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highspeed-fmriprep
ответвлено от lnnrtwttkhn/highspeed-fmriprep
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10.12751/g-node.0ft06t
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    50. 

  50. <body>
    51. 

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  53. <nav class="navbar fixed-top navbar-expand-lg navbar-light bg-light">
    54. 

  54. <div class="collapse navbar-collapse">
    55. 

  55.     <ul class="navbar-nav">
    56. 

  56.         <li class="nav-item"><a class="nav-link" href="#Summary">Summary</a></li>
    57. 

  57.         <li class="nav-item"><a class="nav-link" href="#Anatomical">Anatomical</a></li>
    58. 

  58.         <li class="nav-item dropdown">
    59. 

  59.             <a class="nav-link dropdown-toggle" id="navbarFunctional" data-toggle="dropdown" aria-haspopup="true" aria-expanded="false" href="#">Functional</a>
    60. 

  60.             <div class="dropdown-menu" aria-labelledby="navbarFunctional">
    61. 

  61.                 <a class="dropdown-item" href="#ses-01_task-highspeed_rec-prenorm_run-01"> Session: 01 Task: highspeed Reconstruction: prenorm Run: 01</a>
    62. 

  62.                 <a class="dropdown-item" href="#ses-01_task-highspeed_rec-prenorm_run-02"> Session: 01 Task: highspeed Reconstruction: prenorm Run: 02</a>
    63. 

  63.                 <a class="dropdown-item" href="#ses-01_task-highspeed_rec-prenorm_run-03"> Session: 01 Task: highspeed Reconstruction: prenorm Run: 03</a>
    64. 

  64.                 <a class="dropdown-item" href="#ses-01_task-highspeed_rec-prenorm_run-04"> Session: 01 Task: highspeed Reconstruction: prenorm Run: 04</a>
    65. 

  65.                 <a class="dropdown-item" href="#ses-01_task-rest_rec-prenorm_run-post"> Session: 01 Task: rest Reconstruction: prenorm Run: post</a>
    66. 

  66.                 <a class="dropdown-item" href="#ses-01_task-rest_rec-prenorm_run-pre"> Session: 01 Task: rest Reconstruction: prenorm Run: pre</a>
    67. 

  67.                 <a class="dropdown-item" href="#ses-02_task-highspeed_rec-prenorm_run-01"> Session: 02 Task: highspeed Reconstruction: prenorm Run: 01</a>
    68. 

  68.                 <a class="dropdown-item" href="#ses-02_task-highspeed_rec-prenorm_run-02"> Session: 02 Task: highspeed Reconstruction: prenorm Run: 02</a>
    69. 

  69.                 <a class="dropdown-item" href="#ses-02_task-highspeed_rec-prenorm_run-03"> Session: 02 Task: highspeed Reconstruction: prenorm Run: 03</a>
    70. 

  70.                 <a class="dropdown-item" href="#ses-02_task-highspeed_rec-prenorm_run-04"> Session: 02 Task: highspeed Reconstruction: prenorm Run: 04</a>
    71. 

  71.                 <a class="dropdown-item" href="#ses-02_task-rest_rec-prenorm_run-post"> Session: 02 Task: rest Reconstruction: prenorm Run: post</a>
    72. 

  72.                 <a class="dropdown-item" href="#ses-02_task-rest_rec-prenorm_run-pre"> Session: 02 Task: rest Reconstruction: prenorm Run: pre</a>
    73. 

  73.             </div>
    74. 

  74.         </li>
    75. 

  75.         <li class="nav-item"><a class="nav-link" href="#About">About</a></li>
    76. 

  76.         <li class="nav-item"><a class="nav-link" href="#boilerplate">Methods</a></li>
    77. 

  77.         <li class="nav-item"><a class="nav-link" href="#errors">Errors</a></li>
    78. 

  78.     </ul>
    79. 

  79. </div>
    80. 

  80. </nav>
    81. 

  81. <noscript>
    82. 

  82.     <h1 class="text-danger"> The navigation menu uses Javascript. Without it this report might not work as expected </h1>
    83. 

  83. </noscript>
    84. 

  84. 

  85.     <div id="Summary">
    86. 

  86.     <h1 class="sub-report-title">Summary</h1>
    87. 

  87. <ul class="elem-desc">
    88. 

  88. 		<li>Subject ID: sub-34</li>
    89. 

  89. 		<li>Structural images: 2 T1-weighted </li>
    90. 

  90. 		<li>Functional series: 12</li>
    91. 

  91. 		<ul class="elem-desc">
    92. 

  92. 			<li>Task: highspeed (8 runs)</li>
    93. 

