuation Scale. Gray matter volume changes were analyzed using whole-brain voxel-based morphometry, and resting-state functional connectivity was investigated using a seed-based analysis, with regions of interest corresponding to the main nodes of the salience network (SN), frontoparietal network (FPN), dorsal attention network (DAN), and default mode network (DMN).

RESULTS

At the structural level, fluctuation scores in DLB patients did not relate to the atrophy of insular, temporal, and frontal regions typically found in this pathology, but instead showed a weak correlation with more subtle volume reductions in different regions of the cholinergic system. At the functional level, the DLB group was characterized by a decreased connectivity within the SN and attentional networks, while the AD group showed decreases within the SN and DMN. In addition, higher fluctuation scores in DLB patients were correlated to a greater connectivity of the SN with the DAN and left thalamus, along with a decreased connectivity between the SN and DMN, and between the right thalamus and both the FPN and DMN.

CONCLUSIONS

Functional connectivity changes, rather than significant gray matter loss, could play an important role in the emergence of fluctuations in DLB. Notably, fluctuations in DLB patients appeared to be related to a disturbed external functional connectivity of the SN, which may lead to less relevant transitions between different cognitive states in response to internal and environmental stimuli. Our results also suggest that the thalamus could be a key region for the occurrence of this symptom.

Weighted network measures reveal differences between dementia types: An EEG study

The diagnosis of dementia with Lewy bodies (DLB) versus Alzheimer's disease (AD) can be difficult especially early in the disease process. However, one inexpensive and non‐invasive biomarker which could help is electroencephalography (EEG). Previous studies have shown that the brain network architecture assessed by EEG is altered in AD patients compared with age‐matched healthy control people (HC). However, similar studies in Lewy body diseases, that is, DLB and Parkinson's disease dementia (PDD) are still lacking. In this work, we (a) compared brain network connectivity patterns across conditions, AD, DLB and PDD, in order to infer EEG network biomarkers that differentiate between these conditions, and (b) tested whether opting for weighted matrices led to more reliable results by better preserving the topology of the network. Our results indicate that dementia groups present with reduced connectivity in the EEG α band, whereas DLB shows weaker posterior–anterior patterns within the β‐band and greater network segregation within the θ‐band compared with AD. Weighted network measures were more consistent across global thresholding levels, and the network properties reflected reduction in connectivity strength in the dementia groups. In conclusion, β‐ and θ‐band network measures may be suitable as biomarkers for discriminating DLB from AD, whereas the α‐band network is similarly affected in DLB and PDD compared with HC. These variations may reflect the impairment of attentional networks in Parkinsonian diseases such as DLB and PDD.

Dysfunctional Dynamics of Intra- and Inter-network Connectivity in Dementia With Lewy Bodies

Dementia with Lewy bodies (DLB) is characterized by the transient fluctuating cognition and recurrent visual hallucinations, which may be caused by disorders of the intrinsic brain network dynamics. However, little is known regarding the dynamic features of the brain network behind these symptoms in DLB. In the present study, the intra- and inter-brain network dynamics were explored on a time scale in 17 DLB and 20 healthy controls (HC) applying a sliding-window method followed by k-means clustering analysis. To further evaluate the impact of network dynamics on brain performance, the local and global efficiency of the brain network was calculated. Compared with HC, the dynamic functional connectivity variation matrix in DLB patients was represented by a mixed change of intra-network increase and inter-network decrease. DLB patients devoted more time to a negative connectivity pattern, which represents a state of functional separation. Furthermore, the local efficiency of DLB patients was significantly lower compared with HC. These observations indicate an altered dynamic variability and disorders to the time allocation of state sequences in DLB, which might result in a disturbance of the intricate brain network dynamic properties, thereby leading to a lack of integration and flexibility and an ineffective brain function. In conclusion, dynamic functional connectivity analysis could identify differences between DLB and HC, providing evidences for DLB diagnosis and contributing to the understanding of the widespread clinical features and complex treatment strategies in DLB patients.

Aberrant functional connectivity of resting state networks related to misperceptions and intra-individual variability in Parkinson's disease

