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Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy

Identifieur interne : 002643 ( Pmc/Curation ); précédent : 002642; suivant : 002644

Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy

Auteurs : Jonathan Wirsich [France] ; Alistair Perry [Australie] ; Ben Ridley [France] ; Timothée Proix [France] ; Mathieu Golos [France] ; Christian Bénar [France] ; Jean-Philippe Ranjeva [France] ; Fabrice Bartolomei [France] ; Michael Breakspear [Australie] ; Viktor Jirsa [France] ; Maxime Guye [France]

Source :

RBID : PMC:4909094

Abstract

The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain.

We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven right-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome.

In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.


Url:
DOI: 10.1016/j.nicl.2016.05.010
PubMed: 27330970
PubMed Central: 4909094

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PMC:4909094

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<name sortKey="Benar, Christian" sort="Benar, Christian" uniqKey="Benar C" first="Christian" last="Bénar">Christian Bénar</name>
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<name sortKey="Bartolomei, Fabrice" sort="Bartolomei, Fabrice" uniqKey="Bartolomei F" first="Fabrice" last="Bartolomei">Fabrice Bartolomei</name>
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<name sortKey="Breakspear, Michael" sort="Breakspear, Michael" uniqKey="Breakspear M" first="Michael" last="Breakspear">Michael Breakspear</name>
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<nlm:aff id="af0015">Aix-Marseille Université, Institut de Neurosciences des Systèmes, 13385 Marseille, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>Aix-Marseille Université, Institut de Neurosciences des Systèmes, 13385 Marseille</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="af0020">INSERM, UMR_S 1106, 13385 Marseille, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>INSERM, UMR_S 1106, 13385 Marseille</wicri:regionArea>
</affiliation>
</author>
<author>
<name sortKey="Guye, Maxime" sort="Guye, Maxime" uniqKey="Guye M" first="Maxime" last="Guye">Maxime Guye</name>
<affiliation wicri:level="1">
<nlm:aff id="af0005">Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13385 Marseille, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13385 Marseille</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1">
<nlm:aff id="af0010">APHM, Hôpitaux de la Timone, Pôle d'imagerie Médicale, CEMEREM, 13005 Marseille, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>APHM, Hôpitaux de la Timone, Pôle d'imagerie Médicale, CEMEREM, 13005 Marseille</wicri:regionArea>
</affiliation>
</author>
</analytic>
<series>
<title level="j">NeuroImage : Clinical</title>
<idno type="eISSN">2213-1582</idno>
<imprint>
<date when="2016">2016</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass></textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract" xml:lang="en">
<p>The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain.</p>
<p>We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven righ
<italic>t</italic>
-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome.</p>
<p>In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.</p>
</div>
</front>
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</TEI>
<pmc article-type="research-article">
<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Neuroimage Clin</journal-id>
<journal-id journal-id-type="iso-abbrev">Neuroimage Clin</journal-id>
<journal-title-group>
<journal-title>NeuroImage : Clinical</journal-title>
</journal-title-group>
<issn pub-type="epub">2213-1582</issn>
<publisher>
<publisher-name>Elsevier</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">27330970</article-id>
<article-id pub-id-type="pmc">4909094</article-id>
<article-id pub-id-type="publisher-id">S2213-1582(16)30086-9</article-id>
<article-id pub-id-type="doi">10.1016/j.nicl.2016.05.010</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Regular Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Whole-brain analytic measures of network communication reveal increased structure-function correlation in right temporal lobe epilepsy</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Wirsich</surname>
<given-names>Jonathan</given-names>
</name>
<email>jonathan.wirsich@univ-amu.fr</email>