  93. 			<li>Task: rest (4 runs)</li>
    94. 

  94. 		</ul>
    95. 

  95. 		<li>Resampling targets: T1w, fsnative, MNI152NLin2009cAsym, fsaverage
    96. 

  96. 		<li>FreeSurfer reconstruction: Run by fMRIPrep</li>
    97. 

  97. 	</ul>    </div>
    98. 

  98.     <div id="Anatomical">
    99. 

  99.     <h1 class="sub-report-title">Anatomical</h1>
    100. 

  100. <h3 class="elem-title">Anatomical Conformation</h3>
    101. 

  101. 		<ul class="elem-desc">
    102. 

  102. 			<li>Input T1w images: 2</li>
    103. 

  103. 			<li>Output orientation: RAS</li>
    104. 

  104. 			<li>Output dimensions: 192x256x256</li>
    105. 

  105. 			<li>Output voxel size: 1mm x 1mm x 1mm</li>
    106. 

  106. 			<li>Discarded images: 0</li>
    107. 

  107. 

  108. 		</ul><h3 class="elem-title">Brain mask and brain tissue segmentation of the T1w</h3><p class="elem-desc">This panel shows the template T1-weighted image (if several T1w images were found), with contours delineating the detected brain mask and brain tissue segmentations.<p><br />                        <div class="elem-image">
    109. 

  109.                         <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_seg_brainmask.svg">filename:sub-34/figures/sub-34_seg_brainmask.svg</object>
    110. 

  110.                         </div>
    111. 

  111.                         <div class="elem-filename">
    112. 

  112.                             Get figure file: <a href="./sub-34/figures/sub-34_seg_brainmask.svg" target="_blank">sub-34/figures/sub-34_seg_brainmask.svg</a>
    113. 

  113.                         </div>
    114. 

  114. <h3 class="elem-title">T1 to MNI registration</h3><p class="elem-desc">Nonlinear mapping of the T1w image into MNI space. Hover on the panel with the mouse to transition between both spaces.<p><br />                        <div class="elem-image">
    115. 

  115.                         <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_t1_2_mni.svg">filename:sub-34/figures/sub-34_t1_2_mni.svg</object>
    116. 

  116.                         </div>
    117. 

  117.                         <div class="elem-filename">
    118. 

  118.                             Get figure file: <a href="./sub-34/figures/sub-34_t1_2_mni.svg" target="_blank">sub-34/figures/sub-34_t1_2_mni.svg</a>
    119. 

  119.                         </div>
    120. 

  120. <h3 class="elem-title">Surface reconstruction</h3><p class="elem-desc">Surfaces (white and pial) reconstructed with FreeSurfer (<code>recon-all</code>) overlaid on the participant's T1w template.<p><br />                        <div class="elem-image">
    121. 

  121.                         <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_reconall.svg">filename:sub-34/figures/sub-34_reconall.svg</object>
    122. 

  122.                         </div>
    123. 

  123.                         <div class="elem-filename">
    124. 

  124.                             Get figure file: <a href="./sub-34/figures/sub-34_reconall.svg" target="_blank">sub-34/figures/sub-34_reconall.svg</a>
    125. 

  125.                         </div>
    126. 

  126.     </div>
    127. 

  127.     <div id="Functional">
    128. 

  128.     <h1 class="sub-report-title">Functional</h1>
    129. 

  129.             <div id="ses-01_task-highspeed_rec-prenorm_run-01">
    130. 

  130.                 <h2 class="run-title">Reports for  Session: 01 Task: highspeed Reconstruction: prenorm Run: 01</h2>
    131. 

  131. <h3 class="elem-title">Summary</h3>
    132. 

  132. 		<ul class="elem-desc">
    133. 

  133. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    134. 

  134. 			<li>Slice timing correction: Applied</li>
    135. 

  135. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    136. 

  136. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    137. 

  137. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    138. 

  138. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, non_steady_state_outlier00, non_steady_state_outlier01, non_steady_state_outlier02, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    139. 

  139. 		</ul><h3 class="elem-title">Note on orientation: qform matrix overwritten</h3>
    140. 

  140. 			<p class="elem-desc">The qform has been copied from sform.</p><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    141. 

  141.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_sdc_epi.svg">
    142. 

  142.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    143. 

  143.                             </div>
    144. 

  144.                             <div class="elem-filename">
    145. 

  145.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_sdc_epi.svg</a>
    146. 

  146.                             </div>
    147. 

  147. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    148. 

  148.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_rois.svg">
    149. 

  149.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    150. 

  150.                             </div>
    151. 

  151.                             <div class="elem-filename">
    152. 

