Default network is not hypoactive in dementia with fluctuating cognition: an Alzheimer disease/dementia with Lewy bodies comparison

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.

The central role of the Thalamus in psychosis, lessons from neurodegenerative diseases and psychedelics

The PD-DLB psychosis complex found in Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB) includes hallucinations, Somatic Symptom/Functional Disorders, and delusions. These disorders exhibit similar presentation patterns and progression. Mechanisms at the root of these symptoms also share similarities with processes promoting altered states of consciousness found in Rapid Eye Movement sleep, psychiatric disorders, or the intake of psychedelic compounds. We propose that these mechanisms find a crucial driver and trigger in the dysregulated activity of high-order thalamic nuclei set in motion by ThalamoCortical Dysrhythmia (TCD). TCD generates the loss of finely tuned cortico-cortical modulations promoted by the thalamus and unleashes the aberrant activity of the Default Mode Network (DMN). TCD moves in parallel with altered thalamic filtering of external and internal information. The process produces an input overload to the cortex, thereby exacerbating DMN decoupling from task-positive networks. These phenomena alter the brain metastability, creating dreamlike, dissociative, or altered states of consciousness. In support of this hypothesis, mind-altering psychedelic drugs also modulate thalamic-cortical pathways. Understanding the pathophysiological background of these conditions provides a conceptual bridge between neurology and psychiatry, thereby helping to generate a promising and converging area of investigation and therapeutic efforts.

(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.

Contribution of cognitive and bodily navigation cues to egocentric and allocentric spatial memory in hallucinations due to Parkinson's disease: A case report

Parkinson's disease (PD) manifestations can include visual hallucinations and illusions. Recent findings suggest that the coherent integration of bodily information within an egocentric representation could play a crucial role in these phenomena. Egocentric processing is a key aspect of spatial navigation and is supported by the striatum. Due to the deterioration of the striatal and motor systems, PD mainly impairs the egocentric rather than the allocentric spatial frame of reference. However, it is still unclear the interplay between spatial cognition and PD hallucinations and how different navigation mechanisms can influence such spatial frames of reference. We report the case of A.A., a patient that suffers from PD with frequent episodes of visual hallucinations and illusions. We used a virtual reality (VR) navigation task to assess egocentric and allocentric spatial memory under five navigation conditions (passive, immersive, map, path decision, and attentive cues) in A.A. and a PD control group without psychosis. In general, A.A. exhibited a statistically significant classical dissociation between the egocentric and allocentric performance with a greater deficit for the former. In particular, the dissociation was statistically significant in the “passive” and “attentive cues” conditions. Interestingly in the “immersive” condition, the dissociation was not significant and, in contrast to the other conditions, trends showed better performance for egocentric than allocentric memory. Within the theories of embodiment, we suggest that body-based information, as assessed with VR navigation tasks, could play an important role in PD hallucinations. In addition, the possible neural underpinnings and the usefulness of VR are discussed.

Simultaneous electroencephalography-functional magnetic resonance imaging for assessment of human brain function

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (MRI) have long been used as tools to examine brain activity. Since both methods are very sensitive to changes of synaptic activity, simultaneous recording of EEG and fMRI can provide both high temporal and spatial resolution. Therefore, the two modalities are now integrated into a hybrid tool, EEG-fMRI, which encapsulates the useful properties of the two. Among other benefits, EEG-fMRI can contribute to a better understanding of brain connectivity and networks. This review lays its focus on the methodologies applied in performing EEG-fMRI studies, namely techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. We will investigate simultaneous resting-state and task-based EEG-fMRI studies and discuss their clinical and technological perspectives. Moreover, it is established that the brain regions affected by a task-based neural activity might not be limited to the regions in which they have been initiated. Advanced methods can help reveal the regions responsible for or affected by a developed neural network. Therefore, we have also looked into studies related to characterization of structure and dynamics of brain networks. The reviewed literature suggests that EEG-fMRI can provide valuable complementary information about brain neural networks and functions.

Dynamic network impairments underlie cognitive fluctuations in Lewy body dementia

