Magnetoencephalography Reveals a Widespread Increase in Network Connectivity in Idiopathic/Genetic Generalized Epilepsy
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{"title"=>"Magnetoencephalography reveals a widespread increase in network connectivity in idiopathic/genetic generalized epilepsy", "type"=>"journal", "authors"=>[{"first_name"=>"Adham", "last_name"=>"Elshahabi", "scopus_author_id"=>"56388640800"}, {"first_name"=>"Silke", "last_name"=>"Klamer", "scopus_author_id"=>"25947557800"}, {"first_name"=>"Ashish Kaul", "last_name"=>"Sahib", "scopus_author_id"=>"55366387700"}, {"first_name"=>"Holger", "last_name"=>"Lerche", "scopus_author_id"=>"7004557270"}, {"first_name"=>"Christoph", "last_name"=>"Braun", "scopus_author_id"=>"7202498577"}, {"first_name"=>"Niels K.", "last_name"=>"Focke", "scopus_author_id"=>"23468885000"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"608877896", "pmid"=>"26368933", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0138119", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-84960411987", "sgr"=>"84960411987"}, "id"=>"fddfa51a-8d19-37dd-8023-9f55942bcccb", "abstract"=>"Idiopathic/genetic generalized epilepsy (IGE/GGE) is characterized by seizures, which start and rapidly engage widely distributed networks, and result in symptoms such as absences, generalized myoclonic and primary generalized tonic-clonic seizures. Although routine magnetic resonance imaging is apparently normal, many studies have reported structural alterations in IGE/GGE patients using diffusion tensor imaging and voxel-based morphometry. Changes have also been reported in functional networks during generalized spike wave discharges. However, network function in the resting-state without epileptiforme discharges has been less well studied. We hypothesize that resting-state networks are more representative of the underlying pathophysiology and abnormal network synchrony. We studied functional network connectivity derived from whole-brain magnetoencephalography recordings in thirteen IGE/GGE and nineteen healthy controls. Using graph theoretical network analysis, we found a widespread increase in connectivity in patients compared to controls. These changes were most pronounced in the motor network, the mesio-frontal and temporal cortex. We did not, however, find any significant difference between the normalized clustering coefficients, indicating preserved gross network architecture. Our findings suggest that increased resting state connectivity could be an important factor for seizure spread and/or generation in IGE/GGE, and could serve as a biomarker for the disease.", "link"=>"http://www.mendeley.com/research/magnetoencephalography-reveals-widespread-increase-network-connectivity-idiopathicgenetic-generalize", "reader_count"=>29, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>2, "Researcher"=>5, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>2, "Student > Master"=>7, "Other"=>1, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>2, "Researcher"=>5, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>2, "Student > Master"=>7, "Other"=>1, "Lecturer"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>4, "Unspecified"=>2, "Mathematics"=>1, "Agricultural and Biological Sciences"=>5, "Medicine and Dentistry"=>7, "Neuroscience"=>3, "Psychology"=>4, "Computer Science"=>3}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>7}, "Neuroscience"=>{"Neuroscience"=>3}, "Psychology"=>{"Psychology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>5}, "Computer Science"=>{"Computer Science"=>3}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"United States"=>2}, "group_count"=>3}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2262366"], "description"=>"<p>After artifact rejection, MEG data was projected to the source space using dynamic imaging of coherence sources (DICS) beamformer. The beamformer was based on cross-spectral density matrix and an individual head model. The source model was defined on a regular 3D grid of 1 cm resolution and then warped to fit each participant’s structural MRI. Connectivity between different sources was estimated using the imaginary part of coherence.</p>", "links"=>[], "tags"=>["network connectivity", "Network Analysis", "epileptiforme discharges", "network architecture", "spike wave discharges", "seizure spread", "motor network", "network synchrony", "Diffusion tensor imaging", "network function", "ige", "resonance imaging", "State Connectivity"], "article_id"=>1542285, "categories"=>["Uncategorised"], "users"=>["Adham Elshahabi", "Silke Klamer", "Ashish Kaul Sahib", "Holger Lerche", "Christoph Braun", "Niels K. Focke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0138119.g001", "stats"=>{"downloads"=>2, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Data_processing_and_network_construction_pipeline_/1542285", "title"=>"Data processing and network construction pipeline.