Patients with Parkinson's disease (PD) frequently suffer from visual misperceptions and hallucinations, which are difficult to objectify and quantify. We aimed to develop an image recognition task to objectify misperceptions and to assess performance fluctuations in PD patients with and without self-reported hallucinations. Thirty-two non-demented patients with Parkinson's disease (16 with and 16 without self-reported visual hallucinations) and 25 age-matched healthy controls (HC) were tested. Participants performed a dynamic image recognition task with real and scrambled images. We assessed misperception scores and intra-individual variability in recognition times. To gain insight into possible neural mechanisms related to misperceptions and performance fluctuations we correlated resting state network connectivity to the behavioral outcomes in a subsample of Parkinson's disease patients (N = 16). We found that PD patients with self-reported hallucinations (PD-VH) exhibited higher perceptual error rates, due to decreased perceptual sensitivity and not due to changed decision criteria. In addition, PD-VH patients exhibited higher intra-individual variability in recognition times than HC or PD-nonVH patients. Both, misperceptions and intra-individual variability were negatively correlated with resting state functional connectivity involving frontal and parietal brain regions, albeit in partly different subregions. Consistent with previous research suggesting that hallucinations arise from dysfunction in attentional networks, misperception scores correlated with reduced functional connectivity between the dorsal attention and salience network. Intra-individual variability correlated with decreased connectivity between somatomotor and right fronto-parietal networks. We conclude that our task can detect visual misperceptions that are more prevalent in PD-VH patients. In addition, fluctuating visual performance appear to be a signature of PD-VH patients, which might assist further studies of the underlying pathophysiological mechanisms and cognitive processes.

Cognitive fluctuations in Lewy body dementia: towards a pathophysiological framework

Fluctuating cognition is a complex and disabling symptom that is seen most frequently in the context of Lewy body dementias encompassing dementia with Lewy bodies and Parkinson’s disease dementia. In fact, since their description over three decades ago, cognitive fluctuations have remained a core diagnostic feature of dementia with Lewy bodies, the second most common dementia in the elderly. In the absence of reliable biomarkers for Lewy body pathology, the inclusion of such patients in therapeutic trials depends on the accurate identification of such core clinical features. Yet despite their diagnostic relevance, cognitive fluctuations remain poorly understood, in part due to the lack of a cohesive clinical and scientific explanation of the phenomenon itself. Motivated by this challenge, the present review examines the history, clinical phenomenology and assessment of cognitive fluctuations in the Lewy body dementias. Based on these data, the key neuropsychological, neurophysiological and neuroimaging correlates of cognitive fluctuations are described and integrated into a novel testable heuristic framework from which new insights may be gained.

Vulnerability of multiple large-scale brain networks in dementia with Lewy bodies

Aberrations of large-scale brain networks are found in the majority of neurodegenerative disorders. The brain connectivity alterations underlying dementia with Lewy bodies (DLB) remain, however, still elusive, with contrasting results possibly due to the pathological and clinical heterogeneity characterizing this disorder. Here, we provide a molecular assessment of brain network alterations, based on cerebral metabolic measurements as proxies of synaptic activity and density, in a large cohort of DLB patients (N = 72). We applied a seed-based interregional correlation analysis approach (p < .01, false discovery rate corrected) to evaluate large-scale resting-state networks' integrity and their interactions. We found both local and long-distance metabolic connectivity alterations, affecting the posterior cortical networks, that is, primary visual and the posterior default mode network, as well as the limbic and attention networks, suggesting a widespread derangement of the brain connectome. Notably, patients with the lowest visual and attention cognitive scores showed the most severe connectivity derangement in regions of the primary visual network. In addition, network-level alterations were differentially associated with the core clinical manifestations, namely, hallucinations with more severe metabolic dysfunction of the attention and visual networks, and rapid eye movement sleep behavior disorder with alterations of connectivity of attention and subcortical networks. These multiple network-level vulnerabilities may modulate the core clinical and cognitive features of DLB and suggest that DLB should be considered as a complex multinetwork disorder.

Structural correlates of attention dysfunction in Lewy body dementia and Alzheimer's disease: an ex-Gaussian analysis

BACKGROUND

Lewy body dementia (LBD) and Alzheimer's disease (AD) are common forms of degenerative dementia. While they are characterized by different clinical profiles, attentional deficits are a common feature. The objective of this study was to investigate how attentional problems in LBD and AD differentially affect different aspects of reaction time performance and to identify possible structural neural correlates.

METHODS

We studied reaction time data from an attention task comparing 39 LBD patients, 28 AD patients, and 22 age-matched healthy controls. Data were fitted to an ex-Gaussian model to characterize different facets of the reaction time distribution (mean reaction time, reaction time variability, and the subset of extremely slow responses). Correlations between ex-Gaussian parameters and grey and white matter volume were assessed by voxel-based morphometry.

RESULTS

Both dementia groups showed an increase in extremely slow responses. While there was no difference between AD and controls with respect to mean reaction time and variability, both were significantly increased in LBD patients compared to controls and AD. There were widespread correlations between mean reaction time and variability and grey matter loss in AD, but not in LBD.

CONCLUSIONS

This study shows that different aspects of reaction time performance are differentially affected by AD and LBD, with a difference in structural neural correlates underlying the observed behavioural deficits. While impaired attentional performance is linked to brain atrophy in AD, in LBD it might be related to functional or microstructural rather than macrostructural changes.

