MEG Network Differences between Low- and High-Grade Glioma Related to Epilepsy and Cognition
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{"title"=>"MEG Network Differences between Low- and High-Grade Glioma Related to Epilepsy and Cognition", "type"=>"journal", "authors"=>[{"first_name"=>"Edwin", "last_name"=>"van Dellen", "scopus_author_id"=>"35849449100"}, {"first_name"=>"Linda", "last_name"=>"Douw", "scopus_author_id"=>"24334419600"}, {"first_name"=>"Arjan", "last_name"=>"Hillebrand", "scopus_author_id"=>"6603686887"}, {"first_name"=>"Irene H.M.", "last_name"=>"Ris-Hilgersom", "scopus_author_id"=>"55484412600"}, {"first_name"=>"Menno M.", "last_name"=>"Schoonheim", "scopus_author_id"=>"25958454400"}, {"first_name"=>"Johannes C.", "last_name"=>"Baayen", "scopus_author_id"=>"6603233868"}, {"first_name"=>"Philip C.", "last_name"=>"de Witt Hamer", "scopus_author_id"=>"6602566797"}, {"first_name"=>"Demetrios N.", "last_name"=>"Velis", "scopus_author_id"=>"7003391109"}, {"first_name"=>"Martin", "last_name"=>"Klein", "scopus_author_id"=>"35454106200"}, {"first_name"=>"Jan J.", "last_name"=>"Heimans", "scopus_author_id"=>"35458528100"}, {"first_name"=>"Cornelis J.", "last_name"=>"Stam", "scopus_author_id"=>"7006776249"}, {"first_name"=>"Jaap C.", "last_name"=>"Reijneveld", "scopus_author_id"=>"6601987815"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84869112427", "pui"=>"366053693", "doi"=>"10.1371/journal.pone.0050122", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "sgr"=>"84869112427", "pmid"=>"23166829"}, "id"=>"c882d19c-84ce-3109-b621-b756185539d0", "abstract"=>"ObjectiveTo reveal possible differences in whole brain topology of epileptic glioma patients, being low-grade glioma (LGG) and high-grade glioma (HGG) patients. We studied functional networks in these patients and compared them to those in epilepsy patients with non-glial lesions (NGL) and healthy controls. Finally, we related network characteristics to seizure frequency and cognitive performance within patient groups.MethodsWe constructed functional networks from pre-surgical resting-state magnetoencephalography (MEG) recordings of 13 LGG patients, 12 HGG patients, 10 NGL patients, and 36 healthy controls. Normalized clustering coefficient and average shortest path length as well as modular structure and network synchronizability were computed for each group. Cognitive performance was assessed in a subset of 11 LGG and 10 HGG patients.ResultsLGG patients showed decreased network synchronizability and decreased global integration compared to healthy controls in the theta frequency range (4–8 Hz), similar to NGL patients. HGG patients’ networks did not significantly differ from those in controls. Network characteristics correlated with clinical presentation regarding seizure frequency in LGG patients, and with poorer cognitive performance in both LGG and HGG glioma patients.ConclusionLesion histology partly determines differences in functional networks in glioma patients suffering from epilepsy. We suggest that differences between LGG and HGG patients’ networks are explained by differences in plasticity, guided by the particular lesional growth pattern. Interestingly, decreased synchronizability and decreased global integration in the theta band seem to make LGG and NGL patients more prone to the occurrence of seizures and cognitive decline.", "link"=>"http://www.mendeley.com/research/meg-network-differences-between-low-highgrade-glioma-related-epilepsy-cognition", "reader_count"=>90, "reader_count_by_academic_status"=>{"Unspecified"=>8, "Professor > Associate Professor"=>4, "Librarian"=>1, "Researcher"=>13, "Student > Doctoral Student"=>1, "Student > Ph. D. 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Student"=>22, "Student > Postgraduate"=>6, "Student > Master"=>17, "Other"=>7, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>10, "Engineering"=>4, "Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>15, "Medicine and Dentistry"=>29, "Neuroscience"=>14, "Physics and Astronomy"=>1, "Psychology"=>14, "Computer Science"=>1, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>29}, "Neuroscience"=>{"Neuroscience"=>14}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>14}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>15}, "Computer Science"=>{"Computer Science"=>1}, "Linguistics"=>{"Linguistics"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>10}}, "reader_count_by_country"=>{"Netherlands"=>1, "Egypt"=>1, "Brazil"=>1, "United Kingdom"=>1, "Italy"=>2, "Germany"=>1, "Ethiopia"=>1}, "group_count"=>8}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/291733", "https://ndownloader.figshare.com/files/291775", "https://ndownloader.figshare.com/files/291813", "https://ndownloader.figshare.com/files/291864", "https://ndownloader.figshare.com/files/291931"], "description"=>"<div><h3>Objective</h3><p>To reveal possible differences in whole brain topology of epileptic glioma patients, being low-grade glioma (LGG) and high-grade glioma (HGG) patients. We studied functional networks in these patients and compared them to those in epilepsy patients with non-glial lesions (NGL) and healthy controls. Finally, we related network characteristics to seizure frequency and cognitive performance within patient groups.</p> <h3>Methods</h3><p>We constructed functional networks from pre-surgical resting-state magnetoencephalography (MEG) recordings of 13 LGG patients, 12 HGG patients, 10 NGL patients, and 36 healthy controls. Normalized clustering coefficient and average shortest path length as well as modular structure and network synchronizability were computed for each group. Cognitive performance was assessed in a subset of 11 LGG and 10 HGG patients.