Cognitive fluctuations are a characteristic and distressing disturbance of attention and consciousness seen in patients with Dementia with Lewy bodies and Parkinson's disease dementia. It has been proposed that fluctuations result from disruption of key neuromodulatory systems supporting states of attention and wakefulness which are normally characterised by temporally variable and highly integrated functional network architectures. In this study, patients with DLB (n = 25) and age-matched controls (n = 49) were assessed using dynamic resting state fMRI. A dynamic network signature of reduced temporal variability and integration was identified in DLB patients compared to controls. Reduced temporal variability correlated significantly with fluctuation-related measures using a sustained attention task. A less integrated (more segregated) functional network architecture was seen in DLB patients compared to the control group, with regions of reduced integration observed across dorsal and ventral attention, sensorimotor, visual, cingulo-opercular and cingulo-parietal networks. Reduced network integration correlated positively with subjective and objective measures of fluctuations. Regions of reduced integration and unstable regional assignments significantly matched areas of expression of specific classes of noradrenergic and cholinergic receptors across the cerebral cortex. Correlating topological measures with maps of neurotransmitter/neuromodulator receptor gene expression, we found that regions of reduced integration and unstable modular assignments correlated significantly with the pattern of expression of subclasses of noradrenergic and cholinergic receptors across the cerebral cortex. Altogether, these findings demonstrate that cognitive fluctuations are associated with an imaging signature of dynamic network impairment linked to specific neurotransmitters/neuromodulators within the ascending arousal system, highlighting novel potential diagnostic and therapeutic approaches for this troubling symptom.

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.

Functional neurological disorder and somatic symptom disorder in Parkinson's disease

The occurrence of Functional Neurological Disorder (FND) and Somatic Symptom Disorder (SSD) in PD was not commonly accepted until recently, despite some evidence that emerged in the pre and early L-Dopa era. More recently, the recognition of FND and SSD were noted to be relevant for the management of PD. FND and SSD appear early in the course of PD, often preceding motor symptoms, may interfere with treatment outcomes, often acquire psychotic features during progression, and are mixed with and often concealed by the progressive cognitive decline. We review the related features from the range of the available reports and discuss theoretical models conceived to explain the potential pathophysiological background of these disorders. Finally, we suggest that FND and SSD should be included among the non-motor symptoms of PD and be considered a prodromal feature in a subset of patients. This article is part of the Special Issue "Parkinsonism across the spectrum of movement disorders and beyond" edited by Joseph Jankovic, Daniel D. Truong and Matteo Bologna.

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.

Preexisting Bipolar Disorder Influences the Subsequent Phenotype of Parkinson's Disease

Background

Patients with bipolar spectrum disorders (BSDs) exhibit an increased risk of Parkinson's disease (PD).

Objective

The aim is to investigate whether a previous diagnosis of BSDs influences the phenotype of PD.

Methods

Of 2660 PD patients followed for at least 6 years (6–27), 250 (BSD‐PD) had BSDs, 6–20 years before PD diagnosis; 48%–43% had a PD or BSD family history, and 34 carried glucocerebrosidase (GBA) and Parkin (PRKN) mutations. The cohort was split into a subset of 213 BSD‐PD patients, compared with 426 matched PD patients without BSDs, and a subset of 34 BSD‐PD and 79 PD patients carrying GBA or PRKN mutations. Carriers of mutations absent in BSD‐PD patients and of synuclein triplication were excluded. Structured clinical interviews and mood disorder questionnaires assessed BSDs. Linear mixed models evaluated the assessment scales over time. Thirteen BSD‐PD patients underwent subthalamic nucleus deep brain stimulation (STN‐DBS) and were compared with 27 matched STN‐DBS‐treated PD patients.

Results

Compared to PD patients, BSD‐PD showed (1) higher frequency of family history of PD (odds ratio [OR] 3.31; 2.32–4.71) and BSDs (OR 6.20; 4.11–9.35) 5); (2) higher incidence of impulse control disorders (hazard ratio [HR] 5.95, 3.89–9.09); (3) higher frequency of functional disorders occurring before PD therapy (HR, 5.67, 3.95–8.15); (4) earlier occurrence of delusions or mild dementia (HR, 7.70, 5.55–10.69; HR, 1.43, 1.16–1.75); and (5) earlier mortality (1.48; 1.11–1.97). Genetic BSD‐PD subjects exhibited clinical features indistinguishable from nongenetic BSD‐PD subjects. STN‐DBS‐treated BSD‐PD patients showed no improvements in quality of life compared to the control group.

Conclusions

BSDs as a prodrome to PD unfavorably shape their course and are associated with detrimental neuropsychiatric features and treatment outcomes. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

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.

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.

Electroencephalogram in dementia with Lewy bodies: a systematic review

Dementia with Lewy bodies (DLB) belongs to the spectrum of Lewy body dementia (LBD) that also encompasses Parkinson's disease dementia (PDD). It is a common neurodegenerative disorder characterized by memory decline, cognitive fluctuations, visual hallucinations, autonomic nervous system disturbance, REM sleep behavior disorder, and parkinsonism. Definite diagnosis can be established only through neuropathological confirmation of Lewy bodies' presence in brain tissue. Probable or possible diagnosis relies upon clinical features, imaging, polysomnography, and electroencephalogram (EEG) findings. Potential neurophysiological biomarkers for the diagnosis, management, and evaluation of treatment-response in DLB should be affordable and widely available outside academic centers. Increasing evidence supports the use of quantitative EEG (qEEG) as a potential DLB biomarker, with promising results in discriminating DLB from other dementias and in identifying subjects who are on the trajectory to develop DLB. Several studies evaluated the diagnostic value of EEG in DLB. Visual analysis and qEEG techniques have been implemented, showing a superiority of the last in terms of sensitivity and objectivity. In this systematic review, we attempt to provide a general synthesis of the current knowledge on EEG application in DLB. We review the findings from original studies and address the issues remaining to be further clarified.

