scholarly journals Using Regional Homogeneity to Reveal Altered Spontaneous Activity in Patients with Mild Cognitive Impairment

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yumei Wang ◽  
Xiaochuan Zhao ◽  
Shunjiang Xu ◽  
Lulu Yu ◽  
Lan Wang ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Spontaneous Activity ◽  
Healthy Aging ◽  
Early Stage ◽  
Brain Activity ◽  
Regional Homogeneity ◽  
Whole Brain ◽  
Spontaneous Brain Activity ◽  
Regional Brain Activity

Most patients with mild cognitive impairment (MCI) are thought to be in an early stage of Alzheimer’s disease (AD). Resting-state functional magnetic resonance imaging reflects spontaneous brain activity and/or the endogenous/background neurophysiological process of the human brain. Regional homogeneity (ReHo) rapidly maps regional brain activity across the whole brain. In the present study, we used the ReHo index to explore whole brain spontaneous activity pattern in MCI. Our results showed that MCI subjects displayed an increased ReHo index in the paracentral lobe, precuneus, and postcentral and a decreased ReHo index in the medial temporal gyrus and hippocampus. Impairments in the medial temporal gyrus and hippocampus may serve as important markers distinguishing MCI from healthy aging. Moreover, the increased ReHo index observed in the postcentral and paracentral lobes might indicate compensation for the cognitive function losses in individuals with MCI.

scholarly journals Repeated anodal high-definition transcranial direct current stimulation over the left dorsolateral prefrontal cortex in mild cognitive impairment patients increased regional homogeneity in multiple brain regions

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256100
Author(s):  
Fangmei He ◽  
Youjun Li ◽  
Chenxi Li ◽  
Liming Fan ◽  
Tian Liu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Function ◽  
Dorsolateral Prefrontal Cortex ◽  
Brain Activity ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
High Definition ◽  
Spontaneous Brain Activity ◽  
Dorsolateral Prefrontal

Transcranial direct current stimulation (tDCS) can improve cognitive function. However, it is not clear how high-definition tDCS (HD-tDCS) regulates the cognitive function and its neural mechanism, especially in individuals with mild cognitive impairment (MCI). This study aimed to examine whether HD-tDCS can modulate cognitive function in individuals with MCI and to determine whether the potential variety is related to spontaneous brain activity changes recorded by resting-state functional magnetic resonance imaging (rs-fMRI). Forty-three individuals with MCI were randomly assigned to receive either 10 HD-tDCS sessions or 10 sham sessions to the left dorsolateral prefrontal cortex (L-DLPFC). The fractional amplitude of low-frequency fluctuation (fALFF) and the regional homogeneity (ReHo) was computed using rs-fMRI data from all participants. The results showed that the fALFF and ReHo values changed in multiple areas following HD-tDCS. Brain regions with significant decreases in fALFF values include the Insula R, Precuneus R, Thalamus L, and Parietal Sup R, while the Temporal Inf R, Fusiform L, Occipital Sup L, Calcarine R, and Angular R showed significantly increased in their fALFF values. The brain regions with significant increases in ReHo values include the Temporal Inf R, Putamen L, Frontal Mid L, Precentral R, Frontal Sup Medial L, Frontal Sup R, and Precentral L. We found that HD-tDCS can alter the intensity and synchrony of brain activity, and our results indicate that fALFF and ReHo analysis are sensitive indicators for the detection of HD-tDCS during spontaneous brain activity. Interestingly, HD-tDCS increases the ReHo values of multiple brain regions, which may be related to the underlying mechanism of its clinical effects, these may also be related to a potential compensation mechanism involving the mobilization of more regions to complete a function following a functional decline.

scholarly journals Aggregation of Vascular Risk Factors Modulates the Amplitude of Low-Frequency Fluctuation in Mild Cognitive Impairment Patients

2020 ◽  
Vol 12 ◽  
Author(s):  
Liying Zhuang ◽  
Huafu Ni ◽  
Junyang Wang ◽  
Xiaoyan Liu ◽  
Yajie Lin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Activity ◽  
Low Frequency ◽  
Vascular Risk Factors ◽  
Vascular Risk ◽  
Cvd Risk ◽  
Spontaneous Brain Activity ◽  
Main Effect

