Altered spontaneous activity in Alzheimer's disease and mild cognitive impairment revealed by Regional Homogeneity

Zhang, Zengqiang; Liu, Yong; Jiang, Tianzi; Zhou, Bo; An, Ning; Dai, Haitao; Wang, Pan; Niu, Yixuan; Wang, Luning; Zhang, Xi

doi:10.1016/j.neuroimage.2011.08.049

Cited by 221 publications

(193 citation statements)

References 79 publications

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“…Portions of the fMRI data in the present study have been used in our previous studies of regional homogeneity [34] , and (4) Parkinsonian syndromes, epilepsy, or other nervous system diseases that can influence cognitive function.…”

Section: Participants and Methodsmentioning

confidence: 99%

Grey-matter volume as a potential feature for the classification of Alzheimer’s disease and mild cognitive impairment: an exploratory study

et al. 2014

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Specific patterns of brain atrophy may be helpful in the diagnosis of Alzheimer's disease (AD). In the present study, we set out to evaluate the utility of grey-matter volume in the classification of AD and amnestic mild cognitive impairment (aMCI) compared to normal control (NC) individuals. Voxel-based morphometric analyses were performed on structural MRIs from 35 AD patients, 27 aMCI patients, and 27 NC participants. A two-sample two-tailed t-test was computed between the NC and AD groups to create a map of abnormal grey matter in AD. The brain areas with signifi cant differences were extracted as regions of interest (ROIs), and the grey-matter volumes in the ROIs of the aMCI patients were included to evaluate the patterns of change across different disease severities. Next, correlation analyses between the grey-matter volumes in the ROIs and all clinical variables were performed in aMCI and AD patients to determine whether they varied with disease progression. The results revealed significantly decreased grey matter in the bilateral hippocampus/ parahippocampus, the bilateral superior/middle temporal gyri, and the right precuneus in AD patients.The grey-matter volumes were positively correlated with clinical variables. Finally, we performed exploratory linear discriminative analyses to assess the classifying capacity of grey-matter volumes in the bilateral hippocampus and parahippocampus among AD, aMCI, and NC. Leave-one-out crossvalidation analyses demonstrated that grey-matter volumes in hippocampus and parahippocampus accurately distinguished AD from NC. These fi ndings indicate that grey-matter volumes are useful in the classifi cation of AD.

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Section: Participants and Methodsmentioning

confidence: 99%

Grey-matter volume as a potential feature for the classification of Alzheimer’s disease and mild cognitive impairment: an exploratory study

et al. 2014

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“…First of all, we explored different brain functional networks by independent component analysis (ICA), considering the involvement of specific networks in FTD related to GRN [20]. More recently, a number of functional parameters has been used to study local properties of brain activity at rest, also in FTD related to GRN, like regional homogeneity (ReHo), to look at the coherence of focal resting state fluctuations [21], the fractional amplitude of low frequency fluctuation (fALFF, that describes the power of the signal in the low frequency range) [22], degree centrality (DC, that allows the study of the nodes that form the whole-brain network [23]), and the voxel homotopic connectivity (VMHC, as index of functional symmetry in resting-state brain activity) [24]. In the present work we have taken advantage of the multivariate approach as machine-learning classifier of MVPA: 1) to identify the most accurate functional and/or structural neuroimaging index to be used, and 2) to define the most accurate neuroimaging pattern to classify the different stages of the GRN disease.…”

Section: Introductionmentioning

confidence: 99%

Looking for Neuroimaging Markers in Frontotemporal Lobar Degeneration Clinical Trials: A Multi-Voxel Pattern Analysis Study in Granulin Disease