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.

Visual evoked potential abnormalities in dementia with Lewy bodies

OBJECTIVES

Visuo-perceptual deficits and visual hallucinations (VHs) are common disturbances in patients with dementia with Lewy bodies (DLB) and those with Parkinson's disease (PD). In particular, delays in visual evoked potential (VEP), reversed by l-dopa administration, have previously been observed in PD patients. Impairment in metabolic functions of dopaminergic amacrine cells within the inner plexiform layer of the retina has been largely documented and has been posited as the underlying cause of visual and retinal alterations in PD. The aims of the present study were to investigate the presence of VEP abnormalities in DLB patients, as compared to a PD control group, and to assess the presence of significant correlations between neurophysiological measures and clinical symptoms (i.e., presence of visuospatial deficits and/or visual hallucinations).

METHODS

Fifteen DLB patients and fifteen matched PD patients underwent pattern reversal before and after l-dopa administration, and a short neuropsychological assessment.

RESULTS

In DLB patients, we observed delay of the P100 latency to foveal stimuli in both eyes compared to normative values. Compared to PD, DLB patients showed higher values of the P100 latency for foveal stimulation from the right eye prior to l-dopa administration (p = 0.018). No correlations between VEP alterations, visuo-spatial deficit and visual hallucinations were found.

DISCUSSION

Our findings demonstrated a longer P100 delay in DLB than in PD patients, especially along the right visual pathway. In contrast to previous studies, which focused on a dopaminergic pre-geniculate impairment of visual pathways, our evidence suggests that other mechanisms, possibly relying on thalamic involvement, which is known to be dysfunctional in DLB, can interfere with VEP abnormalities.

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.

Crosstalk between Depression and Dementia with Resting-State fMRI Studies and Its Relationship with Cognitive Functioning

Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.

[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.

3D-Deep Learning Based Automatic Diagnosis of Alzheimer's Disease with Joint MMSE Prediction Using Resting-State fMRI

We performed this research to 1) evaluate a novel deep learning method for the diagnosis of Alzheimer's disease (AD) and 2) jointly predict the Mini Mental State Examination (MMSE) scores of South Korean patients with AD. Using resting-state functional Magnetic Resonance Imaging (rs-fMRI) scans of 331 participants, we obtained functional 3-dimensional (3-D) independent component spatial maps for use as features in classification and regression tasks. A 3-D convolutional neural network (CNN) architecture was developed for the classification task. MMSE scores were predicted using: linear least square regression (LLSR), support vector regression, bagging-based ensemble regression, and tree regression with group independent component analysis (gICA) features. To improve MMSE regression performance, we applied feature optimization methods including least absolute shrinkage and selection operator and support vector machine-based recursive feature elimination (SVM-RFE). The mean balanced test accuracy was 85.27% for the classification of AD versus healthy controls. The medial visual, default mode, dorsal attention, executive, and auditory related networks were mainly associated with AD. The maximum clinical MMSE score prediction accuracy with the LLSR method applied on gICA combined with SVM-RFE features had the lowest root mean square error (3.27 ± 0.58) and the highest R² value (0.63 ± 0.02). Classification of AD and healthy controls can be successfully achieved using only rs-fMRI and MMSE scores can be accurately predicted using functional independent component features. In the absence of trained clinicians, AD disease status and clinical MMSE scores can be jointly predicted using 3-D deep learning and regression learning approaches with rs-fMRI data.

The Role of EEG in the Diagnosis, Prognosis and Clinical Correlations of Dementia with Lewy Bodies-A Systematic Review

Despite improvements in diagnostic criteria for dementia with Lewy bodies (DLB), the ability to discriminate DLB from Alzheimer’s disease (AD) and other dementias remains suboptimal. Electroencephalography (EEG) is currently a supportive biomarker in the diagnosis of DLB. We performed a systematic review to better clarify the diagnostic and prognostic role of EEG in DLB and define the clinical correlates of various EEG features described in DLB. MEDLINE, EMBASE, and PsycINFO were searched using search strategies for relevant articles up to 6 August 2020. We included 43 studies comparing EEG in DLB with other diagnoses, 42 of them included a comparison of DLB with AD, 10 studies compared DLB with Parkinson’s disease dementia, and 6 studies compared DLB with other dementias. The studies were visual EEG assessment (6), quantitative EEG (35) and event-related potential studies (2). The most consistent observation was the slowing of the dominant EEG rhythm (<8 Hz) assessed visually or through quantitative EEG, which was observed in ~90% of patients with DLB and only ~10% of patients with AD. Other findings based on qualitative rating, spectral power analyses, connectivity, microstate and machine learning algorithms were largely heterogenous due to differences in study design, EEG acquisition, preprocessing and analysis. EEG protocols should be standardized to allow replication and validation of promising EEG features as potential biomarkers in DLB.