Resting State Dynamic Functional Connectivity in Neurodegenerative Conditions: A Review of Magnetic Resonance Imaging Findings

In the last few decades, brain functional connectivity (FC) has been extensively assessed using resting-state functional magnetic resonance imaging (RS-fMRI), which is able to identify temporally correlated brain regions known as RS functional networks. Fundamental insights into the pathophysiology of several neurodegenerative conditions have been provided by studies in this field. However, most of these studies are based on the assumption of temporal stationarity of RS functional networks, despite recent evidence suggests that the spatial patterns of RS networks may change periodically over the time of an fMRI scan acquisition. For this reason, dynamic functional connectivity (dFC) analysis has been recently implemented and proposed in order to consider the temporal fluctuations of FC. These approaches hold promise to provide fundamental information for the identification of pathophysiological and diagnostic markers in the vast field of neurodegenerative diseases. This review summarizes the main currently available approaches for dFC analysis and reports their recent applications for the assessment of the most common neurodegenerative conditions, including Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, and frontotemporal dementia. Critical state-of-the-art findings, limitations, and future perspectives regarding the analysis of dFC in these diseases are provided from both a clinical and a technical point of view.

EEG Resting-State Networks in Dementia with Lewy Bodies Associated with Clinical Symptoms

BACKGROUND

Dementia with Lewy bodies (DLB) is characterized by progressive cognitive decline, fluctuating cognition, visual hallucinations, rapid eye movement sleep behavior disorder, and parkinsonism. DLB is the second most common type of degenerative dementia of all dementia cases. However, DLB, particularly in the early stage, is underdiagnosed and sometimes misdiagnosed with other types of dementia. Thus, it is of great interest investigating neurophysiological markers of DLB.

METHOD

We introduced exact low-resolution brain electromagnetic tomography (eLORETA)-independent component analysis (ICA) to assess activities of 5 electroencephalography (EEG) resting-state networks (RSNs) in 41 drug-free DLB patients.

RESULTS

Compared to 80 healthy controls, DLB patients had significantly decreased activities in occipital visual and sensorimotor networks, where DLB patients and healthy controls showed no age dependences in all EEG-RSN activities. Also, we found correlations between all EEG-RSN activities and DLB symptoms. Specifically, decreased occipital α activity showed correlations with worse brain functions related to attention/concentration, visuospatial discrimination, and global cognition. Enhanced visual perception network activity correlated with milder levels of depression and anxiety. Enhanced self-referential network activity correlated with milder levels of depression. Enhanced memory perception network activity correlated with better semantic memory, visuospatial discrimination function, and global cognitive function as well as with severer visual hallucination. In addition, decreased sensorimotor network activity correlated with a better semantic memory.

CONCLUSION

These results indicate that eLORETA-ICA can detect EEG-RSN activity alterations in DLB related to symptoms. Therefore, eLORETA-ICA with EEG data can be a useful noninvasive tool for sensitive detection of EEG-RSN activity changes characteristic of DLB and for understanding the neurophysiological mechanisms underlying this disease.

Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer's disease

We studied the dynamic functional connectivity profile of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) compared to controls, how it differs between the two dementia subtypes, and a possible relation between dynamic connectivity alterations and temporally transient clinical symptoms in DLB. Resting state fMRI data from 31 DLB, 29 AD, and 31 healthy control participants were analyzed using dual regression to determine between-network functional connectivity. Subsequently, we used a sliding window approach followed by k-means clustering and dynamic network analyses to study dynamic functional connectivity. Dynamic connectivity measures that showed significant group differences were tested for correlations with clinical symptom severity. Our results show that AD and DLB patients spent more time than controls in sparse connectivity configurations with absence of strong positive and negative connections and a relative isolation of motor networks from other networks. Additionally, DLB patients spent less time in a more strongly connected state and the variability of global brain network efficiency was reduced in DLB compared to controls. There were no significant correlations between dynamic connectivity measures and clinical symptom severity. An inability to switch out of states of low inter-network connectivity into more highly and specifically connected network configurations might be related to the presence of dementia in general as it was observed in both AD and DLB. In contrast, the loss of global efficiency variability in DLB might indicate the presence of an abnormally rigid brain network and the lack of economical dynamics, factors which could contribute to cognitive slowing and an inability to respond appropriately to situational demands.

Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer's and Lewy Body Diseases

The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) score was matched between the ADMCI and DLBMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test the clinical validity of these rsEEG markers.

Structural and Functional Magnetic Resonance Imaging of Dementia With Lewy Bodies

Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimer's disease (AD). Although diagnosis may be challenging, there is increasing evidence that the use of biomarkers according to 2017 revised criteria for diagnosis and management of dementia with Lewy bodies can increase diagnostic accuracy. Apart from nuclear medicine techniques, various magnetic resonance imaging (MRI) techniques have been utilized in attempt to enhance diagnostic accuracy. This chapter reviews structural, functional and diffusion MRI studies in DLB cohorts being compared to healthy controls, AD or dementia in Parkinson's disease (PDD). We also included relatively new MRI methods that may have potential to identify early DLB subjects and aim at examining brain iron and neuromelanin.