</p> <h3>Results</h3><p>LGG patients showed decreased network synchronizability and decreased global integration compared to healthy controls in the theta frequency range (4–8 Hz), similar to NGL patients. HGG patients’ networks did not significantly differ from those in controls. Network characteristics correlated with clinical presentation regarding seizure frequency in LGG patients, and with poorer cognitive performance in both LGG and HGG glioma patients.</p> <h3>Conclusion</h3><p>Lesion histology partly determines differences in functional networks in glioma patients suffering from epilepsy. We suggest that differences between LGG and HGG patients’ networks are explained by differences in plasticity, guided by the particular lesional growth pattern. Interestingly, decreased synchronizability and decreased global integration in the theta band seem to make LGG and NGL patients more prone to the occurrence of seizures and cognitive decline.</p> </div>", "links"=>[], "tags"=>["meg", "differences", "low-", "high-grade", "glioma", "epilepsy", "cognition"], "article_id"=>117431, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0050122.s001", "https://dx.doi.org/10.1371/journal.pone.0050122.s002", "https://dx.doi.org/10.1371/journal.pone.0050122.s003", "https://dx.doi.org/10.1371/journal.pone.0050122.s004", "https://dx.doi.org/10.1371/journal.pone.0050122.s005"], "stats"=>{"downloads"=>28, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/MEG_Network_Differences_between_Low_and_High_Grade_Glioma_Related_to_Epilepsy_and_Cognition__/117431", "title"=>"MEG Network Differences between Low- and High-Grade Glioma Related to Epilepsy and Cognition", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-11-14 02:03:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/543701"], "description"=>"<p>Overview of functional connectivity and network studies based on MEG recordings in brain tumour and TLE patients. The measure for functional connectivity used in the study is given in the Methods column. Abbreviations: SL  =  Synchronization Likelihood; PLI  =  Phase Lag Index; L/Ls  =  normalized average path length; C/Cs  =  normalized average clustering coefficient; degree cor.  =  degree correlation (measure for the tendency of vertices to connect to other vertices with a similar degree).</p>1<p>MEG recordings used in these studies were obtained after surgery, which might also have had an impact on functional connectivity levels and network topology.</p>2<p>No information available on epilepsy incidence in these patients.</p>3<p>This study did not compare patients to healthy controls, but compared MEG recordings of patients before and after resection of the brain tumour.</p>4<p>This study analyzed patients with non-glial lesions, and should therefore be considered only as a reference for patients with NGL in the present study.</p>", "links"=>[], "tags"=>["meg", "connectivity", "studies", "lesional", "epilepsy"], "article_id"=>214185, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0050122.t003", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_MEG_functional_connectivity_studies_on_lesional_epilepsy_patients_/214185", "title"=>"Overview of MEG functional connectivity studies on lesional epilepsy patients.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-11-14 01:09:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/543497"], "description"=>"<p>Note that seizure frequency is plotted on a logarithmic scale. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050122#pone.0050122.s004\" target=\"_blank\">tables S4</a> and <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050122#pone.0050122.s005\" target=\"_blank\">S5</a> for seizure frequency and synchronizability values for each patient.</p>", "links"=>[], "tags"=>["synchronizability", "seizure", "glioma"], "article_id"=>213978, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0050122.g003", "stats"=>{"downloads"=>0, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Theta_band_synchronizability_and_seizure_frequency_in_low_grade_glioma_patients_/213978", "title"=>"Theta band synchronizability and seizure frequency in low grade glioma patients.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:06:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/543615"], "description"=>"<p>Seizure frequency is given per month; Epilepsy history is defined as months passed since first seizure. Cognitive performance scores are presented as z-scores based on individual matched healthy controls. Also, cognitive performance is presented of the domains attention (Stroop test), executive functioning (Verbal Fluency test) and verbal memory (Visual Verbal Learning test). Abbreviations: AED  =  anti-epileptic drug; DNET  =  Dysembryoplastic Neoepithelial Tumor; MTS  =  Mesiotemporal Sclerosis; HEM  =  Hematoma; HAM  =  Hamartoma; DYS  =  Dysplasia.</p>", "links"=>[], "tags"=>["surgery", "oncology", "neuroscience", "neurological disorders", "mathematics"], "article_id"=>214087, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0050122.t001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Patient_characteristics_/214087", "title"=>"Patient characteristics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-11-14 01:08:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/543554"], "description"=>"<p>Attention scores are presented as z-scores gained by comparison with healthy controls matched for age, gender and educational level. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050122#pone.0050122.s004\" target=\"_blank\">table S4</a> for attention scores and synchronizability values for each patient.