Premi

Cauda

Costa

et al. 2016

JAD

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Abstract. In light of future pharmacological interventions, neuroimaging markers able to assess the response to treatment would be crucial. In Granulin (GRN) disease, preclinical data will prompt pharmacological trials in the future. Two main points need to be assessed: 1) to identify target regions in different disease stages and 2) to determine the most accurate functional and structural neuroimaging index to be used. To this aim, we have taken advantage of the multivariate approach of multi-voxel pattern analysis (MVPA) to explore the information of brain activity patterns in a cohort of GRN Thr272fs carriers at different disease stages (14 frontotemporal dementia (FTD) patients and 17 asymptomatic carriers) and a group of 33 healthy controls. We studied structural changes by voxel-based morphometry (VBM), functional connectivity by assessing salience, default mode, fronto-parietal, dorsal attentional, executive networks, and local connectivity by regional homogeneity, amplitude of low frequency fluctuations (ALFF), fractional ALFF (fALFF), degree centrality, and voxel-mirrored homotopic connectivity. In FTD patients with GRN mutation, the most predictive measure was VBM structural analysis, while in asymptomatic carriers the best predictor marker was the local connectivity measure (fALFF). Altogether, all indexes demonstrated fronto-temporoparietal damage in GRN pathology, with widespread structural damage of fronto-parietal and temporal regions when disease is overt. MVPA could be of aid in identifying the most accurate neuroimaging marker for clinical trials. This approach was able to identify both the target region and the best neuroimaging approach, which would be specific in the different disease stages. Further studies are needed to simultaneously integrate multimodal indexes in a classifier able to trace the disease progression moving from preclinical to clinical stage of the disease.

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“…Findings from our research group and other studies suggest that brain regions with altered ReHo in patients with aMCI are located in structures associated with the EM [3,19,41,56] and EF [4,6,37,57] networks and include regions such as the hippocampus, PCC/precuneus (PCu), right inferior parietal lobule (IPL), DLPFC, and ventromedial prefrontal cortex (VMPFC) [58][59][60][61]. Therefore, the present study computed ReHo values to identify regions with abnormal local connectivity in a group of aMCI patients relative to healthy controls (HC).…”

Section: Introductionmentioning

confidence: 60%

IC‐P‐034: Mediation of Episodic Memory Performance by The Executive Function Network in Patients with Amnestic Mild Cognitive Impairment: A Resting‐State Functional MRI Study

Yuan

Xie

Zhang

2016

Alzheimer's & Dementia

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Deficits in episodic memory (EM) are a hallmark clinical symptom of patients with amnestic mild cognitive impairment (aMCI). Impairments in executive function (EF) are widely considered to exacerbate memory deficits and to increase the risk of conversion from aMCI to Alzheimer's disease (AD). However, the specific mechanisms underlying the interaction between executive dysfunction and memory deficits in aMCI patients remain unclear. Thus, the present study utilized resting-state functional magnetic resonance imaging (fMRI) scans of the EF network and the EM network to investigate this relationship in 79 aMCI patients and 119 healthy controls (HC). The seeds were obtained from the results of a regional homogeneity (ReHo) analysis. Functional connectivity (FC) within the EM network was determined using a seed in the right retrosplenial cortex (RSC), and FC within EF network was assessed using seeds in the right dorsolateral prefrontal cortex (DLPFC). There was a significant negative correlation between EM scores and EF scores in both the aMCI and HC groups. Compared to the HC group, aMCI patients had reduced right RSC connectivity but enhanced right DLPFC connectivity. The overlapping brain regions between the EM and EF networks were associated with FC in the right inferior parietal lobule (IPL) in the right RSC network, and in the bilateral middle cingulate cortex (MCC) and left IPL in the right DLPFC network. A mediation analysis revealed that the EF network had an indirect positive effect on EM performance in the aMCI patients. The present findings provide new insights into the neural mechanisms underlying the interaction between impaired EF and memory deficits in aMCI patients and suggest that the EF network may mediate EM performance in this population.

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Altered spontaneous activity in Alzheimer's disease and mild cognitive impairment revealed by Regional Homogeneity

Cited by 221 publications

References 79 publications

Grey-matter volume as a potential feature for the classification of Alzheimer’s disease and mild cognitive impairment: an exploratory study

Grey-matter volume as a potential feature for the classification of Alzheimer’s disease and mild cognitive impairment: an exploratory study

Looking for Neuroimaging Markers in Frontotemporal Lobar Degeneration Clinical Trials: A Multi-Voxel Pattern Analysis Study in Granulin Disease

IC‐P‐034: Mediation of Episodic Memory Performance by The Executive Function Network in Patients with Amnestic Mild Cognitive Impairment: A Resting‐State Functional MRI Study

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