Alzheimer’s disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions.Although connections between changes in brain networks of Alzheimer’s disease patien...Alzheimer’s disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions.Although connections between changes in brain networks of Alzheimer’s disease patients have been established,the mechanisms that drive these alterations remain incompletely understood.This study,which was conducted in 2018 at Northeastern University in China,included data from 97 participants of the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset covering genetics,imaging,and clinical data.All participants were divided into two groups:normal control(n=52;20 males and 32 females;mean age 73.90±4.72 years)and Alzheimer’s disease(n=45,23 males and 22 females;mean age 74.85±5.66).To uncover the wiring mechanisms that shaped changes in the topology of human brain networks of Alzheimer’s disease patients,we proposed a local naive Bayes brain network model based on graph theory.Our results showed that the proposed model provided an excellent fit to observe networks in all properties examined,including clustering coefficient,modularity,characteristic path length,network efficiency,betweenness,and degree distribution compared with empirical methods.This proposed model simulated the wiring changes in human brain networks between controls and Alzheimer’s disease patients.Our results demonstrate its utility in understanding relationships between brain tissue structure and cognitive or behavioral functions.The ADNI was performed in accordance with the Good Clinical Practice guidelines,US 21 CFR Part 50-Protection of Human Subjects,and Part 56-Institutional Review Boards(IRBs)/Research Good Clinical Practice guidelines Institutional Review Boards(IRBs)/Research Ethics Boards(REBs).展开更多
Background:Different oscillations of brain networks could carry different dimensions of brain integration.We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson’s disease(PD)across ...Background:Different oscillations of brain networks could carry different dimensions of brain integration.We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson’s disease(PD)across early stage to middle stage by using graph theory-based analysis.Methods:Eighty-eight PD patients including 39 PD patients in the early stage(EPD)and 49 patients in the middle stage(MPD)and 36 controls were recruited in the present study.Graph theory-based network analyses from three oscillation frequencies(slow-5:0.01–0.027 Hz;slow-4:0.027–0.073 Hz;slow-3:0.073–0.198 Hz)were analyzed.Nodal metrics(e.g.nodal degree centrality,betweenness centrality and nodal efficiency)were calculated.Results:Our results showed that(1)a divergent effect of oscillation frequencies on nodal metrics,especially on nodal degree centrality and nodal efficiency,that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed,which visually showed that network was perturbed in PD;(2)PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities,which was consistently detected within all three oscillation frequencies;(3)the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients;(4)logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level;(5)occipital disruption within high frequency(slow-3)made a significant influence on motor impairment which was dominated by akinesia and rigidity.Conclusions:Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages.展开更多
基金Fundamental Research Funds for the Central Universities in China,No.N161608001 and No.N171903002
文摘Alzheimer’s disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions.Although connections between changes in brain networks of Alzheimer’s disease patients have been established,the mechanisms that drive these alterations remain incompletely understood.This study,which was conducted in 2018 at Northeastern University in China,included data from 97 participants of the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset covering genetics,imaging,and clinical data.All participants were divided into two groups:normal control(n=52;20 males and 32 females;mean age 73.90±4.72 years)and Alzheimer’s disease(n=45,23 males and 22 females;mean age 74.85±5.66).To uncover the wiring mechanisms that shaped changes in the topology of human brain networks of Alzheimer’s disease patients,we proposed a local naive Bayes brain network model based on graph theory.Our results showed that the proposed model provided an excellent fit to observe networks in all properties examined,including clustering coefficient,modularity,characteristic path length,network efficiency,betweenness,and degree distribution compared with empirical methods.This proposed model simulated the wiring changes in human brain networks between controls and Alzheimer’s disease patients.Our results demonstrate its utility in understanding relationships between brain tissue structure and cognitive or behavioral functions.The ADNI was performed in accordance with the Good Clinical Practice guidelines,US 21 CFR Part 50-Protection of Human Subjects,and Part 56-Institutional Review Boards(IRBs)/Research Good Clinical Practice guidelines Institutional Review Boards(IRBs)/Research Ethics Boards(REBs).
基金This work was supported by the 13th Five-year Plan for National Key Research and Development Program of China(Grant No.2016YFC1306600)the Fundamental Research Funds for the Central Universities of China(Grant No.2017XZZX001-01)+3 种基金the 12th Five-year Plan for National Science and Technology Supporting Program of China(Grant No.2012BAI10B04)the National Natural Science Foundation of China(Grant Nos.81571654,81371519 and 81701647)the Cooperative Project by Ministry of Health and Provincial Department(Grant No.2016149022)the Projects of Medical and Health Technology Development Program in Zhejiang Province(Grant No.2015KYB174).
文摘Background:Different oscillations of brain networks could carry different dimensions of brain integration.We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson’s disease(PD)across early stage to middle stage by using graph theory-based analysis.Methods:Eighty-eight PD patients including 39 PD patients in the early stage(EPD)and 49 patients in the middle stage(MPD)and 36 controls were recruited in the present study.Graph theory-based network analyses from three oscillation frequencies(slow-5:0.01–0.027 Hz;slow-4:0.027–0.073 Hz;slow-3:0.073–0.198 Hz)were analyzed.Nodal metrics(e.g.nodal degree centrality,betweenness centrality and nodal efficiency)were calculated.Results:Our results showed that(1)a divergent effect of oscillation frequencies on nodal metrics,especially on nodal degree centrality and nodal efficiency,that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed,which visually showed that network was perturbed in PD;(2)PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities,which was consistently detected within all three oscillation frequencies;(3)the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients;(4)logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level;(5)occipital disruption within high frequency(slow-3)made a significant influence on motor impairment which was dominated by akinesia and rigidity.Conclusions:Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages.
