Structural Interactions within the Default Mode Network Identified by Bayesian Network Analysis in Alzheimer’s Disease
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{"title"=>"Structural Interactions within the Default Mode Network Identified by Bayesian Network Analysis in Alzheimer's Disease", "type"=>"journal", "authors"=>[{"first_name"=>"Yan", "last_name"=>"Wang", "scopus_author_id"=>"55968303800"}, {"first_name"=>"Kewei", "last_name"=>"Chen", "scopus_author_id"=>"7410238086"}, {"first_name"=>"Li", "last_name"=>"Yao", "scopus_author_id"=>"7201688042"}, {"first_name"=>"Zhen", "last_name"=>"Jin", "scopus_author_id"=>"46961272300"}, {"first_name"=>"Xiaojuan", "last_name"=>"Guo", "scopus_author_id"=>"8647122500"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84883335603", "sgr"=>"84883335603", "issn"=>"19326203", "isbn"=>"1932-6203", "pmid"=>"24015315", "doi"=>"10.1371/journal.pone.0074070", "pui"=>"369732680"}, "id"=>"b87ec360-4075-3002-9cca-5e4e3e8d0e81", "abstract"=>"Alzheimer's disease (AD) is a well-known neurodegenerative disease that is associated with dramatic morphological abnormalities. The default mode network (DMN) is one of the most frequently studied resting-state networks. However, less is known about specific structural dependency or interactions among brain regions within the DMN in AD. In this study, we performed a Bayesian network (BN) analysis based on regional grey matter volumes to identify differences in structural interactions among core DMN regions in structural MRI data from 80 AD patients and 101 normal controls (NC). Compared to NC, the structural interactions between the medial prefrontal cortex (mPFC) and other brain regions, including the left inferior parietal cortex (IPC), the left inferior temporal cortex (ITC) and the right hippocampus (HP), were significantly reduced in the AD group. In addition, the AD group showed prominent increases in structural interactions from the left ITC to the left HP, the left HP to the right ITC, the right HP to the right ITC, and the right IPC to the posterior cingulate cortex (PCC). The BN models significantly distinguished AD patients from NC with 87.12% specificity and 81.25% sensitivity. We then used the derived BN models to examine the replicability and stability of AD-associated BN models in an independent dataset and the results indicated discriminability with 83.64% specificity and 80.49% sensitivity. The results revealed that the BN analysis was effective for characterising regional structure interactions and the AD-related BN models could be considered as valid and predictive structural brain biomarker models for AD. Therefore, our study can assist in further understanding the pathological mechanism of AD, based on the view of the structural network, and may provide new insights into classification and clinical application in the study of AD in the future.", "link"=>"http://www.mendeley.com/research/structural-interactions-within-default-mode-network-identified-bayesian-network-analysis-alzheimers", "reader_count"=>44, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>6, "Researcher"=>10, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>5, "Other"=>2, "Student > Master"=>6, "Student > Bachelor"=>4, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>6, "Researcher"=>10, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>5, "Other"=>2, "Student > Master"=>6, "Student > Bachelor"=>4, "Professor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>3, "Unspecified"=>1, "Biochemistry, Genetics and Molecular Biology"=>2, "Nursing and Health Professions"=>1, "Agricultural and Biological Sciences"=>5, "Medicine and Dentistry"=>7, "Neuroscience"=>12, "Psychology"=>7, "Social Sciences"=>2, "Computer Science"=>4}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>7}, "Neuroscience"=>{"Neuroscience"=>12}, "Social Sciences"=>{"Social Sciences"=>2}, "Psychology"=>{"Psychology"=>7}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>5}, "Computer Science"=>{"Computer Science"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"United States"=>2, "United Kingdom"=>2, "Slovenia"=>1}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1183755"], "description"=>"<p>Note: The left column, “NC>AD”, shows the probabilities of type-I error in the hypothesis that connections in NC group are greater than in the AD group. The right column, “AD>NC”, displays the opposite situation. The probabilities in bold indicate significantly greater connections (<i>p</i><0.05).</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "neuroanatomy", "neuroscience", "neural networks", "neuroimaging", "Population biology", "epidemiology", "Diagnostic medicine", "pathology", "Biomarker epidemiology", "neurology", "dementia", "Alzheimer disease", "radiology", "Diagnostic radiology", "Magnetic resonance imaging", "probabilities", "between-group"], "article_id"=>783312, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Yan Wang", "Kewei Chen", "Li Yao", "Zhen Jin", "Xiaojuan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0074070.t003", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Type_I_error_probabilities_of_the_between_group_connection_differences_/783312", "title"=>"Type-I error probabilities of the between-group connection differences.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-08-28 01:50:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1183753"], "description"=>"<p>The arrows represent dependency among brain regions and the thickness of the arrows represents the strength of the connections. The connections with asterisks are those that were significantly stronger for NC/AD than for AD/NC.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "neuroanatomy", "neuroscience", "neural networks", "neuroimaging", "Population biology", "epidemiology", "Diagnostic medicine", "pathology", "Biomarker epidemiology", "neurology", "dementia", "Alzheimer disease", "radiology", "Diagnostic radiology", "Magnetic resonance imaging", "dmn", "grey", "variations", "nc"], "article_id"=>783310, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Yan Wang", "Kewei Chen", "Li Yao", "Zhen Jin", "Xiaojuan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0074070.g001", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Bayesian_network_models_of_DMN_based_on_grey_matter_volume_variations_in_NC_left_panel_and_AD_right_panel_/783310", "title"=>"Bayesian network models of DMN based on grey matter volume variations in NC (left panel) and AD (right panel).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-28 01:50:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1183756"], "description"=>"<p>Eight ROIs in the DMN.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "neuroanatomy", "neuroscience", "neural networks", "neuroimaging", "Population biology", "epidemiology", "Diagnostic medicine", "pathology", "Biomarker epidemiology", "neurology", "dementia", "Alzheimer disease", "radiology", "Diagnostic radiology", "Magnetic resonance imaging", "rois"], "article_id"=>783313, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Yan Wang", "Kewei Chen", "Li Yao", "Zhen Jin", "Xiaojuan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0074070.t001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Eight_ROIs_in_the_DMN_/783313", "title"=>"Eight ROIs in the DMN.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-08-28 01:50:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1183754"], "description"=>"<p>Note: Part I of this table lists connections in both the AD and NC groups. Parts II and III list the connections present in only the NC or AD, respectively. Part IV lists connections with opposing direction for the two groups.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "neuroanatomy", "neuroscience", "neural networks", "neuroimaging", "Population biology", "epidemiology", "Diagnostic medicine", "pathology", "Biomarker epidemiology", "neurology", "dementia", "Alzheimer disease", "radiology", "Diagnostic radiology", "Magnetic resonance imaging", "connections", "corresponding", "coefficients", "bayesian", "nc"], "article_id"=>783311, "categories"=>["Medicine", "Biological Sciences"], "users"=>["Yan Wang", "Kewei Chen", "Li Yao", "Zhen Jin", "Xiaojuan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0074070.t002", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_List_of_connections_and_corresponding_weight_coefficients_in_the_Bayesian_network_models_of_the_NC_and_AD_groups_/783311", "title"=>"List of connections and corresponding weight coefficients in the Bayesian network models of the NC and AD groups.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-08-28 01:50:53"}

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Relative Metric

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