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.

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.

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.

Somatic symptoms disorders in Parkinson's disease are related to default mode and salience network dysfunction

Background

Somatic Symptoms Disorder (SSD) has been shown to have a clinically very high prevalence in Parkinson's Disease (PD) with frequencies ranging from 7.0% to 66.7%, higher than in the general population (10%- 25%).

SSD has been associated with dysfunction in Default Mode and Salience network.

Aim

With the present study we aim to verify by means of resting state functional MRI whether possible specific abnormalities in the activation and functional connectivity of the default mode network (DMN) and salience network in cognitively intact PD patients may be more prominent in PD patients with somatic symptoms (SSD-PD) as compared with patients without SSD (PD).

Methods

Eighteen SSD-PD patients (61% male), 18 PD patients (83% male) and 22 healthy age-matched subjects (59% male) were enrolled in the study and underwent resting state functional MRI.

Results

fractional amplitude of low-frequency fluctuation (fALFF) showed reduced activity in bilateral lateral parietal cortex and in left anterior insula in both SSD-PD and PD compared to control group. Functional connectivity (FC) values in the DMN areas and between DMN and salience network areas were found to be lower in SSD-PD than in control group and PD. No significant correlation was found between fMRI results and demographic and clinical variables, excluding the effect of possible confounders on fMRI results.

The present study, showing reduced activity in bilateral parietal areas and in the left anterior insula as compared to healthy controls, suggests a dysfunction of the DMN and salience network in PD, either with or without SSD.

The FC reduction within DMN areas and between DMN and salience network areas in SSD-PD patients suggests a role of dysfunctional connectivity in the resting state network of patients with SSD.

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Reduced activity in parietal areas and in anterior insula in Parkinson's Disease.

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Functional connectivity is lower in Parkinson's disease with somatic symptoms.

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Somatic Symptoms in PD are related to default mode and salience network alterations.

Hallucinations, somatic-functional disorders of PD-DLB as expressions of thalamic dysfunction

Hallucinations, delusions, and functional neurological manifestations (conversion and somatic symptom disorders) of Parkinson's disease (PD) and dementia with Lewy bodies increase in frequency with disease progression, predict the onset of cognitive decline, and eventually blend with and are concealed by dementia. These symptoms share the absence of reality constraints and can be considered comparable elements of the PD-dementia with Lewy bodies psychosis. We propose that PD-dementia with Lewy bodies psychotic disorders depend on thalamic dysfunction promoting a theta burst mode and subsequent thalamocortical dysrhythmia with focal cortical coherence to theta electroencephalogram rhythms. This theta electroencephalogram activity, also called fast-theta or pre-alpha, has been shown to predict cognitive decline and fluctuations in Parkinson's disease with dementia and dementia with Lewy bodies. These electroencephalogram alterations are now considered a predictive marker for progression to dementia. The resulting thalamocortical dysrhythmia inhibits the frontal attentional network and favors the decoupling of the default mode network. As the default mode network is involved in integration of self-referential information into conscious perception, unconstrained default mode network activity, as revealed by recent imaging studies, leads to random formation of connections that link strong autobiographical correlates to trivial stimuli, thereby producing hallucinations, delusions, and functional neurological disorders. The thalamocortical dysrhythmia default mode network decoupling hypothesis provides the rationale for the design and testing of novel therapeutic pharmacological and nonpharmacological interventions in the context of PD, PD with dementia, and dementia with Lewy bodies. © 2019 International Parkinson and Movement Disorder Society.

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.

Evaluation of Functional Decline in Alzheimer's Dementia Using 3D Deep Learning and Group ICA for rs-fMRI Measurements

Purpose: To perform automatic assessment of dementia severity using a deep learning framework applied to resting-state functional magnetic resonance imaging (rs-fMRI) data.

Method: We divided 133 Alzheimer’s disease (AD) patients with clinical dementia rating (CDR) scores from 0.5 to 3 into two groups based on dementia severity; the groups with very mild/mild (CDR: 0.5–1) and moderate to severe (CDR: 2–3) dementia consisted of 77 and 56 subjects, respectively. We used rs-fMRI to extract functional connectivity features, calculated using independent component analysis (ICA), and performed automated severity classification with three-dimensional convolutional neural networks (3D-CNNs) based on deep learning.