<xref rid="af0005" ref-type="aff">a</xref>
<xref rid="af0010" ref-type="aff">b</xref>
<xref rid="af0015" ref-type="aff">c</xref>
<xref rid="af0020" ref-type="aff">d</xref>
<xref rid="cr0005" ref-type="corresp"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Perry</surname>
<given-names>Alistair</given-names>
</name>
<email>alistairperry123@gmail.com</email>
<xref rid="af0030" ref-type="aff">f</xref>
<xref rid="af0035" ref-type="aff">g</xref>
<xref rid="af0040" ref-type="aff">h</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ridley</surname>
<given-names>Ben</given-names>
</name>
<email>ben.ridley@univ-amu.fr</email>
<xref rid="af0005" ref-type="aff">a</xref>
<xref rid="af0010" ref-type="aff">b</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Proix</surname>
<given-names>Timothée</given-names>
</name>
<email>timothee.proix@gmail.com</email>
<xref rid="af0015" ref-type="aff">c</xref>
<xref rid="af0020" ref-type="aff">d</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Golos</surname>
<given-names>Mathieu</given-names>
</name>
<email>mathieu.golos@univ-amu.fr</email>
<xref rid="af0015" ref-type="aff">c</xref>
<xref rid="af0020" ref-type="aff">d</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bénar</surname>
<given-names>Christian</given-names>
</name>
<email>christian.benar@univ-amu.fr</email>
<xref rid="af0015" ref-type="aff">c</xref>
<xref rid="af0020" ref-type="aff">d</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ranjeva</surname>
<given-names>Jean-Philippe</given-names>
</name>
<email>jean-philippe.ranjeva@univ-amu.fr</email>
<xref rid="af0005" ref-type="aff">a</xref>
<xref rid="af0010" ref-type="aff">b</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bartolomei</surname>
<given-names>Fabrice</given-names>
</name>
<email>fabrice.bartolomei@ap-hm.fr</email>
<xref rid="af0015" ref-type="aff">c</xref>
<xref rid="af0020" ref-type="aff">d</xref>
<xref rid="af0025" ref-type="aff">e</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Breakspear</surname>
<given-names>Michael</given-names>
</name>
<email>mjbreaks@gmail.com</email>
<xref rid="af0035" ref-type="aff">g</xref>
<xref rid="af0040" ref-type="aff">h</xref>
<xref rid="af0045" ref-type="aff">i</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jirsa</surname>
<given-names>Viktor</given-names>
</name>
<email>viktor.jirsa@univ-amu.fr</email>
<xref rid="af0015" ref-type="aff">c</xref>
<xref rid="af0020" ref-type="aff">d</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Guye</surname>
<given-names>Maxime</given-names>
</name>
<email>maxime.guye@univ-amu.fr</email>
<xref rid="af0005" ref-type="aff">a</xref>
<xref rid="af0010" ref-type="aff">b</xref>
</contrib>
</contrib-group>
<aff id="af0005">
<label>a</label>
Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13385 Marseille, France</aff>
<aff id="af0010">
<label>b</label>
APHM, Hôpitaux de la Timone, Pôle d'imagerie Médicale, CEMEREM, 13005 Marseille, France</aff>
<aff id="af0015">
<label>c</label>
Aix-Marseille Université, Institut de Neurosciences des Systèmes, 13385 Marseille, France</aff>
<aff id="af0020">
<label>d</label>
INSERM, UMR_S 1106, 13385 Marseille, France</aff>
<aff id="af0025">
<label>e</label>
APHM, Hôpitaux de la Timone, Pôle de Neurosciences Cliniques, Service de Neurophysiologie Clinique, 13005 Marseille, France</aff>
<aff id="af0030">
<label>f</label>
Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, NSW, Australia</aff>
<aff id="af0035">
<label>g</label>
School of Psychiatry, University of New South Wales, Sydney, NSW 2052, Australia</aff>
<aff id="af0040">
<label>h</label>
Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006, Australia</aff>
<aff id="af0045">
<label>i</label>
Metro North Mental Health Services, Brisbane, QLD 4006, Australia</aff>
<author-notes>
<corresp id="cr0005">
<label></label>
Corresponding author at: CRMBM UMR 7339, Faculté de Médecine, 27 Boulevard Jean Moulin, 13385 Marseille, France.CRMBM UMR 7339, Faculté de Médecine27 Boulevard Jean MoulinMarseille13385France
<email>jonathan.wirsich@univ-amu.fr</email>
</corresp>
</author-notes>
<pub-date pub-type="pmc-release">
<day>19</day>
<month>5</month>
<year>2016</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on .</pmc-comment>
<pub-date pub-type="collection">
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>19</day>
<month>5</month>
<year>2016</year>
