Functional connectivity in mild cognitive impairment with Lewy bodies

Resting-State Functional MRI Approaches to Parkinsonisms and Related Dementia

PURPOSE OF THE REVIEW

In this review, we attempt to summarize the most updated studies that applied resting-state functional magnetic resonance imaging (rs-fMRI) in the field of Parkinsonisms and related dementia.

RECENT FINDINGS

Over the past decades, increasing interest has emerged on investigating the presence and pathophysiology of cognitive symptoms in Parkinsonisms and their possible role as predictive biomarkers of neurodegenerative brain processes. In recent years, evidence has been provided, applying mainly three methodological approaches (i.e. seed-based, network-based and graph-analysis) on rs-fMRI data, with promising results. Neural correlates of cognitive impairment and dementia have been detected in patients with Parkinsonisms along the diseases course. Interestingly, early functional connectivity signatures were proposed to track and predict future progression of neurodegenerative processes. However, longitudinal studies are still sparce and further investigations are needed to overcome this knowledge gap.

Posterior default mode network is associated with the social performance in male children with autism spectrum disorder: A dynamic causal modeling analysis based on triple-network model

The triple-network model has been widely applied in neuropsychiatric disorders including autism spectrum disorder (ASD). However, the mechanism of causal regulations within the triple-network and their relations with symptoms of ASD remains unclear. 81 male ASD and 80 well matched typically developing control (TDC) were included in this study, recruited from Autism Brain Image Data Exchange-I datasets. Spatial reference-based independent component analysis was used to identify the anterior and posterior part of default-mode network (aDMN and pDMN), salience network (SN), and bilateral executive-control network (ECN) from resting-state functional magnetic resonance imaging data. Spectral dynamic causal model and parametric empirical Bayes with Bayesian model reduction/average were adopted to explore the effective connectivity (EC) within triple-network and the relationship between EC and autism diagnostic observation schedule (ADOS) scores. After adjusting for age and site effect, ASD and TDC groups both showed inhibition patterns. Compared with TDC, ASD group showed weaker self-inhibition in aDMN and pDMN, stronger inhibition in pDMN→aDMN, weaker inhibition in aDMN→LECN, pDMN→SN, LECN→SN, and LECN→RECN. Furthermore, negative relationships between ADOS scores and pDMN self-inhibition strength, as well as with the EC of pDMN→aDMN were observed in ASD group. The present study reveals imbalanced effective connections within triple-networks in ASD children. More attentions should be focused at the pDMN, which modulates the core symptoms of ASD and may serve as an important region for ASD diagnosis and the target region for ASD treatments.

Striato-cortical functional connectivity changes in mild cognitive impairment with Lewy bodies

BACKGROUND

Functional connectivity changes in clinically overt neurodegenerative diseases such as dementia with Lewy bodies have been described, but studies on connectivity changes in the pre-dementia phase are scarce.

OBJECTIVES

We concentrated on evaluating striato-cortical functional connectivity differences between patients with Mild Cognitive Impairment with Lewy bodies and healthy controls and on assessing the relation to cognition.

METHODS

Altogether, we enrolled 77 participants (47 patients, of which 35 met all the inclusion criteria for the final analysis, and 30 age- and gender-matched healthy controls, of which 28 met all the inclusion criteria for the final analysis) to study the seed-based connectivity of the dorsal, middle, and ventral striatum. We assessed correlations between functional connectivity in the regions of between-group differences and neuropsychological scores of interest (visuospatial and executive domains z-scores).

RESULTS

Subjects with Mild Cognitive Impairment with Lewy Bodies, as compared to healthy controls, showed increased connectivity from the dorsal part of the striatum particularly to the bilateral anterior part of the temporal cortex with an association with executive functions.

CONCLUSIONS

We were able to capture early abnormal connectivity within cholinergic and noradrenergic pathways that correlated with cognitive functions known to be linked to cholinergic/noradrenergic deficits. The knowledge of specific alterations may improve our understanding of early neural changes in pre-dementia stages and enhance research of disease modifying therapy.

Effective hyper-connectivity network construction and learning: Application to major depressive disorder identification

Functional connectivity (FC) derived from resting-state fMRI (rs-fMRI) is a primary approach for identifying brain diseases, but it is limited to capturing the pairwise correlation between regions-of-interest (ROIs) in the brain. Thus, hyper-connectivity which describes the higher-order relationship among multiple ROIs is receiving increasing attention. However, most hyper-connectivity methods overlook the directionality of connections. The direction of information flow constitutes a pivotal factor in shaping brain activity and cognitive processes. Neglecting this directional aspect can lead to an incomplete understanding of high-order interactions within the brain. To this end, we propose a novel effective hyper-connectivity (EHC) network that integrates direction detection and hyper-connectivity modeling. It characterizes the high-order directional information flow among multiple ROIs, providing a more comprehensive understanding of brain activity. Then, we develop a directed hypergraph convolutional network (DHGCN) to acquire deep representations from EHC network and functional indicators of ROIs. In contrast to conventional hypergraph convolutional networks designed for undirected hypergraphs, DHGCN is specifically tailored to handle directed hypergraph data structures. Moreover, unlike existing methods that primarily focus on fMRI time series, our proposed DHGCN model also incorporates multiple functional indicators, providing a robust framework for feature learning. Finally, deep representations generated via DHGCN, combined with demographic factors, are used for major depressive disorder (MDD) identification. Experimental results demonstrate that the proposed framework outperforms both FC and undirected hyper-connectivity models, as well as surpassing other state-of-the-art methods. The identification of EHC abnormalities through our framework can enhance the analysis of brain function in individuals with MDD.

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.