</p>", "links"=>[], "tags"=>["synchronizability", "stroop"], "article_id"=>214037, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0050122.g004", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Theta_band_synchronizability_and_attention_as_measured_by_Stroop_tests_/214037", "title"=>"Theta band synchronizability and attention as measured by Stroop tests.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:07:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/543285"], "description"=>"<p>Parameters were averaged for each sensor on a group level and displayed on a helmet-shaped surface to show global patterns of differences between patient groups. Note that particularly in LGG patients, theta band clustering and participation coefficients show global alterations irrespective of local PLI values. Abbreviations: CTL  =  healthy controls; LGG  =  low-grade glioma patients; HGG  =  high-grade glioma patients; NGL  =  non-glioma patients; PLI  =  phase lag index; C<sub>w,i</sub>*  =  nodal clustering coefficient; L<sub>w,i</sub>*  =  nodal path length;  =  within-module degree z-score;  =  participation coefficient. <i>*In the analysis we use normalized average weighted clustering coefficient (C<sub>w</sub>/C<sub>ws</sub>) and normalized average weighted shortest path length (L<sub>w</sub>/L<sub>ws</sub>) instead of the unnormalized values for each vertex i, C<sub>w,i</sub> and L<sub>w,i</sub> which are visualized here. C<sub>w</sub>/C<sub>ws</sub> and L<sub>w</sub>/L<sub>ws</sub> are calculated by first averaging over nodes and then dividing C<sub>w</sub> and L<sub>w</sub> by a reference value C<sub>ws</sub> and L<sub>ws</sub>, in order to get normalized values. However, this normalization does not affect the spatial distribution of C<sub>w,i</sub> and L<sub>w,i</sub>, and therefore the original data is presented.</i></p>", "links"=>[], "tags"=>["pli", "characteristics", "patients"], "article_id"=>213763, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0050122.g001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Theta_band_PLI_and_network_characteristics_for_patients_and_healthy_controls_/213763", "title"=>"Theta band PLI and network characteristics for patients and healthy controls.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:02:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/543408"], "description"=>"<p>The upper images show T2-weighted MRI images of the tumor. The lower images show theta band PLI levels (background colors; red colors represent high PLI levels, blue colors represent low PLI levels). Note that the tumor region seems to have the highest theta band PLI. The colored lines represent connections between sensors, each color representing another module. Connections are shown when their strength passes an arbitrary threshold chosen for optimal connection visualization. In HGG patients, only few connections exist above the threshold. Note that especially connections to the tumor region in LGG patients pass the threshold. However, two other modules are also clearly shown that are not found in the HGG patient, suggesting that the differences between LGG and HGG patients networks are not restricted to the tumor region.</p>", "links"=>[], "tags"=>["theta", "differences", "lgg", "hgg", "located", "frontal"], "article_id"=>213879, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0050122.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Example_of_theta_band_connection_differences_between_a_LGG_patient_and_a_HGG_patient_both_suffering_from_a_tumor_located_in_the_right_frontal_lobe_/213879", "title"=>"Example of theta band connection differences between a LGG patient and a HGG patient, both suffering from a tumor located in the right frontal lobe.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-14 01:04:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/543653"], "description"=>"<p>Results are given as mean values of network characterstics and p-values of Kruskall-Wallis tests. P-values were considered significant for (p<0.05) after correction using the false discovery rate. Note that the within-module degree z-score (not shown) did not differ significantly.</p><p>Results are marked (↑ or ↓) when significantly different from other groups based on post-hoc analyses using Mann-Whitney U tests. Significance levels are given in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050122#pone.0050122.s001\" target=\"_blank\">table S1</a>.</p><p>Abbreviations: NGL  =  non-glial lesion; LGG  =  low-grade glioma; HGG  =  high-grade glioma; PLI  =  phase lag index; Cw/Cws  =  normalized average weighted clustering coefficient; L<sub>w</sub>/L<sub>ws</sub>  =  normalized average weighted shortest path length; S  =  synchronizability;  =  modularity; P<sub>w</sub>  =  between-module connectivity.</p>", "links"=>[], "tags"=>["patients", "controls", "theta"], "article_id"=>214135, "categories"=>["Cancer", "Mathematics", "Medicine", "Neuroscience"], "users"=>["Edwin van Dellen", "Linda Douw", "Arjan Hillebrand", "Irene H. M. Ris-Hilgersom", "Menno M. Schoonheim", "Johannes C. Baayen", "Philip C. De Witt Hamer", "Demetrios N. Velis", "Martin Klein", "Jan J. Heimans", "Cornelis J. Stam", "Jaap C. Reijneveld"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0050122.t002", "stats"=>{"downloads"=>1, "page_views"=>41, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Differences_between_patients_and_healthy_controls_regarding_theta_band_network_characteristics_/214135", "title"=>"Differences between patients and healthy controls regarding theta band network characteristics.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-11-14 01:08:55"}

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Relative Metric

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