Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence
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{"title"=>"Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence", "type"=>"journal", "authors"=>[{"first_name"=>"Kai", "last_name"=>"Wu", "scopus_author_id"=>"36160728800"}, {"first_name"=>"Yasuyuki", "last_name"=>"Taki", "scopus_author_id"=>"35729609800"}, {"first_name"=>"Kazunori", "last_name"=>"Sato", "scopus_author_id"=>"7406412389"}, {"first_name"=>"Hiroshi", "last_name"=>"Hashizume", "scopus_author_id"=>"35728592500"}, {"first_name"=>"Yuko", "last_name"=>"Sassa", "scopus_author_id"=>"8386305200"}, {"first_name"=>"Hikaru", "last_name"=>"Takeuchi", "scopus_author_id"=>"35424418300"}, {"first_name"=>"Benjamin", "last_name"=>"Thyreau", "scopus_author_id"=>"16069644400"}, {"first_name"=>"Yong", "last_name"=>"He", "scopus_author_id"=>"56190799600"}, {"first_name"=>"Alan C.", "last_name"=>"Evans", "scopus_author_id"=>"7404362358"}, {"first_name"=>"Xiaobo", "last_name"=>"Li", "scopus_author_id"=>"53870396100"}, {"first_name"=>"Ryuta", "last_name"=>"Kawashima", "scopus_author_id"=>"7005986241"}, {"first_name"=>"Hiroshi", "last_name"=>"Fukuda", "scopus_author_id"=>"35407744000"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84873507641", "doi"=>"10.1371/journal.pone.0055347", "pui"=>"368294370", "pmid"=>"23390528", "scopus"=>"2-s2.0-84873507641", "issn"=>"19326203", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)"}, "id"=>"52b02cde-7d22-37a0-ba0c-3a819e4b1a70", "abstract"=>"Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.", "link"=>"http://www.mendeley.com/research/topological-organization-functional-brain-networks-healthy-children-differences-relation-age-sex-int", "reader_count"=>126, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>8, "Researcher"=>17, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>36, "Student > Postgraduate"=>9, "Student > Master"=>25, "Other"=>2, "Student > Bachelor"=>15, "Lecturer"=>2, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>8, "Researcher"=>17, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>36, "Student > Postgraduate"=>9, "Student > Master"=>25, "Other"=>2, "Student > Bachelor"=>15, "Lecturer"=>2, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>14, "Agricultural and Biological Sciences"=>20, "Philosophy"=>1, "Arts and Humanities"=>2, "Computer Science"=>6, "Engineering"=>5, "Mathematics"=>2, "Medicine and Dentistry"=>23, "Neuroscience"=>17, "Sports and Recreations"=>1, "Physics and Astronomy"=>5, "Psychology"=>29, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>23}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>5}, "Psychology"=>{"Psychology"=>29}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>14}, "Arts and Humanities"=>{"Arts and Humanities"=>2}, "Engineering"=>{"Engineering"=>5}, "Neuroscience"=>{"Neuroscience"=>17}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>20}, "Computer Science"=>{"Computer Science"=>6}, "Linguistics"=>{"Linguistics"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "Netherlands"=>3, "United States"=>4, "Norway"=>2, "China"=>1, "Finland"=>1, "United Kingdom"=>1, "Malaysia"=>1}, "group_count"=>3}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/496037"], "description"=>"<p>Global hubs are defined as the brain regions with higher values (>Mean + SD) in any of (A) node degree, (B) node efficiency, and (C) node betweenness. The global hubs are shown in red with node sizes that indicate the values in regional nodal parameters. For a description of the abbreviations, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055347#pone.0055347.s001\" target=\"_blank\">Table S1</a>.</p>", "links"=>[], "tags"=>["hubs"], "article_id"=>166547, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055347.g002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_hubs_in_functional_brain_networks_/166547", "title"=>"Global hubs in functional brain networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-04 01:49:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/496255"], "description"=>"<p>The significant higher values of regional nodal parameters in female and male groups are shown in red and blue, respectively. The significances of p<0.05 and p<0.01 (uncorrected) are indicated by spheres in small and big size, respectively. For a description of the abbreviations, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055347#pone.0055347.s001\" target=\"_blank\">Table S1</a>.</p>", "links"=>[], "tags"=>["nodal"], "article_id"=>166767, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055347.g004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_sex_on_regional_nodal_properties_/166767", "title"=>"Effect of sex on regional nodal properties.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-04 01:52:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/482300", "https://ndownloader.figshare.com/files/482302", "https://ndownloader.figshare.com/files/482305", "https://ndownloader.figshare.com/files/482306", "https://ndownloader.figshare.com/files/482309", "https://ndownloader.figshare.com/files/482312", "https://ndownloader.figshare.com/files/482315", "https://ndownloader.figshare.com/files/482318", "https://ndownloader.figshare.com/files/482319", "https://ndownloader.figshare.com/files/482322", "https://ndownloader.figshare.com/files/482325"], "description"=>"<div><p>Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.