Research diagnostic criteria for mild cognitive impairment with Lewy bodies: A systematic review and meta-analysis

INTRODUCTION

Operationalized research criteria for mild cognitive impairment with Lewy bodies (MCI-LB) were published in 2020. The aim of this systematic review and meta-analysis was to review the evidence for the diagnostic clinical features and biomarkers in MCI-LB set out in the criteria.

METHODS

MEDLINE, PubMed, and Embase were searched on 9/28/22 for relevant articles. Articles were included if they presented original data reporting the rates of diagnostic features in MCI-LB.

RESULTS

Fifty-seven articles were included. The meta-analysis supported the inclusion of the current clinical features in the diagnostic criteria. Evidence for striatal dopaminergic imaging and meta-iodobenzylguanidine cardiac scintigraphy, though limited, supports their inclusion. Quantitative electroencephalogram (EEG) and fluorodeoxyglucose positron emission tomography (PET) show promise as diagnostic biomarkers.

DISCUSSION

The available evidence largely supports the current diagnostic criteria for MCI-LB. Further evidence will help refine the diagnostic criteria and understand how best to apply them in clinical practice and research.

HIGHLIGHTS

A meta-analysis of the diagnostic features of MCI-LB was carried out. The four core clinical features were more common in MCI-LB than MCI-AD/stable MCI. Neuropsychiatric and autonomic features were also more common in MCI-LB. More evidence is needed for the proposed biomarkers. FDG-PET and quantitative EEG show promise as diagnostic biomarkers in MCI-LB.

(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.

Neuroscience robotics for controlled induction and real-time assessment of hallucinations

Although hallucinations are important and frequent symptoms in major psychiatric and neurological diseases, little is known about their brain mechanisms. Hallucinations are unpredictable and private experiences, making their investigation, quantification and assessment highly challenging. A major shortcoming in hallucination research is the absence of methods able to induce specific and short-lasting hallucinations, which resemble clinical hallucinations, can be elicited repeatedly and vary across experimental conditions. By integrating clinical observations and recent advances in cognitive neuroscience with robotics, we have designed a novel device and sensorimotor method able to repeatedly induce a specific, clinically relevant hallucination: presence hallucination. Presence hallucinations are induced by applying specific conflicting (spatiotemporal) sensorimotor stimulation including an upper extremity and the torso of the participant. Another, MRI-compatible, robotic device using similar sensorimotor stimulation permitted the identification of the brain mechanisms of these hallucinations. Enabling the identification of behavioral and a frontotemporal neural biomarkers of hallucinations, under fully controlled experimental conditions and in real-time, this method can be applied in healthy participants as well as patients with schizophrenia, neurodegenerative disease or other hallucinations. The execution of these protocols requires intermediate-level skills in cognitive neuroscience and MRI processing, as well as minimal coding experience to control the robotic device. These protocols take ~3 h to be completed.

Exploring the Recent Trends in Management of Dementia and Frailty: Focus on Diagnosis and Treatment

Dementia and frailty increase health adversities in older adults, which are topics of growing research interest. Frailty is considered to correspond to a biological syndrome associated with age. Frail patients may ultimately develop multiple dysfunctions across several systems, including stroke, transient ischemic attack, vascular dementia, Parkinson's disease, Alzheimer's disease, frontotemporal dementia, dementia with Lewy bodies, cortico-basal degeneration, multiple system atrophy, amyotrophic lateral sclerosis, and Creutzfeldt-Jakob disease. Patients with dementia and frailty often develop malnutrition and weight loss. Rigorous nutritional, pharmacological, and non-pharmacological interventions generally are required for these patients, which is a challenging issue for healthcare providers. A healthy diet and lifestyle instigated at an early age can reduce the risk of frailty and dementia. For optimal treatment, accurate diagnosis involving clinical evaluation, cognitive screening, essential laboratory evaluation, structural imaging, functional neuroimaging, and neuropsychological testing is necessary. Diagnosis procedures best apply the clinical diagnosis, identifying the cause(s) and the condition(s) appropriate for treatment. The patient's history, caregiver's interview, physical examination, cognitive evaluation, laboratory tests, and structural imaging should best be involved in the diagnostic process. Varying types of physical exercise can aid the treatment of these disorders. Nutrition maintenance is a particularly significant factor, such as exceptionally high-calorie dietary supplements and a Mediterranean diet to support weight gain. The core purpose of this article is to investigate trends in the management of dementia and frailty, focusing on improving diagnosis and treatment. Substantial evidence builds the consensus that a combination of balanced nutrition and good physical activity is an integral part of treatment. Notably, more evidence-based medicine knowledge is required.

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.

Temporal stability of the ventral attention network and general cognition along the Alzheimer's disease spectrum

Understanding the interrelationships of clinical manifestations of Alzheimer's disease (AD) and functional connectivity (FC) as the disease progresses is necessary for use of FC as a potential neuroimaging biomarker. Degradation of resting-state networks in AD has been observed when FC is estimated over the entire scan, however, the temporal dynamics of these networks are less studied. We implemented a novel approach to investigate the modular structure of static (sFC) and time-varying (tvFC) connectivity along the AD spectrum in a two-sample Discovery/Validation design (n = 80 and 81, respectively). Cortical FC networks were estimated across 4 diagnostic groups (cognitively normal, subjective cognitive decline, mild cognitive impairment, and AD) for whole scan (sFC) and with sliding window correlation (tvFC). Modularity quality (across a range of spatial scales) did not differ in either sFC or tvFC. For tvFC, group differences in temporal stability within and between multiple resting state networks were observed; however, these differences were not consistent between samples. Correlation analyses identified a relationship between global cognition and temporal stability of the ventral attention network, which was reproduced in both samples. While the ventral attention system has been predominantly studied in task-evoked designs, the relationship between its intrinsic dynamics at-rest and general cognition along the AD spectrum highlights its relevance regarding clinical manifestation of the disease.