{"id":18951,"date":"2024-09-23T12:32:44","date_gmt":"2024-09-23T10:32:44","guid":{"rendered":"https:\/\/sano.science\/?post_type=research&p=18951"},"modified":"2025-01-10T13:46:48","modified_gmt":"2025-01-10T12:46:48","slug":"investigating-the-interaction-between-eeg-and-fnirs-a-multimodal-network-analysis-of-brain-connectivity","status":"publish","type":"research","link":"https:\/\/sano.science\/research\/investigating-the-interaction-between-eeg-and-fnirs-a-multimodal-network-analysis-of-brain-connectivity\/","title":{"rendered":"Investigating the interaction between EEG and fNIRS: A multimodal network analysis of brain connectivity"},"content":{"rendered":"\n

Rosmary Blanco, Cemal Koba, Alessandro Crimi <\/h2>\n\n\n\n
<\/div>\n\n\n\n

Rosmary Blanco, Cemal Koba, Alessandro Crimi Exploring the brain’s complex networks requires multiple neuroimaging techniques, each offering unique insights. Combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has gained attention for its potential to deepen our understanding of brain functioning. However, how these modalities relate is still an open question. Understanding how the electrical and hemodynamic activities relate is crucial for effectively integrating these modalities, potentially enhancing the spatio-temporal resolution of neuroimaging and revealing information about brain function that might be missed when each modality is used in isolation. In this study, we compared brain networks captured by EEG (electrical activity) and fNIRS (hemodynamic activity) in both resting and task-related conditions. Complementarity between modalities was observed, particularly during tasks, as well as a certain level of redundancy when comparing the multimodal and the unimodal approach, which depends on the modality and the specific brain state. Overall, the results highlight differences in how EEG and fNIRS capture brain network topology in different brain states and emphasize the value of integrating multiple modalities for a comprehensive view of brain functioning.<\/p>\n\n\n\n

<\/div>\n\n\n\n

Authors<\/strong>:  Rosmary Blanco, Cemal Koba, Alessandro Crimi <\/p>\n\n\n\n

DOI<\/strong>: https:\/\/doi.org\/10.1016\/j.jocs.2024.102416<\/a> <\/p>\n\n\n\n

Link to article<\/strong>: www.sciencedirect.com<\/a><\/p>\n\n\n\n

Keywords<\/strong>: multimodal neuroimaging, EEG, fNIRS, Multilayer Networks<\/p>\n\n\n\n

<\/div>\n\n\n\n\t\n \n \n\t\t\t\n\n\t\t\t\t\n\t\t\t\t\tREAD HERE\n\t\t\t\t<\/span>\n\n\t\t\t<\/a>\n\n \n \n\n\n\n
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Method workflow:<\/strong> 1.<\/strong> The EEG and fNIRS data collection. 2.<\/strong> Data pre-processing. 3.<\/strong> Source reconstruction. 4.<\/strong> Mapping of the source signals onto the same brain space. 5.<\/strong> Functional connectivity computation. 6.<\/strong> Graph analysis for comparing the topology of brain networks. 7.<\/strong> Multilayer network analysis for modalities integration and multimodal vs unimodal network comparison. Source: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750324002096<\/em><\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"