  152.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_rois.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_rois.svg</a>
    153. 

  153.                             </div>
    154. 

  154. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    155. 

  155.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_bbregister.svg">
    156. 

  156.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    157. 

  157.                             </div>
    158. 

  158.                             <div class="elem-filename">
    159. 

  159.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_bbregister.svg</a>
    160. 

  160.                             </div>
    161. 

  161. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    162. 

  162.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_carpetplot.svg">
    163. 

  163.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    164. 

  164.                             </div>
    165. 

  165.                             <div class="elem-filename">
    166. 

  166.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-01_carpetplot.svg</a>
    167. 

  167.                             </div>
    168. 

  168.             </div>
    169. 

  169.             <div id="ses-01_task-highspeed_rec-prenorm_run-02">
    170. 

  170.                 <h2 class="run-title">Reports for  Session: 01 Task: highspeed Reconstruction: prenorm Run: 02</h2>
    171. 

  171. <h3 class="elem-title">Summary</h3>
    172. 

  172. 		<ul class="elem-desc">
    173. 

  173. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    174. 

  174. 			<li>Slice timing correction: Applied</li>
    175. 

  175. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    176. 

  176. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    177. 

  177. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    178. 

  178. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    179. 

  179. 		</ul><h3 class="elem-title">Note on orientation: qform matrix overwritten</h3>
    180. 

  180. 			<p class="elem-desc">The qform has been copied from sform.</p><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    181. 

  181.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_sdc_epi.svg">
    182. 

  182.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    183. 

  183.                             </div>
    184. 

  184.                             <div class="elem-filename">
    185. 

  185.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_sdc_epi.svg</a>
    186. 

  186.                             </div>
    187. 

  187. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    188. 

  188.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_rois.svg">
    189. 

  189.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    190. 

  190.                             </div>
    191. 

  191.                             <div class="elem-filename">
    192. 

  192.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_rois.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_rois.svg</a>
    193. 

  193.                             </div>
    194. 

  194. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    195. 

  195.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_bbregister.svg">
    196. 

  196.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    197. 

  197.                             </div>
    198. 

  198.                             <div class="elem-filename">
    199. 

  199.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_bbregister.svg</a>
    200. 

  200.                             </div>
    201. 

  201. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    202. 

  202.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_carpetplot.svg">
    203. 

  203.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    204. 

  204.                             </div>
    205. 

  205.                             <div class="elem-filename">
    206. 

  206.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-02_carpetplot.svg</a>
    207. 

  207.                             </div>
    208. 

  208.             </div>
    209. 

  209.             <div id="ses-01_task-highspeed_rec-prenorm_run-03">
    210. 

  210.                 <h2 class="run-title">Reports for  Session: 01 Task: highspeed Reconstruction: prenorm Run: 03</h2>
    211. 

  211. <h3 class="elem-title">Summary</h3>
    212. 

  212. 		<ul class="elem-desc">
    213. 

  213. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    214. 

  214. 			<li>Slice timing correction: Applied</li>
    215. 

  215. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    216. 

  216. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    217. 

  217. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    218. 

  218. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    219. 

  219. 		</ul><h3 class="elem-title">Note on orientation: qform matrix overwritten</h3>
    220. 

  220. 			<p class="elem-desc">The qform has been copied from sform.</p><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    221. 

  221.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_sdc_epi.svg">
    222. 

  222.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    223. 

  223.                             </div>
    224. 

  224.                             <div class="elem-filename">
    225. 

  225.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_sdc_epi.svg</a>
    226. 

  226.                             </div>
    227. 

  227. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    228. 

  228.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_rois.svg">
    229. 

  229.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    230. 

  230.                             </div>
    231. 

  231.                             <div class="elem-filename">
    232. 

  232.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_rois.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_rois.svg</a>
    233. 

  233.                             </div>
    234. 

  234. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    235. 

  235.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_bbregister.svg">
    236. 

  236.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    237. 

  237.                             </div>
    238. 

  238.                             <div class="elem-filename">
    239. 

  239.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_bbregister.svg</a>
    240. 

  240.                             </div>
    241. 

  241. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    242. 

  242.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_carpetplot.svg">
    243. 

  243.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    244. 

  244.                             </div>
    245. 

  245.                             <div class="elem-filename">
    246. 

  246.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-03_carpetplot.svg</a>
    247. 

  247.                             </div>
    248. 

  248.             </div>
    249. 

  249.             <div id="ses-01_task-highspeed_rec-prenorm_run-04">
    250. 

  250.                 <h2 class="run-title">Reports for  Session: 01 Task: highspeed Reconstruction: prenorm Run: 04</h2>
    251. 

