{"id":426,"date":"2009-11-01T00:00:05","date_gmt":"2009-10-31T23:00:05","guid":{"rendered":"http:\/\/www.poil.dk\/s\/?p=426"},"modified":"2011-04-06T09:15:35","modified_gmt":"2011-04-06T08:15:35","slug":"abstract-the-neurophysiological-biomarker-toolbox-for-pre-clinical-eegmeg-research","status":"publish","type":"post","link":"https:\/\/www.poil.dk\/s\/abstract-the-neurophysiological-biomarker-toolbox-for-pre-clinical-eegmeg-research\/426","title":{"rendered":"Abstract: The Neurophysiological Biomarker Toolbox for pre-clinical EEG\/MEG research"},"content":{"rendered":"<p style=\"text-align: center;\"><strong>The Neurophysiological Biomarker Toolbox for pre-clinical EEG\/MEG research<\/strong><\/p>\n<p style=\"text-align: center;\">Simon-Shlomo Poil, Klaus Linkenkaer-Hansen<br \/>\nDepartment of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), VU University Amsterdam, The Netherlands.<\/p>\n<p><strong>Introduction<\/strong> Eyes-closed rest EEG\/MEG is used for assessing the functional state of the brain in pre-clinical research\u2014typically in terms of disease influences on neuronal oscillation frequency, amplitude, or coherence. However, neuronal oscillations fluctuate considerably in time and amplitude and this is not captured by the classical analyses.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter\" title=\"NBT\" src=\"http:\/\/www.poil.dk\/s\/wp-content\/uploads\/NBTFig1.png\" alt=\"\" width=\"632\" height=\"307\" \/><\/p>\n<p><span>The study of spatial and temporal dimensions of neuronal processing requires different correlation analyses. Coordination of anatomically distributed activity (parallel processing) may be studied by computing correlations between neuronal signals from different brain areas (Cross-correlations). In contrast, coordination of brain activity over time (serial processing) may be studied by computing auto-correlations in neuronal signals within a single brain area (Auto-correlations). See Figure.<\/span><\/p>\n<p><span><strong>Methods<\/strong> The MATLAB-based &#8220;Neurophysiological Biomarker Toolbox&#8221; (or NBT)\u00a0provides algorithms for characterizing the temporal structure of ongoing oscillations. (<a href=\"http:\/\/www.falw.vu\/~nbt\/\">see our webpage<\/a>) <\/span><\/p>\n<p><strong>Results<\/strong> Using the NBT, we have observed a prominent decrease in auto-correlations in early-stage Alzheimer&#8217;s disease  <a href=\"http:\/\/www.poil.dk\/s\/article-altered-temporal-correlations-in-parietal-alpha-and-prefrontal-theta-oscillations-in-early-stage-alzheimer-disease\/126\" target=\"_self\">(Montez &amp; Poil et al., PNAS, 2009)<\/a>. See Figure.<\/p>\n<p><strong>Conclusions<\/strong> The temporal structure of ongoing oscillations may be important for brain function and its quantitative analysis provides an important insight into the functional organization of the brain in pre-clinical research using resting-state EEG\/MEG. We invite collaborators to use our NBT toolbox.<\/p>\n<p>Please feel free to contact me:<br \/>\nsimo<a title=\"Reveal this e-mail address\" onclick=\"window.open('http:\/\/mailhide.recaptcha.net\/d?k=01BgDyPlSfaN_6hA7O0FaI_A==&amp;c=pKCrCNWTw-vl3AjPHv1iGeuVZeUq7jphdiu30JrYox4=', '', 'toolbar=0,scrollbars=0,location=0,statusbar=0,menubar=0,resizable=0,width=500,height=300'); return false;\" href=\"http:\/\/mailhide.recaptcha.net\/d?k=01BgDyPlSfaN_6hA7O0FaI_A==&amp;c=pKCrCNWTw-vl3AjPHv1iGeuVZeUq7jphdiu30JrYox4=\">(click here to reveal email)<\/a>@cncr.vu.nl<\/p>\n<p><strong>Keywords<\/strong> Ongoing oscillations, MEG, EEG, biomarkers, Alzheimer\u2019s disease<\/p>\n<p>(abstract: ONWA annual PhD-meeting 2009)<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Neurophysiological Biomarker Toolbox for pre-clinical EEG\/MEG research Simon-Shlomo Poil, Klaus Linkenkaer-Hansen Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), VU University Amsterdam, The Netherlands. Introduction Eyes-closed rest EEG\/MEG is used for assessing the functional state of<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19],"tags":[18,11,59,8,7],"class_list":["post-426","post","type-post","status-publish","format-standard","hentry","category-abstracts","tag-biomarkers","tag-long-range-temporal-correlations","tag-neuroimaging","tag-ongoing-oscillations","tag-resting-state"],"_links":{"self":[{"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/posts\/426","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/comments?post=426"}],"version-history":[{"count":12,"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/posts\/426\/revisions"}],"predecessor-version":[{"id":498,"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/posts\/426\/revisions\/498"}],"wp:attachment":[{"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/media?parent=426"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/categories?post=426"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.poil.dk\/s\/wp-json\/wp\/v2\/tags?post=426"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}