Results: The mean balanced classification accuracy was 0.923 ± 0.042 (p < 0.001) with a specificity of 0.946 ± 0.019 and sensitivity of 0.896 ± 0.077. The rs-fMRI data indicated that the medial frontal, sensorimotor, executive control, dorsal attention, and visual related networks mainly correlated with dementia severity.

Conclusions: Our CDR-based novel classification using rs-fMRI is an acceptable objective severity indicator. In the absence of trained neuropsychologists, dementia severity can be objectively and accurately classified using a 3D-deep learning framework with rs-fMRI independent components.

Going beyond the mean: Intraindividual variability of cognitive performance in prodromal and early neurodegenerative disorders

OBJECTIVE

Intraindividual variability (IIV), generally defined as short-term variations in behavior, has been proposed as a sign of subtle early impairment in neurodegenerative disorders, presumably associated with the disintegration of neuronal network connectivity. We aim to provide a review of IIV as a sensitive cognitive marker in prodromal neurodegenerative disorders.

METHOD

A narrative review focusing not only on theoretical and methodological definitions, including an overview on the neural correlates of IIV, but mainly on results from population-based and clinical-based studies on the role of IIV as a reliable predictor of mild cognitive impairment (MCI) and conversion to dementia in neurodegenerative disorders, mostly Alzheimer's and Parkinson's disease.

RESULTS

Most studies focus on MCI and Alzheimer's disease and demonstrate that IIV is a reliable cognitive marker. IIV is partly more sensitive than mean performance in the prediction of cognitive impairment or progressive deterioration and is independent of socio-demographic variables and disease mediators (e.g., genetic susceptibility). Neuroimaging data, mostly from healthy subjects, suggest a relationship between IIV and dysfunction of the default mode network, presumably mediated by white matter disintegration in frontal and parietal areas.

CONCLUSIONS

IIV measures may provide valuable information about diagnosis and progression in prodromal stages of neurodegenerative disorders. Thus, further conceptual and methodological clarifications are needed to justify the inclusion of IIV as a sensible cognitive marker in routine clinical neuropsychological assessment.

Cortical Network Topology in Prodromal and Mild Dementia Due to Alzheimer's Disease: Graph Theory Applied to Resting State EEG

Graph theory analysis on resting state electroencephalographic rhythms disclosed topological properties of cerebral network. In Alzheimer's disease (AD) patients, this approach showed mixed results. Granger causality matrices were used as input to the graph theory allowing to estimate the strength and the direction of information transfer between electrode pairs. The number of edges (degree), the number of inward edges (in-degree), of outgoing edges (out-degree) were statistically compared among healthy controls, patients with mild cognitive impairment due to AD (AD-MCI) and AD patients with mild dementia (ADD) to evaluate if degree abnormality could involve low and/or high degree vertices, the so called hubs, in both prodromal and over dementia stage. Clustering coefficient and local efficiency were evaluated as measures of network segregation, path length and global efficiency as measures of integration, the assortativity coefficient as a measure of resilience. Degree, in-degree and out-degree values were lower in AD-MCI and ADD than the control group for non-hubs and hubs vertices. The number of edges was preserved for frontal electrodes, where patients' groups showed an additional hub in F3. Clustering coefficient was lower in ADD compared with AD-MCI in the right occipital electrode, and it was positively correlated with mini mental state examination. Local and global efficiency values were lower in patients' than control groups. Our results show that the topology of the network is altered in AD patients also in its prodromal stage, begins with the reduction of the number of edges and the loss of the local and global efficiency.

Neuroimaging in aging and neurologic diseases

Neuroimaging biomarkers for neurologic diseases are important tools, both for understanding pathology associated with cognitive and clinical symptoms and for differential diagnosis. This chapter explores neuroimaging measures, including structural and functional measures from magnetic resonance imaging (MRI) and molecular measures primarily from positron emission tomography (PET), in healthy aging adults and in a number of neurologic diseases. The spectrum covers neuroimaging measures from normal aging to a variety of dementias: late-onset Alzheimer's disease [AD; including mild cognitive impairment (MCI)], familial and nonfamilial early-onset AD, atypical AD syndromes, posterior cortical atrophy (PCA), logopenic aphasia (lvPPA), cerebral amyloid angiopathy (CAA), vascular dementia (VaD), sporadic and familial behavioral-variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA), frontotemporal dementia with motor neuron disease (FTD-MND), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with and without dementia, and multiple systems atrophy (MSA). We also include a discussion of the appropriate use criteria (AUC) for amyloid imaging and conclude with a discussion of differential diagnosis of neurologic dementia disorders in the context of neuroimaging.

