Discovering Relations Between Mind, Brain, and Mental Disorders Using Topic Mapping
Publication Date
October 11, 2012
Journal
PLOS Computational Biology
Authors
Russell A. Poldrack, Jeanette A. Mumford, Tom Schonberg, Donald Kalar, et al
Volume
8
Issue
10
Pages
e1002707
DOI
https://dx.plos.org/10.1371/journal.pcbi.1002707
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1002707
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23071428
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3469446
Europe PMC
http://europepmc.org/abstract/MED/23071428
Web of Science
000310568800008
Scopus
84868141240
Mendeley
http://www.mendeley.com/research/discovering-relations-between-mind-brain-mental-disorders-using-topic-mapping
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/561068"], "description"=>"<p>The left panel shows the top words associated with each topic, and the right panel shows a map of voxels that were significantly associated with loading on that topic across documents. The image intensity is proportional to the Pearson correlation between the activation vector and the topic loading vector at each voxel (with red-yellow depicting positive correlations and blue-white depicting negative correlations), thresholded using a whole brain false discovery rate of q.01. The topics are shown in order of descending number of documents with nonzero loadings on the topic; those at the top showed loading on a relatively small number of documents, whereas those at the bottom showed loading across a broader set of documents. The images are presented in radiological convention (i.e., left-right reversed).</p>", "links"=>[], "tags"=>["topics"], "article_id"=>231562, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.g004", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Examples_of_mental_function_topics_and_associated_topic_maps_/231562", "title"=>"Examples of mental function topics and associated topic maps.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-11 00:26:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/561299"], "description"=>"<p>Topics are ordered in terms of the number of documents loading on the topic; color maps reflect the correlation coefficient between topic loading and activation across documents. The images are presented in radiological convention (i.e., left-right reversed).</p>", "links"=>[], "tags"=>["maps", "disorder-related"], "article_id"=>231789, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.g006", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Examples_of_topic_maps_based_on_a_topic_model_limited_to_disorder_related_terms_/231789", "title"=>"Examples of topic maps based on a topic model limited to disorder-related terms.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-11 00:29:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/561400"], "description"=>"<p>Euclidean distance was used as the distance metric for clustering, and hierarchical clustering was performed using Ward's method. The colored blocks show the four major groupings obtained by cutting the tree at a height of 2.0. Abbreviations: APH: aphasia, DLX:dyslexia, SLI: specific language impairment, DA: drug abuse, AD:Alzheimer's disease, DEP:depressive disorder, MDD:major depressive disorder, ANX:anxiety disorder, PAN: panic disorder, BPD: bipolar disorder, CD: conduct disorder, GAM: gambling, MD: mood disorder, PD: Parkinson's disease, OCD: obsessive compulsive disorder, PHO: phobia, EAT: eating disorder, SZ: schizophrenia, OBE: obesity, COC: cocaine related disorder, PSY: psychotic disorder, PAR: paranoid disorder, SZTY: schizotypal personality disorder, TIC: tic disorder, ALC: alcoholism, ALX: alexia, ADD: attention deficit disorder, AMN: amnesia, AUT: autism, ASP: Asperger syndrome.</p>", "links"=>[], "tags"=>["clustering", "denodrogram", "relationships", "topics", "neural", "activation"], "article_id"=>231889, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.g007", "stats"=>{"downloads"=>3, "page_views"=>33, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_clustering_denodrogram_showing_the_relationships_between_the_different_disorder_topics_based_on_their_distance_in_neural_activation_space_/231889", "title"=>"A clustering denodrogram showing the relationships between the different disorder topics based on their distance in neural activation space.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-11 00:31:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/561505"], "description"=>"<p>The top five topics for each canonical variate exceeding a loading value of 0.2 are shown in the table.</p>", "links"=>[], "tags"=>["variates", "sparse", "canonical", "neural", "activation"], "article_id"=>231989, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.t001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Canonical_variates_obtained_using_sparse_canonical_correlation_analysis_on_neural_activation_data_for_mental_concept_and_disorder_topics_/231989", "title"=>"Canonical variates obtained using sparse canonical correlation analysis on neural activation data for mental concept and disorder topics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-10-11 00:33:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/560984"], "description"=>"<p>Histograms of the number of topics per document (top row) and documents per topic (bottom row) for cognitive terms (left column) and disorder terms (right column).</p>", "links"=>[], "tags"=>["topics", "documents"], "article_id"=>231478, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.g003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Histograms_of_the_number_of_topics_per_document_top_row_and_documents_per_topic_bottom_row_for_cognitive_terms_left_column_and_disorder_terms_right_column_/231478", "title"=>"Histograms of the number of topics per document (top row) and documents per topic (bottom row) for cognitive terms (left column) and disorder terms (right column).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-11 00:24:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/560932"], "description"=>"<p>Plots of the average empirical likelihood of the left-out document sets across cross validation folds, for cognitive terms (left) and disorder terms (right).</p>", "links"=>[], "tags"=>["empirical", "left-out", "sets", "validation"], "article_id"=>231419, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.g002", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Plots_of_the_average_empirical_likelihood_of_the_left_out_document_sets_across_cross_validation_folds_for_cognitive_terms_left_and_disorder_terms_right_/231419", "title"=>"Plots of the average empirical likelihood of the left-out document sets across cross validation folds, for cognitive terms (left) and disorder terms (right).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-11 00:23:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/561538"], "description"=>"<p>The top five topics for each canonical variate exceeding a loading value of 0.2 are shown in the table.</p>", "links"=>[], "tags"=>["variates", "sparse", "canonical", "loading", "distributions"], "article_id"=>232030, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.t002", "stats"=>{"downloads"=>4, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Canonical_variates_obtained_using_sparse_canonical_correlation_analysis_directly_on_document_topic_loading_distributions_for_cognitive_and_disorder_topics_/232030", "title"=>"Canonical variates obtained using sparse canonical correlation analysis directly on document/topic loading distributions for cognitive and disorder topics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-10-11 00:33:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/561187"], "description"=>"<p>All topics with “language in their top 5 terms were first identified from the results for topic models fit to the data at 10, 50, 100, and 250 topics. At each level, each topic is linked to the topic at the previous level with which it had the highest correlation in its document loadings. The values on each edge reflect the correlation in the topic loading vector across documents between the two levels.</p>", "links"=>[], "tags"=>["hierarchical", "graph", "depicting", "topics", "involving"], "article_id"=>231678, "categories"=>["Information And Computing Sciences", "Neuroscience"], "users"=>["Russell A. Poldrack", "Jeanette A. Mumford", "Tom Schonberg", "Donald Kalar", "Bishal Barman", "Tal Yarkoni"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002707.g005", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_hierarchical_graph_depicting_topics_involving_the_term_8220_language_8221_across_multiple_topic_dimensionalities_/231678", "title"=>"A hierarchical graph depicting topics involving the term “language” across multiple topic dimensionalities.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-11 00:27:58"}

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Relative Metric

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