Background: Several vascular risk factors, including hypertension, diabetes, body mass index, and smoking status are found to be associated with cognitive decline and the risk of Alzheimer's disease (AD). We aimed to investigate whether an aggregation of vascular risk factors modulates the amplitude of low-frequency fluctuation (ALFF) in patients with mild cognitive impairment (MCI).Methods: Forty-three MCI patients and twenty-nine healthy controls (HCs) underwent resting-state functional MRI scans, and spontaneous brain activity was measured by the ALFF technique. The vascular risk profile was represented with the Framingham Heart Study general cardiovascular disease (FHS-CVD) risk score, and each group was further divided into high and low risk subgroups. Two-way ANOVA was performed to explore the main effects of diagnosis and vascular risk and their interaction on ALFF.Results: The main effect of diagnosis on ALFF was found in left middle temporal gyrus (LMTG) and left superior parietal gyrus (LSPG), and the main effect of risk on ALFF was detected in left fusiform gyrus (LFFG), left precuneus (LPCUN), and left cerebellum posterior lobe (LCPL). Patients with MCI exhibited increased ALFF in the LMTG and LSPG than HCs, and participants with high vascular risk showed increased ALFF in the LFFG and LCPL, while decreased ALFF in the LPCUN. An interaction between diagnosis (MCI vs. HC) and FHS-CVD risk (high vs. low) regarding ALFF was observed in the left hippocampus (LHIP). HCs with high vascular risk showed significantly increased ALFF in the LHIP than those with low vascular risk, while MCI patients with high vascular risk showed decreased ALFF in the LHIP than HCs with high vascular risk. Interestingly, the mean ALFF of LHIP positively correlated with word recall test in HCs with high vascular risk (rho = 0.630, P = 0.016), while negatively correlated with the same test in MCI patients with high vascular risk (rho = −0.607, P = 0.001).Conclusions: This study provides preliminary evidence highlighting that the aggregation of vascular risk factors modulates the spontaneous brain activity in MCI patients, and this may serve as a potential imaging mechanism underlying vascular contribution to AD.

scholarly journals Effects of Smoking on Regional Homogeneity in Mild Cognitive Impairment: A Resting-State Functional MRI Study

2020 ◽  
Vol 12 ◽  
Author(s):  
Tianyi Zhang ◽  
Xiao Luo ◽  
Qingze Zeng ◽  
Yanv Fu ◽  
Zheyu Li ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Functional Mri ◽  
Resting State ◽  
Brain Activity ◽  
Verbal Learning ◽  
Regional Homogeneity ◽  
Angular Gyrus ◽  
Healthy Elderly ◽  
Intrinsic Brain Activity

BackgroundSmoking is a modifiable risk factor for Alzheimer’s disease (AD). However, smoking-related effects on intrinsic brain activity in high-risk AD population are still unclear.ObjectiveWe aimed to explore differences in smoking effects on brain function between healthy elderly and amnestic mild cognitive impairment (aMCI) patients using ReHo mapping.MethodsWe identified 64 healthy elderly controls and 116 aMCI patients, including 98 non-smoking and 18 smoking aMCI. Each subject underwent structural and resting-state functional MRI scanning and neuropsychological evaluations. Regional homogeneity (ReHo) mapping was used to assess regional brain synchronization. After correction for age, gender, education, and gray matter volume, we explored the difference of ReHo among groups in a voxel-wise way based on analysis of covariance (ANCOVA), followed by post hoc two-sample analyses (p < 0.05, corrected). Further, we correlated the mean ReHo with neuropsychological scales.ResultsThree groups were well-matched in age, gender, and education. Significant ReHo differences were found among three groups, located in the left supramarginal gyrus (SMG) and left angular gyrus (AG). Specifically, non-smoking aMCI had lower ReHo in SMG and AG than smoking aMCI and controls. By contrast, smoking aMCI had greater AG ReHo than healthy controls (p < 0.05). Across groups, correlation analyses showed that left AG ReHo correlated with MMSE (r = 0.18, p = 0.015), clock drawing test (r = 0.20, p = 0.007), immediate recall (r = 0.36, p < 0.001), delayed recall (r = 0.34, p < 0.001), and auditory verbal learning test (r = 0.20, p = 0.007).ConclusionSmoking might pose compensatory or protective effects on intrinsic brain activity in aMCI patients.

scholarly journals Altered regional homogeneity and functional brain networks in Type 2 diabetes with and without mild cognitive impairment

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ying Xiong ◽  
Xiaodan Chen ◽  
Xu Zhao ◽  
Yang Fan ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Activity ◽  
Regional Homogeneity ◽  
Clustering Coefficient ◽  
Inferior Temporal Gyrus ◽  
Network Analyses ◽  
Initial Symptoms