</pub-date>
<volume>11</volume>
<fpage>707</fpage>
<lpage>718</lpage>
<history>
<date date-type="received">
<day>18</day>
<month>9</month>
<year>2015</year>
</date>
<date date-type="rev-recd">
<day>15</day>
<month>3</month>
<year>2016</year>
</date>
<date date-type="accepted">
<day>18</day>
<month>5</month>
<year>2016</year>
</date>
</history>
<permissions>
<copyright-statement>© 2016 Published by Elsevier Inc.</copyright-statement>
<copyright-year>2016</copyright-year>
<copyright-holder></copyright-holder>
<license license-type="CC BY" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p>This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).</license-p>
</license>
</permissions>
<abstract id="ab0005">
<p>The in vivo structure-function relationship is key to understanding brain network reorganization due to pathologies. This relationship is likely to be particularly complex in brain network diseases such as temporal lobe epilepsy, in which disturbed large-scale systems are involved in both transient electrical events and long-lasting functional and structural impairments. Herein, we estimated this relationship by analyzing the correlation between structural connectivity and functional connectivity in terms of analytical network communication parameters. As such, we targeted the gradual topological structure-function reorganization caused by the pathology not only at the whole brain scale but also both in core and peripheral regions of the brain.</p>
<p>We acquired diffusion (dMRI) and resting-state fMRI (rsfMRI) data in seven righ
<italic>t</italic>
-lateralized TLE (rTLE) patients and fourteen healthy controls and analyzed the structure-function relationship by using analytical network communication metrics derived from the structural connectome.</p>
<p>In rTLE patients, we found a widespread hypercorrelated functional network. Network communication analysis revealed greater unspecific branching of the shortest path (search information) in the structural connectome and a higher global correlation between the structural and functional connectivity for the patient group. We also found evidence for a preserved structural rich-club in the patient group. In sum, global augmentation of structure-function correlation might be linked to a smaller functional repertoire in rTLE patients, while sparing the central core of the brain which may represent a pathway that facilitates the spread of seizures.</p>
</abstract>
<trans-abstract xml:lang="fr">
<title>Highlights</title>
<p>
<list list-type="simple">
<list-item id="u0005">
<label></label>
<p>rTLE patients exhibit increased mean search information compared controls.</p>
</list-item>
<list-item id="u0010">
<label></label>
<p>Structural search information best predicts functional connectivity in both groups.</p>
</list-item>
<list-item id="u0015">
<label></label>
<p>Whole brain structure-function correlation is increased in rTLE patients.</p>
</list-item>
<list-item id="u0020">
<label></label>
<p>Structure-function correlation differs in brain periphery but not in the rich club.</p>
</list-item>
</list>
</p>
</trans-abstract>
<kwd-group id="ks0005">
<title>Abbreviations</title>
<kwd>CSD, constrained spherical deconvolution</kwd>
<kwd>CSF, cerebrospinal fluid</kwd>
<kwd>dMRI, diffusion magnetic resonance imaging</kwd>
<kwd>FA, fractional anisotropy</kwd>
<kwd>FCA, analytic functional connectivity</kwd>
<kwd>FCD, functional connectivity dynamics</kwd>
<kwd>FOD, fiber orientation distribution</kwd>
<kwd>NBS, network based statistics</kwd>
<kwd>rsfMRI, resting state functional magnetic resonance imaging</kwd>
<kwd>rTLE, right temporal lobe epilepsy</kwd>
</kwd-group>
<kwd-group id="ks0010">
<title>Keywords</title>
<kwd>Structural connectivity</kwd>
<kwd>Functional connectivity</kwd>
<kwd>Temporal lobe epilepsy</kwd>
<kwd>Network communication</kwd>
<kwd>Rich club</kwd>
<kwd>Network based statistics</kwd>
</kwd-group>
</article-meta>
</front>
<floats-group>
<fig id="f0005">
<label>Fig. 1</label>
<caption>
<p>Illustration of graph metrics to characterize features of the shortest path from A to B: a) weighted path length (summed connection strengths); b) search information (weight path length by paths branching off in one of the shortest path’s nodes) and c) path transitivity (path lengths weighted by additional triangle detours which can be used to arrive at B).</p>
</caption>