Journal paper in: www.sciencedirect.com, 2024.<\/p>\n","protected":false},"featured_media":0,"template":"","research_type":[8],"research_team":[15],"class_list":["post-18951","research","type-research","status-publish","hentry","research_type-publications","research_team-computational-neuroscience"],"yoast_head":"\nInvestigating the interaction between EEG and fNIRS: A multimodal network analysis of brain connectivity - Centre for Computational Personalized Medicine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sano.science\/research\/investigating-the-interaction-between-eeg-and-fnirs-a-multimodal-network-analysis-of-brain-connectivity\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Investigating the interaction between EEG and fNIRS: A multimodal network analysis of brain connectivity\" \/>\n<meta property=\"og:description\" content=\"Journal paper in: www.sciencedirect.com, 2024.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sano.science\/research\/investigating-the-interaction-between-eeg-and-fnirs-a-multimodal-network-analysis-of-brain-connectivity\/\" \/>\n<meta property=\"og:site_name\" content=\"Centre for Computational Personalized Medicine\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/sano.science\/\" \/>\n<meta property=\"article:modified_time\" content=\"2025-01-10T12:46:48+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sano.science\/wp-content\/uploads\/2024\/09\/image.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1215\" \/>\n\t<meta property=\"og:image:height\" content=\"722\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@sanoscience\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/sano.science\\\/research\\\/investigating-the-interaction-between-eeg-and-fnirs-a-multimodal-network-analysis-of-brain-connectivity\\\/\",\"url\":\"https:\\\/\\\/sano.science\\\/research\\\/investigating-the-interaction-between-eeg-and-fnirs-a-multimodal-network-analysis-of-brain-connectivity\\\/\",\"name\":\"Investigating the interaction between EEG and fNIRS: A multimodal network analysis of brain connectivity - 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Combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has gained attention for its potential to deepen our understanding of brain functioning. However, how these modalities relate is still an open question. Understanding how the electrical and hemodynamic activities relate is crucial for effectively integrating these modalities, potentially enhancing the spatio-temporal resolution of neuroimaging and revealing information about brain function that might be missed when each modality is used in isolation. In this study, we compared brain networks captured by EEG (electrical activity) and fNIRS (hemodynamic activity) in both resting and task-related conditions. Complementarity between modalities was observed, particularly during tasks, as well as a certain level of redundancy when comparing the multimodal and the unimodal approach, which depends on the modality and the specific brain state. Overall, the results highlight differences in how EEG and fNIRS capture brain network topology in different brain states and emphasize the value of integrating multiple modalities for a comprehensive view of brain functioning.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Rosmary Blanco, Cemal Koba, Alessandro Crimi Exploring the brain's complex networks requires multiple neuroimaging techniques, each offering unique insights. Combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has gained attention for its potential to deepen our understanding of brain functioning. However, how these modalities relate is still an open question. Understanding how the electrical and hemodynamic activities relate is crucial for effectively integrating these modalities, potentially enhancing the spatio-temporal resolution of neuroimaging and revealing information about brain function that might be missed when each modality is used in isolation. In this study, we compared brain networks captured by EEG (electrical activity) and fNIRS (hemodynamic activity) in both resting and task-related conditions. Complementarity between modalities was observed, particularly during tasks, as well as a certain level of redundancy when comparing the multimodal and the unimodal approach, which depends on the modality and the specific brain state. Overall, the results highlight differences in how EEG and fNIRS capture brain network topology in different brain states and emphasize the value of integrating multiple modalities for a comprehensive view of brain functioning.<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"50px","epAnimationGeneratedClass":"edplus_anim-m7Y65m","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-zeiYMr","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\"><strong>Authors<\/strong>:  Rosmary Blanco, Cemal Koba, Alessandro Crimi <\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\"><strong>Authors<\/strong>:  Rosmary Blanco, Cemal Koba, Alessandro Crimi <\/p>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-KyXlgX","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\"><strong>DOI<\/strong>: <a href=\"https:\/\/doi.org\/10.1016\/j.jocs.2024.102416\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/doi.org\/10.1016\/j.jocs.2024.102416<\/a> <\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\"><strong>DOI<\/strong>: <a href=\"https:\/\/doi.org\/10.1016\/j.jocs.2024.102416\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/doi.org\/10.1016\/j.jocs.2024.102416<\/a> <\/p>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-zeiYMr","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\"><strong>Link to article<\/strong>: <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750324002096\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">www.sciencedirect.com<\/a><\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\"><strong>Link to article<\/strong>: <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750324002096\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">www.sciencedirect.com<\/a><\/p>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-zeiYMr","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\"><strong>Keywords<\/strong>: multimodal neuroimaging, EEG, fNIRS, Multilayer Networks<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\"><strong>Keywords<\/strong>: multimodal neuroimaging, EEG, fNIRS, Multilayer Networks<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"50px","epAnimationGeneratedClass":"edplus_anim-m7Y65m","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"acf\/button","attrs":{"title":"READ HERE","button_type":"link","url":"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750324002096","button_style":"primary","target":"_self","button_extra_classes":""},"innerBlocks":[],"innerHTML":"","innerContent":[]},{"blockName":"core\/spacer","attrs":{"height":"50px","epAnimationGeneratedClass":"edplus_anim-m7Y65m","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:50px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"core\/image","attrs":{"id":18960,"sizeSlug":"large","linkDestination":"none","epAnimationGeneratedClass":"edplus_anim-G005GI","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<figure class=\"wp-block-image size-large eplus-wrapper\"><img src=\"https:\/\/sano.science\/wp-content\/uploads\/2024\/09\/image-1024x609.png\" alt=\"\" class=\"wp-image-18960\"\/><figcaption class=\"wp-element-caption\"><strong>Method workflow:<\/strong> <strong>1.<\/strong> The EEG and fNIRS data collection. <strong>2.<\/strong> Data pre-processing. <strong>3.<\/strong> Source reconstruction. <strong>4.<\/strong> Mapping of the source signals onto the same brain space. <strong>5.<\/strong> Functional connectivity computation. <strong>6.<\/strong> Graph analysis for comparing the topology of brain networks. <strong>7.<\/strong> Multilayer network analysis for modalities integration and multimodal vs unimodal network comparison. <em>Source: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750324002096<\/em><\/figcaption><\/figure>\n","innerContent":["\n<figure class=\"wp-block-image size-large eplus-wrapper\"><img src=\"https:\/\/sano.science\/wp-content\/uploads\/2024\/09\/image-1024x609.png\" alt=\"\" class=\"wp-image-18960\"\/><figcaption class=\"wp-element-caption\"><strong>Method workflow:<\/strong> <strong>1.<\/strong> The EEG and fNIRS data collection. <strong>2.<\/strong> Data pre-processing. <strong>3.<\/strong> Source reconstruction. <strong>4.<\/strong> Mapping of the source signals onto the same brain space. <strong>5.<\/strong> Functional connectivity computation. <strong>6.<\/strong> Graph analysis for comparing the topology of brain networks. <strong>7.<\/strong> Multilayer network analysis for modalities integration and multimodal vs unimodal network comparison. <em>Source: https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877750324002096<\/em><\/figcaption><\/figure>\n"]}],"meta_data":{"is_automatically_other_posts":true,"number_of_posts":"3","is_automatically_check_also_posts":true},"_links":{"self":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research\/18951","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research"}],"about":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/types\/research"}],"version-history":[{"count":23,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research\/18951\/revisions"}],"predecessor-version":[{"id":20724,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research\/18951\/revisions\/20724"}],"wp:attachment":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media?parent=18951"}],"wp:term":[{"taxonomy":"research_type","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research_type?post=18951"},{"taxonomy":"research_team","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/research_team?post=18951"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}