AbstractPatients with Type-2 Diabetes Mellitus (T2DM) have a considerably higher risk of developing mild cognitive impairment (MCI) and dementia. The initial symptoms are very insidious at onset. We investigated the alterations in spontaneous brain activity and network connectivity through regional homogeneity (ReHo) and graph theoretical network analyses, respectively, of resting-state functional Magnetic Resonance Imaging (rs-fMRI) in T2DM patients with and without MCI, so as to facilitate early diagnose. Twenty-five T2DM patients with MCI (DM-MCI), 25 T2DM patients with normal cognition (DM-NC), 27 healthy controls were enrolled. Whole-brain ReHo values were calculated and topological properties of functional networks were analyzed. The DM-MCI group exhibited decreased ReHo in the left inferior/middle occipital gyrus and right inferior temporal gyrus, and increased ReHo in frontal gyrus compared to the DM-NCs. Significant correlations were found between ReHo values and clinical measurements. The DM-MCI group illustrated greater clustering coefficient/local efficiency and altered nodal characteristics (efficiency, degree and betweenness), which increased in certain occipital, temporal and parietal regions but decreased in the right inferior temporal gyrus, compared to the DM-NCs. The altered ReHo and impaired network organization may underlie the impaired cognitive functions in T2DM and suggesting a compensation mechanism. These rs-fMRI measures have the potential as biomarkers of disease progression in diabetic encephalopathy.

scholarly journals An explainable self-attention deep neural network for detecting mild cognitive impairment using multi-inputbdigital drawing tasks

2021 ◽  
Author(s):  
Natthanan Ruengchaijatuporn ◽  
Itthi Chatnuntawech ◽  
Surat Teerapittayanon ◽  
Sira Sriswasdi ◽  
Sirawaj Itthipuripat ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Healthy Aging ◽  
Neurodegenerative Disorder ◽  
Early Stage ◽  
Aging Population ◽  
Modeling Framework ◽  
Drawing Tasks

Mild cognitive impairment (MCI) is an early stage of age-inappropriate cognitive decline, which could develop into dementia – an untreatable neurodegenerative disorder. An early detection of MCI is a crucial step for timely prevention and intervention. To tackle this problem, recent studies have developed deep learning models to detect MCI and various types of dementia using data obtained from the classic clock-drawing test (CDT), a popular neuropsychological screening tool that can be easily and rapidly implemented for assessing cognitive impairments in an aging population. While these models succeed at distinguishing severe forms of dementia, it is still difficult to predict the early stage of the disease using the CDT data alone. Also, the state-of-the-art deep learning techniques still face the black-box challenges, making it questionable to implement them in the clinical setting. Here, we propose a novel deep learning modeling framework that incorporates data from multiple drawing tasks including the CDT, cube-copying, and trail-making tasks obtained from a digital platform. Using self-attention and soft-label methods, our model achieves much higher classification performance at detecting MCI compared to those of a well-established convolutional neural network model. Moreover, our model can highlight features of the MCI data that considerably deviate from those of the healthy aging population, offering accurate predictions for detecting MCI along with visual explanation that aids the interpretation of the deep learning model.

scholarly journals Differentiated Regional Homogeneity in Progressive Mild Cognitive Impairment: A Study With Post Hoc Label

2018 ◽  
Vol 33 (6) ◽  
pp. 373-384 ◽  
Author(s):  
Suping Cai ◽  
Yubo Wang ◽  
Yafei Kang ◽  
Haidong Wang ◽  
Hyejin Kim ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Parietal Lobe ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Superior Temporal Gyrus ◽  
Regional Homogeneity ◽  
Specific Patient ◽  
Post Hoc ◽  
Cognitively Intact

Purpose: Mild cognitive impairment (MCI) is considered to be the clinical transition stage between patients with cognitively intact geriatrics and Alzheimer’s disease (AD). When observed longitudinally, however, a certain proportion of patients with MCI are expected to revert to a cognitively intact state (MCI_R) while others either remain in the MCI state (MCI_S) or deteriorate into AD (MCI_P). It is worthwhile to investigate the divergence in the brain activities of these MCI groups with different post hoc labels. Methods: In this study, we employed the regional homogeneity (ReHo) measure to explore the characteristics of local brain activity in these MCI groups. Results: Compared to age-matched normal controls, our results exhibited that (1) in MCI_R group, ReHo index showed an increase in the left insula and a decrease in the left superior temporal gyrus; (2) in MCI_S group, ReHo index increased in the left orbital part of the inferior frontal gyrus (IFG_orb) and decreased in the left inferior parietal lobe; and (3) in MCI_P group, ReHo index elevated in the left IFG_orb and decreased in the left putamen. Conclusions: The distinct ReHo changes in the individual MCI groups indicated a potential evidence for differentially active interventions for a specific patient with MCI.

Complexity Analysis of Spontaneous Brain Activity in Alzheimer Disease and Mild Cognitive Impairment

2010 ◽  
Vol 24 (2) ◽  
pp. 182-189 ◽  
Author(s):  
Alberto Fernández ◽  
Roberto Hornero ◽  
Carlos Gómez ◽  
Agustín Turrero ◽  
Pedro Gil-Gregorio ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Alzheimer Disease ◽  
Complexity Analysis ◽  
Brain Activity ◽  
Spontaneous Brain Activity
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