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-09-14 04:03:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/2262383", "https://ndownloader.figshare.com/files/2262384", "https://ndownloader.figshare.com/files/2262385", "https://ndownloader.figshare.com/files/2262386"], "description"=>"<div><p>Idiopathic/genetic generalized epilepsy (IGE/GGE) is characterized by seizures, which start and rapidly engage widely distributed networks, and result in symptoms such as absences, generalized myoclonic and primary generalized tonic-clonic seizures. Although routine magnetic resonance imaging is apparently normal, many studies have reported structural alterations in IGE/GGE patients using diffusion tensor imaging and voxel-based morphometry. Changes have also been reported in functional networks during generalized spike wave discharges. However, network function in the resting-state without epileptiforme discharges has been less well studied. We hypothesize that resting-state networks are more representative of the underlying pathophysiology and abnormal network synchrony. We studied functional network connectivity derived from whole-brain magnetoencephalography recordings in thirteen IGE/GGE and nineteen healthy controls. Using graph theoretical network analysis, we found a widespread increase in connectivity in patients compared to controls. These changes were most pronounced in the motor network, the mesio-frontal and temporal cortex. We did not, however, find any significant difference between the normalized clustering coefficients, indicating preserved gross network architecture. Our findings suggest that increased resting state connectivity could be an important factor for seizure spread and/or generation in IGE/GGE, and could serve as a biomarker for the disease.</p></div>", "links"=>[], "tags"=>["network connectivity", "Network Analysis", "epileptiforme discharges", "network architecture", "spike wave discharges", "seizure spread", "motor network", "network synchrony", "Diffusion tensor imaging", "network function", "ige", "resonance imaging", "State Connectivity"], "article_id"=>1542302, "categories"=>["Uncategorised"], "users"=>["Adham Elshahabi", "Silke Klamer", "Ashish Kaul Sahib", "Holger Lerche", "Christoph Braun", "Niels K. Focke"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0138119.s001", "https://dx.doi.org/10.1371/journal.pone.0138119.s002", "https://dx.doi.org/10.1371/journal.pone.0138119.s003", "https://dx.doi.org/10.1371/journal.pone.0138119.s004"], "stats"=>{"downloads"=>4, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Magnetoencephalography_Reveals_a_Widespread_Increase_in_Network_Connectivity_in_Idiopathic_Genetic_Generalized_Epilepsy_/1542302", "title"=>"Magnetoencephalography Reveals a Widespread Increase in Network Connectivity in Idiopathic/Genetic Generalized Epilepsy", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-09-14 04:03:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/2262368"], "description"=>"<p>IGE/GGE patients show clusters of increased connectivity in the beta1 (12–20 Hz) and beta2 (21–29 Hz) bands. In beta1 band, the clusters were mainly located at the left superior temporal gyrus (p = 0.004), the right inferior temporal gyrus (p = 0.011), and the left middle frontal gyrus (p = 0.029). In the beta2 band, four significant clusters were found, located mainly at the left middle frontal gyrus (p = 0.0003), the left fusiform gyrus (p = 0.002), the triangular part of the left inferior frontal guys (p = 0.005) and the right postcentral gyrus (p = 0.034).</p>", "links"=>[], "tags"=>["network connectivity", "Network Analysis", "epileptiforme discharges", "network architecture", "spike wave discharges", "seizure spread", "motor network", "network synchrony", "Diffusion tensor imaging", "network function", "ige", "resonance imaging", "State Connectivity"], "article_id"=>1542287, "categories"=>["Uncategorised"], "users"=>["Adham Elshahabi", "Silke Klamer", "Ashish Kaul Sahib", "Holger Lerche", "Christoph Braun", "Niels K. Focke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0138119.g003", "stats"=>{"downloads"=>4, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Group_comparison_of_functional_connectivity_in_IGE_and_healthy_controls_in_high_resolution_networks_/1542287", "title"=>"Group comparison of functional connectivity in IGE and healthy controls in high-resolution networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-09-14 04:03:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/2262369"], "description"=>"<p>(A) The brightness of the lines connecting regions is proportional to the connectivity value between the two regions. Same color scaling is used for controls and patients’ plots in the same frequency band. (B) The grand average low-resolution network obtained from patients in the beta2 band showing the labels of the AAL regions associated with each node in the network.</p>", "links"=>[], "tags"=>["network connectivity", "Network Analysis", "epileptiforme discharges", "network architecture", "spike wave discharges", "seizure spread", "motor network", "network synchrony", "Diffusion tensor imaging", "network function", "ige", "resonance imaging", "State Connectivity"], "article_id"=>1542288, "categories"=>["Uncategorised"], "users"=>["Adham Elshahabi", "Silke Klamer", "Ashish Kaul Sahib", "Holger Lerche", "Christoph Braun", "Niels K. Focke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0138119.g004", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Grand_averaged_low_resolution_connectivity_networks_across_participants_of_each_group_/1542288", "title"=>"Grand averaged low-resolution connectivity networks across participants of each group.