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<meta name="DC.Title" content="Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index" />
<meta name="DC.Identifier" content="10.3174/ajnr.A5169" />
<meta name="DC.Date" content="2017-06-01" />
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<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI.

MATERIALS AND METHODS: Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF.

RESULTS: Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P &lt; .05). Regression analysis of the fALFF with the laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI.

CONCLUSIONS: The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI.

ALFF
:   amplitude of low-frequency fluctuation
BOLD
:   blood oxygen level–dependent
fALFF
:   fractional amplitude of low-frequency fluctuation
FC
:   functional connectivity
LI
:   laterality index
rsfMRI
:   resting-state fMRI" />
<meta name="DC.Contributor" content="K.A. Smitha" />
<meta name="DC.Contributor" content="K.M. Arun" />
<meta name="DC.Contributor" content="P.G. Rajesh" />
<meta name="DC.Contributor" content="B. Thomas" />
<meta name="DC.Contributor" content="C. Kesavadas" />
<meta name="article:published_time" content="2017-06-01" />
<meta name="article:section" content="FUNCTIONAL" />
<meta name="citation_title" content="Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the &lt;i&gt;z&lt;/i&gt; scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Pearson correlation analysis between signals obtained from the &lt;i&gt;z&lt;/i&gt; score of fALFF and the laterality index yielded a correlation coefficient of 0.849 (&lt;i&gt;P&lt;/i&gt; &amp;lt; .05). Regression analysis of the fALFF with the laterality index yielded an &lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI.&lt;/p&gt;" />
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<meta name="twitter:title" content="Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI.

MATERIALS AND METHODS: Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF.

RESULTS: Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P &lt; .05). Regression analysis of the fALFF with the laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI.

CONCLUSIONS: The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI.

ALFF
:   amplitude of low-frequency fluctuation
BOLD
:   blood oxygen level–dependent
fALFF
:   fractional amplitude of low-frequency fluctuation
FC
:   functional connectivity
LI
:   laterality index
rsfMRI
:   resting-state fMRI" />
<meta name="og-title" property="og:title" content="Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/38/6/1187" />
<meta name="og-site-name" property="og:site_name" content="American Journal of Neuroradiology" />
<meta name="og-description" property="og:description" content="BACKGROUND AND PURPOSE: Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI.

MATERIALS AND METHODS: Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF.

RESULTS: Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P &lt; .05). Regression analysis of the fALFF with the laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI.

CONCLUSIONS: The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI.

ALFF
:   amplitude of low-frequency fluctuation
BOLD
:   blood oxygen level–dependent
fALFF
:   fractional amplitude of low-frequency fluctuation
FC
:   functional connectivity
LI
:   laterality index
rsfMRI
:   resting-state fMRI" />
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      <div class="highwire-cite-overline"><span  class="highwire-cite-metadata-article-type highwire-cite-metadata">Research Article</span><span class="separator-pipe"></span><span  class="highwire-cite-metadata-art-cat highwire-cite-metadata"><span class="wrapper">FUNCTIONAL</span></span></div>
  
      <div class="highwire-cite-access"><span class="highwire-citation-access"><i class="highwire-access-icon highwire-access-icon-open-access open-access hw-icon-open-access" title="Open Access" aria-hidden="true"></i><span  class="element-invisible highwire-access-icon highwire-access-icon-open-access" style="">Open Access</span></span></div>
  