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.

Default Mode Network Complexity and Cognitive Decline in Mild Alzheimer's Disease

The human resting-state is characterized by spatially coherent brain activity at a low temporal frequency. The default mode network (DMN), one of so-called resting-state networks, has been associated with cognitive processes that are directed toward the self, such as introspection and autobiographic memory. The DMN's integrity appears to be crucial for mental health. For example, patients with Alzheimer's disease or other psychiatric conditions show disruptions of functional connectivity within the brain regions of the DMN. However, in prodromal or early stages of Alzheimer's disease, physiological alterations are sometimes elusive, despite manifested cognitive impairment. While functional connectivity assesses the signal correlation between brain areas, multi-scale entropy (MSE) measures the complexity of the blood-oxygen level dependent signal within an area and thus might show local changes before connectivity is affected. Hence, we investigated alterations of functional connectivity and MSE within the DMN in fifteen mild Alzheimer's disease patients as compared to fourteen controls. Potential associations of MSE with functional connectivity and cognitive abilities [i.e., mini-mental state examination (MMSE)] were assessed. A moderate decrease of DMN functional connectivity between posterior cingulate cortex and right hippocampus in Alzheimer's disease was found, whereas no differences were evident for whole-network functional connectivity. In contrast, the Alzheimer's disease group yielded lower global DMN-MSE than the control group. The most pronounced regional effects were localized in left and right hippocampi, and this was true for most scales. Moreover, MSE significantly correlated with functional connectivity, and DMN-MSE correlated positively with the MMSE in Alzheimer's disease. Most interestingly, the right hippocampal MSE was positively associated with semantic memory performance. Thus, our results suggested that cognitive decline in Alzheimer's disease is reflected by decreased signal complexity in DMN nodes, which might further lead to disrupted DMN functional connectivity. Additionally, altered entropy in Alzheimer's disease found in the majority of the scales indicated a disturbance of both local information processing and information transfer between distal areas. Conclusively, a loss of nodal signal complexity potentially impairs synchronization across nodes and thus preempts functional connectivity changes. MSE presents a putative functional marker for cognitive decline that might be more sensitive than functional connectivity alone.

Functional Disconnectivity during Inter-Task Resting State in Dementia with Lewy Bodies

AIMS

Limited research has been done on the functional connectivity in visuoperceptual regions in dementia with Lewy bodies (DLB) patients. This study aimed to investigate the functional connectivity differences between a task condition and an inter-task resting state condition within a visuoperceptual paradigm, in DLB patients compared with Alzheimer disease (AD) patients and healthy elderly control subjects.

METHODS

Twenty-six DLB, 29 AD, and 22 healthy subjects underwent a detailed clinical and neuropsychological examination along with a functional MRI during the different conditions of a visuoperceptual paradigm. Functional images were analyzed using group-level spatial independent component analysis and seed-based connectivity analyses.

RESULTS

While the DLB patients scored well and did not differ from the control and AD groups in terms of functional activity and connectivity during the task conditions, they showed decreased functional connectivity in visuoperceptual regions during the resting state condition, along with a temporal impairment of the default-mode network activity. Functional connectivity disturbances were also found within two attentional-executive networks and between these networks and visuoperceptual regions.

CONCLUSION

We found a specific functional profile in the switching between task and resting state conditions in DLB patients. This result could help better characterize functional impairments in DLB and their contribution to several core symptoms of this pathology such as visual hallucinations and cognitive fluctuations.

Correlates of nursing care burden among institutionalized patients with dementia

ABSTRACTBackground:The stress associated with care of patients with dementia has led to high nursing staff turnover. This study aims to explore patient factors that are related to nursing burden.

METHODS

The present study examined nursing care burden related to 55 institutionalized dementia patients using the Modified Nursing Care Assessment Scale (M-NCAS). Cognition was assessed with the Severe Impairment Battery (SIB), activities of daily living (ADLs) were measured with the Alzheimer's Disease Functional Assessment of Change Scale (ADFACS), aggression was measured with the Aggressive Behavior Scale (ABS), and the Charlson Comorbidity Index (CCI) was used to assess medical comorbidity. Finally, the Dementia Cognitive Fluctuation Scale (DCFS) was used to assess the presence and severity of cognitive fluctuations (CFs). Linear regression models were used to assess their relationships with nursing care burden.

RESULTS

The mean age of the patients was 90.41 years (SD=2.84) and 89.10% were males. ADFACS total score (B = 0.36, β = 0.42, p = 0.002) and ABS score (B = 2.933, β = 0.37, p = 0.002) significantly predicted the M-NCAS Attitude score. ABS score was the only significant predictor of M-NCAS Strain score (B = 2.57, β = 0.35, p = 0.009).