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-09-14 04:03:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/2262367"], "description"=>"<p>A) Nodal strength in high-resolution networks B) weighted normalized clustering coefficient in high-resolution networks C) weighted normalized characteristic path length in high-resolution networks D) nodal strength in low-resolution networks E) weighted normalized clustering coefficient in low-resolution networks F) weighted normalized characteristic path length in low-resolution networks. Plots show the medians and the interquartile range across participants in each group. The stars indicate the significant statistical difference between the IGE and healthy control groups using the Mann-Whitney U test. Patients show a significant increase in the nodal strength in both beta1 (p = 0.003) and beta2 (p = 0.0003) bands in high-resolution, as well as in the low-resolution networks (p = 0.005 and p = 0.0003 respectively). Patients also show a significantly lower characteristic path length in the beta2 band in high-resolution network (p = 0.013).</p>", "links"=>[], "tags"=>["network connectivity", "Network Analysis", "epileptiforme discharges", "network architecture", "spike wave discharges", "seizure spread", "motor network", "network synchrony", "Diffusion tensor imaging", "network function", "ige", "resonance imaging", "State Connectivity"], "article_id"=>1542286, "categories"=>["Uncategorised"], "users"=>["Adham Elshahabi", "Silke Klamer", "Ashish Kaul Sahib", "Holger Lerche", "Christoph Braun", "Niels K. Focke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0138119.g002", "stats"=>{"downloads"=>4, "page_views"=>121, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_network_characteristics_in_high_resolution_and_low_resolution_networks_/1542286", "title"=>"Global network characteristics in high-resolution and low-resolution networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-09-14 04:03:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/2262376"], "description"=>"<p>IGE/GGE patients show sub-networks of edges with significantly higher connectivity values in the alpha, beta1 and beta2 bands. Note the particular involvement of motor-networks. No significant clusters were found with higher connectivity in healthy controls. Color and size codes are proportional to the t-statistic value. The brain networks were visualized with the BrainNet Viewer [<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0138119#pone.0138119.ref034\" target=\"_blank\">34</a>].</p>", "links"=>[], "tags"=>["network connectivity", "Network Analysis", "epileptiforme discharges", "network architecture", "spike wave discharges", "seizure spread", "motor network", "network synchrony", "Diffusion tensor imaging", "network function", "ige", "resonance imaging", "State Connectivity"], "article_id"=>1542295, "categories"=>["Uncategorised"], "users"=>["Adham Elshahabi", "Silke Klamer", "Ashish Kaul Sahib", "Holger Lerche", "Christoph Braun", "Niels K. Focke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0138119.g005", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Group_comparison_of_functional_connectivity_in_IGE_GGE_and_healthy_controls_in_low_resolution_networks_/1542295", "title"=>"Group comparison of functional connectivity in IGE/GGE and healthy controls in low-resolution networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-09-14 04:03:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/2262377"], "description"=>"<p>Anatomical brain regions (based on the automated anatomical labeling [AAL] atlas) were determined by the coordinates of the local cluster maximum.</p><p>Clusters resulting from nonparametric between-groups clustering statistics of the nodal strength in high-resolution networks (all grey matter voxels).</p>", "links"=>[], "tags"=>["network connectivity", "Network Analysis", "epileptiforme discharges", "network architecture", "spike wave discharges", "seizure spread", "motor network", "network synchrony", "Diffusion tensor imaging", "network function", "ige", "resonance imaging", "State Connectivity"], "article_id"=>1542296, "categories"=>["Uncategorised"], "users"=>["Adham Elshahabi", "Silke Klamer", "Ashish Kaul Sahib", "Holger Lerche", "Christoph Braun", "Niels K. Focke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0138119.t001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Clusters_resulting_from_nonparametric_between_groups_clustering_statistics_of_the_nodal_strength_in_high_resolution_networks_all_grey_matter_voxels_/1542296", "title"=>"Clusters resulting from nonparametric between-groups clustering statistics of the nodal strength in high-resolution networks (all grey matter voxels).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-09-14 04:03:35"}

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Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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