<alt-text id="al0005">Fig. 1</alt-text>
<graphic xlink:href="gr1"></graphic>
</fig>
<fig id="f0010">
<label>Fig. 2</label>
<caption>
<p>Network based statistics (NBS) on absolute functional connectivity (t-test rTLE > controls, subnetwork of modified edges threshold T > = 5, p (NBS corrected) < 0.05). Yellow nodes represent a subnetwork hub at nodal degree k > = 5 (considering only subnetwork connections), red nodes represent a degree k < 5.</p>
</caption>
<alt-text id="al0010">Fig. 2</alt-text>
<graphic xlink:href="gr2"></graphic>
</fig>
<fig id="f0015">
<label>Fig. 3</label>
<caption>
<p>a) High degree rich club nodes and their intra-connections at a degree threshold of k = 250, 300 and 330 connections for controls and rTLE patients forming a rich club at different levels (for better visualization 512 regions are projected on the 90 regions of the AAL atlas); b) Rich club coefficient for averaged connectomes (connectome sparsity = 30%, rich club coefficient weighted by streamline counts); c) Subnetwork size (number of nodes) of the largest component as a function of the nodal degree threshold (connectome sparsity = 30%), grey background marks significant difference between the two groups (p < 0.05, two-sided t-test, 10000 permutations of group labels to build the averaged connectome).</p>
</caption>
<alt-text id="al0015">Fig. 3</alt-text>
<graphic xlink:href="gr3"></graphic>
</fig>
<fig id="f0020">
<label>Fig. 4</label>
<caption>
<p>Prediction of functional connectivity a) using a combined model of euclidian distance, path length, path transitivity and search information (contols R = 0.575, rTLE patients R = 0.656, rTLE > controls: p < 0.05, 10000 permutations ) and b) using group averaged search information (controls R = −0.46, rTLE patients R = −0.535, rTLE > controls: p < 0.05, 10000 permutations).</p>
</caption>
<alt-text id="al0020">Fig. 4</alt-text>
<graphic xlink:href="gr4"></graphic>
</fig>
<fig id="f0025">
<label>Fig. 5</label>
<caption>
<p>Prediction of functional connectivity for controls and rTLE patients using a) Euclidian distance, b) search information and c) streamline count based on group averaged connectomes for connections in the altered NBS subnetwork of functional connectivity; Euclidian distance (middle row) and search information (lower row) vs. functional connectivity in three subnetworks at a degree threshold k > 250 splitting the brain in d) Rich club connections, e) Feeder connections and f) Local connections. For detailed correlation values and slope differences see
<xref rid="t0005" ref-type="table">Table 1</xref>
,
<xref rid="t0010" ref-type="table">Table 2</xref>
.</p>
</caption>
<alt-text id="al0025">Fig. 5</alt-text>
<graphic xlink:href="gr5"></graphic>
</fig>
<table-wrap id="t0005" position="float">
<label>Table 1</label>
<caption>
<p>Pearson correlation between functional connectivity and structural derived metrics in the whole brain and in subnetworks (all predictors were significant with P < 10
<sup>− 6</sup>
, group averaged connectivity matrices, NBS: altered NBS subnetwork of functional connectivity rTLE > controls, Rich Club, Feeder and Local: rich club, feeder and local connections for structural connectome sparsitiy 30%, and nodal degree > 250); FCA: analytic functional connectivity, ED: Euclidian distance, PL: Path length, PT: Path transitivity, SI: search information, PP path predictors (path length, path transitivity, search information).</p>
</caption>
<alt-text id="al0030">Table 1</alt-text>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th></th>
<th colspan="2" align="left">Whole-brain
<hr></hr>
</th>
<th colspan="2" align="left">NBS
<hr></hr>
</th>
<th colspan="2" align="left">Rich Club
<hr></hr>
</th>
<th colspan="2" align="left">Feeder
<hr></hr>
</th>
<th colspan="2" align="left">Local
<hr></hr>
</th>
</tr>
<tr>
<th align="left">Controls</th>
<th align="left">rTLE</th>
<th align="left">Controls</th>
<th align="left">rTLE</th>
<th align="left">Controls</th>
<th align="left">rTLE</th>
<th align="left">Controls</th>
<th align="left">rTLE</th>
<th align="left">Controls</th>
<th align="left">rTLE</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Streamline count (log)</td>
<td align="left">0.375</td>
<td align="left">0.433</td>
<td align="left">0.714</td>
<td align="left">0.726</td>
<td align="left">0.331</td>
<td align="left">0.332</td>
<td align="left">0.356</td>