CONCLUSIONS

In the long-term care setting, aggressive behavior plays an important role in both subjective and objective nursing burden, while impaired ADLs increase the objective burden for nursing staff.

Technical note: can resting state functional MRI assist in routine clinical diagnosis?

Despite some differences in clinical presentation, it is often difficult to differentiate between dementia with Lewy bodies (DLB), clinical Alzheimer’s dementia (AD) and Parkinson’s disease dementia. However, differentiation can be crucial, especially as patients with DLB characteristically have a hypersensitivity to most antiemetic and neuroleptic drugs as they affect the cholinergic and dopaminergic system, potentially leading to life-threatening catatonia, loss of cognitive function and muscle rigidity. The aim of this study is to evaluate if resting state (RS) functional MRI (fMRI) can be used in routine practice on a 1.5 T scanner to differentiate between AD and DLB on an individual basis. We age- and gender-matched a known DLB patient with an AD patient and a human control (HC). Individual independent component analysis was carried out. Region of interest seeds were chosen from the midcingulate and insula regions. Functional connectivity from insula to midcingulate and within the midcingulate network (part of the Salience network) was lower in DLB than AD or HC. RS-fMRI on a 1.5 T scanner, in a routine clinical setting, detected abnormal functional connectivity patterns and allowed differentiation of DLB and AD in a routine clinical setting. This is the first evaluation of RS-fMRI in a routine clinical setting. It shows that incorporating RS-fMRI into the clinical scanning protocol can assist in early diagnosis and likely assist in monitoring the natural history of the disease or disease modifying treatments.

Neuroimaging in Lewy body dementia

Lewy body dementia (DLB) is a common form of cognitive impairment, accounting for 30% of dementia cases in ages over 65 years. Early diagnosis of DLB has been challenging; particularly in the context of differentiation with Parkinson’s disease dementia and other forms of dementias, such as Alzheimer’s disease and rapidly progressive dementias. Current practice involves the use of [¹²³I]FP-CIT-SPECT, [¹⁸F]FDG PET and [¹²³I]MIBG molecular imaging to support diagnostic procedures. Structural imaging techniques have an essential role for excluding structural causes, which could lead to a DLB-like phenotype, as well as aiding differential diagnosis through illustrating disease-specific patterns of atrophy. Novel PET molecular imaging modalities, such as amyloid and tau imaging, may provide further insights into DLB pathophysiology and may aid in early diagnosis. A multimodal approach, through combining various established techniques and possibly using novel radioligands, might further aid towards an in-depth understanding of this highly disabling disease. In this review, we will provide an overview of neuroimaging applications in patients with DLB.

Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?

Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.

The association between cognitive fluctuations and activities of daily living and quality of life among institutionalized patients with dementia

OBJECTIVE

Cognitive fluctuations (CFs) occur commonly in dementia of all types. While it is generally accepted that CFs can affect the clinical rating of dementia severity and neuropsychological performance, little is known about their impact on patients' activities of daily living (ADLs) and quality of life (QOL). Our study aims to explore the impact of CFs on ADLs and QOL among institutionalized patients with dementia.

METHODS

The present study examined the nature and frequency of CFs in 55 institutionalized dementia patients. We used the Dementia Cognitive Fluctuation Scale (DCFS) to assess the presence and severity of CFs. The Alzheimer's Disease Functional Assessment of Change Scale (ADFACS) was used to assess patients' ADLs, and the Quality of Life in Late Stage Dementia scale (QUALID) was used to assess QOL. Linear regression models were used to assess the relationships between CFs, ADLs, and QOL.

RESULTS

The mean age of the patients was 90.41 years (SD = 2.84). Their mean Aggressive Behavior Scale score was 1.13 (SD = 1.59), mean Severe Impairment Battery total score was 86.65 (SD = 13.77), and mean DCFS score was 10.07 (SD = 3.04). The mean ADFACS-ADL score was 10.88 (SD = 6.37), mean ADFACS-IADL score was 16.61 (SD = 9.54), and mean QUALID total score was 18.25 (SD = 5.70). DCFS significantly predicted ADFACS-ADL score (R²  = 0.39, β = 0.30, P = .011) although the relationship between ADFACS-IADL score and DCFS score was not significant (R²  = 0.16, P = .111). DCFS significantly predicted QUALID score (R²  = 0.08, β = 0.29, P = .033).

CONCLUSION

More severe CFs in patients with dementia were significantly associated with impaired ability to engage in ADLs and poorer QOL.