</p> </div>", "links"=>[], "tags"=>["topological", "networks", "differences", "intelligence"], "article_id"=>155760, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055347.s001", "https://dx.doi.org/10.1371/journal.pone.0055347.s002", "https://dx.doi.org/10.1371/journal.pone.0055347.s003", "https://dx.doi.org/10.1371/journal.pone.0055347.s004", "https://dx.doi.org/10.1371/journal.pone.0055347.s005", "https://dx.doi.org/10.1371/journal.pone.0055347.s006", "https://dx.doi.org/10.1371/journal.pone.0055347.s007", "https://dx.doi.org/10.1371/journal.pone.0055347.s008", "https://dx.doi.org/10.1371/journal.pone.0055347.s009", "https://dx.doi.org/10.1371/journal.pone.0055347.s010", "https://dx.doi.org/10.1371/journal.pone.0055347.s011"], "stats"=>{"downloads"=>26, "page_views"=>44, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Topological_Organization_of_Functional_Brain_Networks_in_Healthy_Children_Differences_in_Relation_to_Age_Sex_and_Intelligence__/155760", "title"=>"Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-02-04 01:36:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/496159"], "description"=>"<p>Significant linear positive, linear negative, quadratic positive, and quadratic negative correlations are indicated by red, green, yellow, and blue spheres, respectively. The significances of p<0.05 and p<0.01(uncorrected) are shown by spheres in small and big size, respectively. For a description of the abbreviations, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055347#pone.0055347.s001\" target=\"_blank\">Table S1</a>.</p>", "links"=>[], "tags"=>["nodal"], "article_id"=>166670, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055347.g003", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_age_on_regional_nodal_properties_/166670", "title"=>"Effect of age on regional nodal properties.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-04 01:51:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/496540"], "description"=>"a<p>Two multiply linear regressions that modeled age and age<sup>2</sup> as predictors, along with sex as a covariate; the best model was determined by AIC.</p>b<p>A multiply linear regression that modeled age, sex, and age-sex interaction.</p>c<p>Pearson's correlation analysis between IQ and global network properties, each of which was regressed by a multiply linear regression that modeled age, sex, and age-sex interaction.</p><p>L+: Linear regression model showing significant positive correlation. F>M: female shows significantly higher values than male; Fp<0.05 and shown by bold characters.</p><p><i>C</i>, clustering coefficient; <i>L</i>, characteristic path length; <i>NC</i>, normalized clustering coefficient; <i>NL</i>, normalized characteristic path length; <i>SW</i>, small-worldness; <i>LE</i>, local efficiency; <i>GE</i>, global efficiency.</p>", "links"=>[], "tags"=>["iq"], "article_id"=>167051, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055347.t001", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effects_of_age_sex_and_IQ_on_global_network_properties_/167051", "title"=>"The effects of age, sex, and IQ on global network properties.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-04 01:57:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/496455"], "description"=>"<p>The significant positive and negative correlation between IQ and regional nodal parameters are shown in red and blue, respectively. The significances of p<0.05 and p<0.01 (uncorrected) are indicated by spheres in small and big size, respectively. For a description of the abbreviations, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055347#pone.0055347.s001\" target=\"_blank\">Table S1</a>.</p>", "links"=>[], "tags"=>["iq", "nodal"], "article_id"=>166969, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055347.g006", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_IQ_on_regional_nodal_properties_/166969", "title"=>"Effect of IQ on regional nodal properties.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-04 01:56:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/495947"], "description"=>"<p>(A) The clustering coefficient and (B) the characteristic path length are shown as a function of cost thresholds and compared to the matched random networks. (C) The normalized clustering coefficient, the normalized characteristic path length, and (D) the small-worldness are shown as a function of cost thresholds. Note that the small-world regime of cost threshold adopted in this study was from 0.2 to 0.35. (E) The local efficiency and (F) the global efficiency are shown as a function of cost thresholds and compared to the matched random networks. Error bars indicate standard error in all subjects.</p>", "links"=>[], "tags"=>["physiology", "neuroscience", "neurological disorders"], "article_id"=>166451, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055347.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_network_properties_/166451", "title"=>"Global network properties.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-04 01:47:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/496364"], "description"=>"<p>The significant age-by-sex interactions on regional nodal parameters are shown. The correlation between age and regional nodal parameters are shown in female and male groups, respectively. For a description of the abbreviations, see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055347#pone.0055347.s001\" target=\"_blank\">Table S1</a>.</p>", "links"=>[], "tags"=>["nodal"], "article_id"=>166879, "categories"=>["Physiology", "Neuroscience"], "users"=>["Kai Wu", "Yasuyuki Taki", "Kazunori Sato", "Hiroshi Hashizume", "Yuko Sassa", "Hikaru Takeuchi", "Benjamin Thyreau", "Yong He", "Alan C. Evans", "Xiaobo Li", "Ryuta Kawashima", "Hiroshi Fukuda"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0055347.g005", "stats"=>{"downloads"=>1, "page_views"=>50, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Age_by_sex_interaction_on_regional_nodal_properties_/166879", "title"=>"Age-by-sex interaction on regional nodal properties.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-04 01:54:39"}

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Relative Metric

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