      <h1 class="highwire-cite-title" id="page-title">Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">K.A. Smitha</span>, <span class="highwire-citation-author" data-delta="1">K.M. Arun</span>, <span class="highwire-citation-author" data-delta="2">P.G. Rajesh</span>, <span class="highwire-citation-author" data-delta="3">B. Thomas</span> and <span class="highwire-citation-author" data-delta="4">C. Kesavadas</span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">June 2017,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">38 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(6) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1187-1192; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A5169 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-54723--2715948408" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">K.A. Smitha </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Imaging Sciences and Interventional Radiology (K.A.S., K.M.A., B.T., C.K.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=K.A.%2BSmitha%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Smitha%20K&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AK.A.%2BSmitha%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="http://orcid.org/0000-0003-4882-399X" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for K.A. Smitha</a></li></ul></div><div class="author-tooltip-1"><div class="author-tooltip-name">K.M. Arun </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Imaging Sciences and Interventional Radiology (K.A.S., K.M.A., B.T., C.K.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=K.M.%2BArun%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Arun%20K&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AK.M.%2BArun%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="http://orcid.org/0000-0002-7984-0402" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for K.M. Arun</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">P.G. Rajesh </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>b</span>Neurology (P.G.R.), Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India.</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=P.G.%2BRajesh%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Rajesh%20P&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AP.G.%2BRajesh%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="http://orcid.org/0000-0003-1818-6889" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for P.G. Rajesh</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">B. Thomas </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Imaging Sciences and Interventional Radiology (K.A.S., K.M.A., B.T., C.K.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=B.%2BThomas%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Thomas%20B&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AB.%2BThomas%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="http://orcid.org/0000-0003-0355-3375" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for B. Thomas</a></li></ul></div><div class="author-tooltip-4"><div class="author-tooltip-name">C. Kesavadas </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Departments of Imaging Sciences and Interventional Radiology (K.A.S., K.M.A., B.T., C.K.)</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=C.%2BKesavadas%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Kesavadas%20C&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AC.%2BKesavadas%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="http://orcid.org/0000-0003-4914-8666" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for C. 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    <div class="highwire-markup"><div xmlns="http://www.w3.org/1999/xhtml" data-highwire-cite-ref-tooltip-instance="highwire_reflinks_tooltip" class="content-block-markup" xmlns:xhtml="http://www.w3.org/1999/xhtml"><div class="article abstract-view "><span class="highwire-journal-article-marker-start"></span><div class="section abstract" id="abstract-2"><h2>Abstract</h2><div id="sec-1" class="subsection"><p id="p-3"><strong>BACKGROUND AND PURPOSE:</strong> Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI.</p></div><div id="sec-2" class="subsection"><p id="p-4"><strong>MATERIALS AND METHODS:</strong> Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the <em>z</em> scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF.</p></div><div id="sec-3" class="subsection"><p id="p-5"><strong>RESULTS:</strong> Pearson correlation analysis between signals obtained from the <em>z</em> score of fALFF and the laterality index yielded a correlation coefficient of 0.849 (<em>P</em> &lt; .05). Regression analysis of the fALFF with the laterality index yielded an <em>R</em><sup>2</sup> value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI.</p></div><div id="sec-4" class="subsection"><p id="p-6"><strong>CONCLUSIONS:</strong> The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI.</p></div></div><div class="section glossary" id="glossary-1"><h2 class="">ABBREVIATIONS:</h2><dl id="def-list-1"><dt id="def-item-1">ALFF<span class="def-item-dt-sep"></span></dt><dd>amplitude of low-frequency fluctuation<span class="def-item-dd-sep"></span></dd><dt id="def-item-2">BOLD<span class="def-item-dt-sep"></span></dt><dd>blood oxygen level–dependent<span class="def-item-dd-sep"></span></dd><dt id="def-item-3">fALFF<span class="def-item-dt-sep"></span></dt><dd>fractional amplitude of low-frequency fluctuation<span class="def-item-dd-sep"></span></dd><dt id="def-item-4">FC<span class="def-item-dt-sep"></span></dt><dd>functional connectivity<span class="def-item-dd-sep"></span></dd><dt id="def-item-5">LI<span class="def-item-dt-sep"></span></dt><dd>laterality index<span class="def-item-dd-sep"></span></dd><dt id="def-item-6">rsfMRI<span class="def-item-dt-sep"></span></dt><dd>resting-state fMRI</dd></dl></div><ul class="copyright-statement"><li class="fn" id="copyright-statement-1">© 2017 by American Journal of Neuroradiology</li></ul><div class="license" id="license-1"><p id="p-1">Indicates open access to non-subscribers at <a href="http://www.ajnr.org" rel="license">www.ajnr.org</a></p></div><span class="highwire-journal-article-marker-end"></span></div><span class="related-urls"></span></div><a href="http://ajnr-stage2.stage.highwire.org/content/38/6/1187.full" class="hw-link hw-link-article-full-text" data-icon-position="" data-hide-link-title="0">View Full Text</a></div>  </div>

  
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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 38</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 6 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Jun 2017 </div></div>
      
      
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