<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="https://www.nitrc.org/themes/nitrc3.0/css/rss.xsl.php?feed=https://www.nitrc.org/export/rss20_forum.php?forum_id=6109" ?>
<?xml-stylesheet type="text/css" href="https://www.nitrc.org/themes/nitrc3.0/css/rss.css" ?>
<rss version="2.0"> <channel>
  <title>NITRC News Group Forum: ballistocardiogram-artefact-correction-taking-into-account-physiological-signal-preservation-in-simultaneous-eeg-fmri.</title>
  <link>http://www.nitrc.org/forum/forum.php?forum_id=6109</link>
  <description>
	&lt;table border=&quot;0&quot; width=&quot;100%&quot;&gt;&lt;tr&gt;&lt;td align=&quot;left&quot;/&gt;&lt;/tr&gt;&lt;/table&gt;
        &lt;p&gt;&lt;b&gt;Ballistocardiogram artefact correction taking into account physiological signal preservation in simultaneous EEG-fMRI.&lt;/b&gt;&lt;/p&gt;          
        &lt;p&gt;Neuroimage. 2016 Mar 21;&lt;/p&gt;
        &lt;p&gt;Authors:  Abreu R, Leite M, Jorge J, Grouiller F, van der Zwaag W, Leal A, Figueiredo P&lt;/p&gt;
        &lt;p&gt;Abstract&lt;br/&gt;
        The ballistocardiogram (BCG) artefact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artefacts and/or deterioration of the physiological signals of interest. In this paper, we propose a family of methods whereby the EEG is decomposed using Independent Component Analysis (ICA) and a novel approach for the selection of BCG-related independent components (ICs) is used (PROJection onto Independent Components, PROJIC). Three ICA-based strategies for BCG artefact correction are then explored: 1) BCG-related ICs are removed from the back-reconstruction of the EEG (PROJIC); and 2-3) BCG-related ICs are corrected for the artefact occurrences using an Optimal Basis Set (OBS) or Average Artefact Subtraction (AAS) framework, before back-projecting all ICs onto EEG space (PROJIC-OBS and PROJIC-AAS, respectively). A novel evaluation pipeline is also proposed to assess the methods performance, which takes into account not only artefact but also physiological signal removal, allowing for a flexible weighting of the importance given to physiological signal preservation. This evaluation is used for the group-level parameter optimization of each algorithm on simultaneous EEG-fMRI data acquired using two different setups at 3T and 7T. Comparison with state-of-the-art BCG correction methods showed that PROJIC-OBS and PROJIC-AAS outperformed the others when priority was given to artefact removal or physiological signal preservation, respectively, while both PROJIC-AAS and AAS were in general the best choices for intermediate trade-offs. The impact of the BCG correction on the quality of event-related potentials (ERPs) of interest was assessed in terms of the relative reduction of the standard error (SE) across trials: 26/66%, 32/62% and 18/61% were achieved by, respectively, PROJIC, PROJIC-OBS and PROJIC-AAS, for data collected at 3T/7T. Although more significant improvements were achieved at 7T, the results were qualitatively comparable for both setups, which indicate the wide applicability of the proposed methodologies and recommendations.&lt;br/&gt;
        &lt;/p&gt;&lt;p&gt;PMID: 27012501 [PubMed - as supplied by publisher]&lt;/p&gt;
    </description>
  <language>en-us</language>
  <copyright>Copyright 2000-2026 NITRC OSI</copyright>
  <webMaster></webMaster>
  <lastBuildDate>Mon, 04 May 2026 20:21:00 GMT</lastBuildDate>
  <docs>http://blogs.law.harvard.edu/tech/rss</docs>
  <generator>NITRC RSS generator</generator>
 </channel>
</rss>