<td align="left">0.352</td>
<td align="left">0.413</td>
<td align="left">0.451</td>
</tr>
<tr>
<td align="left">FCA</td>
<td align="left">0.349</td>
<td align="left">0.413</td>
<td align="left">0.705</td>
<td align="left">0.717</td>
<td align="left">0.315</td>
<td align="left">0.321</td>
<td align="left">0.315</td>
<td align="left">0.317</td>
<td align="left">0.354</td>
<td align="left">0.404</td>
</tr>
<tr>
<td align="left">ED</td>
<td align="left">− 0.531</td>
<td align="left">− 0.619</td>
<td align="left">− 0.790</td>
<td align="left">− 0.912</td>
<td align="left">− 0.635</td>
<td align="left">− 0.748</td>
<td align="left">− 0.601</td>
<td align="left">− 0.676</td>
<td align="left">− 0.619</td>
<td align="left">− 0.676</td>
</tr>
<tr>
<td align="left">PL</td>
<td align="left">− 0.227</td>
<td align="left">− 0.289</td>
<td align="left">− 0.594</td>
<td align="left">− 0.615</td>
<td align="left">− 0.437</td>
<td align="left">− 0.368</td>
<td align="left">− 0.274</td>
<td align="left">− 0.252</td>
<td align="left">− 0.177</td>
<td align="left">− 0.208</td>
</tr>
<tr>
<td align="left">PT</td>
<td align="left">0.254</td>
<td align="left">0.337</td>
<td align="left">0.629</td>
<td align="left">0.719</td>
<td align="left">0.148</td>
<td align="left">0.162</td>
<td align="left">0.120</td>
<td align="left">0.131</td>
<td align="left">0.026</td>
<td align="left">0.134</td>
</tr>
<tr>
<td align="left">SI (log)</td>
<td align="left">− 0.460</td>
<td align="left">− 0.535</td>
<td align="left">− 0.773</td>
<td align="left">− 0.833</td>
<td align="left">− 0.413</td>
<td align="left">− 0.425</td>
<td align="left">− 0.496</td>
<td align="left">− 0.482</td>
<td align="left">− 0.545</td>
<td align="left">− 0.559</td>
</tr>
<tr>
<td align="left">Combined PP with ED</td>
<td align="left">0.575</td>
<td align="left">0.656</td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="t0010" position="float">
<label>Table 2</label>
<caption>
<p>P-values for permutation of group labels of the averaged connectome on the regression slopes of a linear fit (Controls vs. rTLE, n = 10.000, *p < 0.05); NBS: altered NBS subnetwork of functional connectivity rTLE > controls, Rich Club, Feeder and Local: rich club, feeder and local connections for structural connectome sparsitiy 30%, and nodal degree > 250), FCA: analytic functional connectivity, ED: Euclidian distance, PL: Path length, PT: Path transitivity, SI: search information, PP combined path predictors: path length, path transitivity, search information.</p>
</caption>
<alt-text id="al0035">Table 2</alt-text>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th></th>
<th align="left">Whole-brain</th>
<th align="left">NBS</th>
<th align="left">Rich Club</th>
<th align="left">Feeder</th>
<th align="left">Local</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left">Streamline count (log)</td>
<td align="left">0.0020
<sup></sup>
</td>
<td align="char">0.0013
<sup></sup>
</td>
<td align="char">0.3149</td>
<td align="char">0.4628</td>
<td align="char">0.0028
<sup></sup>
</td>
</tr>
<tr>
<td align="left">FCA</td>
<td align="left">0.0055
<sup></sup>
</td>
<td align="char">0.0037
<sup></sup>
</td>
<td align="char">0.3673</td>
<td align="char">0.6393</td>
<td align="char">0.0041
<sup></sup>
</td>
</tr>
<tr>
<td align="left">ED</td>
<td align="left">0.0111
<sup></sup>
</td>
<td align="char">0.0074
<sup></sup>
</td>
<td align="char">0.0935</td>
<td align="char">0.0496
<sup></sup>
</td>
<td align="char">0.0316
<sup></sup>
</td>
</tr>
<tr>
<td align="left">PL</td>
<td align="left">0.1942</td>
<td align="char">0.0278
<sup></sup>
</td>
<td align="char">0.4623</td>
<td align="char">0.6588</td>
<td align="char">0.2612</td>
</tr>
<tr>
<td align="left">PT</td>
<td align="left">0.0043
<sup></sup>
</td>
<td align="char">0.0017
<sup></sup>
</td>
<td align="char">0.4148</td>
<td align="char">0.6738</td>
<td align="char">0.0009*</td>
</tr>
<tr>
<td align="left">SI (log)</td>
<td align="left">0.0188
<sup></sup>
</td>
<td align="char">0.0025
<sup></sup>
</td>
<td align="char">0.4656</td>
<td align="char">0.3579</td>
<td align="char">0.0236*</td>
</tr>
<tr>
<td align="left">Combined PP with ED</td>
<td align="left">0.0019
<sup></sup>
</td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
<td align="left"></td>
</tr>
</tbody>
</table>
</table-wrap>
</floats-group>
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