Functional connectivity in dementia with Lewy bodies: A within- and between-network analysis

Dementia with Lewy bodies (DLB) is a common form of dementia and is characterized by cognitive fluctuations, visual hallucinations, and Parkinsonism. The phenotypic expression of the disease may, in part, relate to alterations in functional connectivity within and between brain networks. This resting‐state study sought to clarify this in DLB, how networks differed from Alzheimer's disease (AD), and whether they were related to clinical symptoms in DLB. Resting‐state networks were estimated using independent component analysis. We investigated functional connectivity changes in 31 DLB patients compared to 31 healthy controls and a disease comparator group of 29 AD patients using dual regression and FSLNets. Within‐network connectivity was generally decreased in DLB compared to controls, mainly in motor, temporal, and frontal networks. Between‐network connectivity was mainly intact; only the connection between a frontal and a temporal network showed increased connectivity in DLB. Differences between AD and DLB were subtle and we did not find any significant correlations with the severity of clinical symptoms in DLB. This study emphasizes the importance of reduced connectivity within motor, frontal, and temporal networks in DLB with relative sparing of the default mode network. The lack of significant correlations between connectivity measures and clinical scores indicates that the observed reduced connectivity within these networks might be related to the presence, but not to the severity of motor and cognitive impairment in DLB patients. Furthermore, our results suggest that AD and DLB may show more similarities than differences in patients with mild disease.

Long reaction times are associated with delayed brain activity in lewy body dementia

A significant symptom of Lewy body dementia (LBD) is slow cognitive processing or bradyphrenia. In a previous fMRI task‐based study, we found slower responses in LBD, accompanied by greater deactivation in the default mode network. In this study, we investigated the timing and magnitude of the activations and deactivations with respect to reaction time to determine whether the slower responses in LBD were associated with delayed neuronal activity. Using fMRI, we examined the magnitude and latency of activations and deactivations during an event‐related attention task in 32 patients with LBD and 23 healthy controls using predefined regions of interest. Default mode network deactivations did not significantly differ in their timing between groups or task conditions, while the task‐related activations in the parietal, occipital, frontal, and motor cortex were all significantly later in the LBD group. Repeating the analysis with reaction time as a parametric modulator of activation magnitude produced similar findings, with the reaction time modulator being significant in a number of regions including the default mode network, suggesting that the increased deactivation in LBD is partly explained by slower task completion. Our data suggest that the default mode network deactivation is initiated at the start of the task, and remains deactivated until its end, with the increased magnitude of deactivation in LBD reflecting the more prolonged cognitive processing in these patients. These data add substantially to our understanding of the neural origins of bradyphrenia, which will be essential for determining optimum therapeutic strategies for cognitive impairment in LBD. Hum Brain Mapp 39:633–643, 2018. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Cognitive Fluctuations and Cognitive Test Performance Among Institutionalized Persons With Dementia

OBJECTIVE

To examine the nature and frequency of cognitive fluctuations (CFs) among institutionalized persons with dementia.

METHOD

A clinical interview and a medical chart review were conducted, and 55 patients were assigned a specific dementia diagnosis. The Severe Impairment Battery (SIB) was administered to assess cognitive function, and the Dementia Cognitive Fluctuation Scale (DCFS) was administered to each patient's primary nurse to determine the presence and severity of CFs.

RESULTS

A simple linear regression model was conducted with DCFS as the predictor variable and SIB total score as the dependent variable. The overall model was significant, suggesting that score on the DCFS significantly predicted SIB total score. Additionally, greater severity of CFs predicted poorer performance in the areas of orientation, language, and praxis.

CONCLUSIONS

Results suggest that CFs exert a clinically significant influence over patients' cognitive abilities and should be considered as a source of excess disability.

Can a Resting-State Functional Connectivity Index Identify Patients with Alzheimer's Disease and Mild Cognitive Impairment Across Multiple Sites?

Resting-state functional connectivity is one promising biomarker for Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, it is still not known how accurately network analysis identifies AD and MCI across multiple sites. In this study, we examined whether resting-state functional connectivity data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) could identify patients with AD and MCI at our site. We implemented an index based on the functional connectivity frequency distribution and compared performance for AD and MCI identification with multivoxel pattern analysis. The multivoxel pattern analysis using a connectivity map of the default mode network showed good performance, with an accuracy of 81.9% for AD and MCI identification within the ADNI, but the classification model obtained from the ADNI failed to classify AD, MCI, and healthy elderly adults from our site, with an accuracy of only 43.1%. In contrast, a functional connectivity index of the medial temporal lobe based on the frequency distribution showed moderate performance, with an accuracy of 76.5-80.3% for AD identification within the ADNI. The performance of this index was similar for our data, with an accuracy of 73.9-82.6%. The frequency distribution-based index of functional connectivity could be a good biomarker for AD across multiple sites.