  251. <h3 class="elem-title">Summary</h3>
    252. 

  252. 		<ul class="elem-desc">
    253. 

  253. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    254. 

  254. 			<li>Slice timing correction: Applied</li>
    255. 

  255. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    256. 

  256. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    257. 

  257. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    258. 

  258. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    259. 

  259. 		</ul><h3 class="elem-title">Note on orientation: qform matrix overwritten</h3>
    260. 

  260. 			<p class="elem-desc">The qform has been copied from sform.</p><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    261. 

  261.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_sdc_epi.svg">
    262. 

  262.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    263. 

  263.                             </div>
    264. 

  264.                             <div class="elem-filename">
    265. 

  265.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_sdc_epi.svg</a>
    266. 

  266.                             </div>
    267. 

  267. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    268. 

  268.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_rois.svg">
    269. 

  269.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    270. 

  270.                             </div>
    271. 

  271.                             <div class="elem-filename">
    272. 

  272.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_rois.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_rois.svg</a>
    273. 

  273.                             </div>
    274. 

  274. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    275. 

  275.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_bbregister.svg">
    276. 

  276.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    277. 

  277.                             </div>
    278. 

  278.                             <div class="elem-filename">
    279. 

  279.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_bbregister.svg</a>
    280. 

  280.                             </div>
    281. 

  281. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    282. 

  282.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_carpetplot.svg">
    283. 

  283.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    284. 

  284.                             </div>
    285. 

  285.                             <div class="elem-filename">
    286. 

  286.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-highspeed_rec-prenorm_run-04_carpetplot.svg</a>
    287. 

  287.                             </div>
    288. 

  288.             </div>
    289. 

  289.             <div id="ses-01_task-rest_rec-prenorm_run-post">
    290. 

  290.                 <h2 class="run-title">Reports for  Session: 01 Task: rest Reconstruction: prenorm Run: post</h2>
    291. 

  291. <h3 class="elem-title">Summary</h3>
    292. 

  292. 		<ul class="elem-desc">
    293. 

  293. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    294. 

  294. 			<li>Slice timing correction: Applied</li>
    295. 

  295. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    296. 

  296. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    297. 

  297. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    298. 

  298. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, non_steady_state_outlier00, non_steady_state_outlier01, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    299. 

  299. 		</ul><h3 class="elem-title">Note on orientation: qform matrix overwritten</h3>
    300. 

  300. 			<p class="elem-desc">The qform has been copied from sform.</p><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    301. 

  301.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_sdc_epi.svg">
    302. 

  302.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    303. 

  303.                             </div>
    304. 

  304.                             <div class="elem-filename">
    305. 

  305.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_sdc_epi.svg</a>
    306. 

  306.                             </div>
    307. 

  307. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    308. 

  308.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_rois.svg">
    309. 

  309.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    310. 

  310.                             </div>
    311. 

  311.                             <div class="elem-filename">
    312. 

  312.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_rois.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_rois.svg</a>
    313. 

  313.                             </div>
    314. 

  314. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    315. 

  315.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_bbregister.svg">
    316. 

  316.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    317. 

  317.                             </div>
    318. 

  318.                             <div class="elem-filename">
    319. 

  319.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_bbregister.svg</a>
    320. 

  320.                             </div>
    321. 

  321. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    322. 

  322.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_carpetplot.svg">
    323. 

  323.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    324. 

  324.                             </div>
    325. 

  325.                             <div class="elem-filename">
    326. 

  326.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-post_carpetplot.svg</a>
    327. 

  327.                             </div>
    328. 

  328.             </div>
    329. 

  329.             <div id="ses-01_task-rest_rec-prenorm_run-pre">
    330. 

  330.                 <h2 class="run-title">Reports for  Session: 01 Task: rest Reconstruction: prenorm Run: pre</h2>
    331. 

  331. <h3 class="elem-title">Summary</h3>
    332. 

  332. 		<ul class="elem-desc">
    333. 

  333. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    334. 

  334. 			<li>Slice timing correction: Applied</li>
    335. 

  335. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    336. 

  336. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    337. 

  337. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    338. 

  338. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    339. 

  339. 		</ul><h3 class="elem-title">Note on orientation: qform matrix overwritten</h3>
    340. 

  340. 			<p class="elem-desc">The qform has been copied from sform.</p><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    341. 

  341.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_sdc_epi.svg">
    342. 

  342.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    343. 

  343.                             </div>
    344. 

  344.                             <div class="elem-filename">
    345. 

  345.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_sdc_epi.svg</a>
    346. 

  346.                             </div>
    347. 

  347. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    348. 

  348.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_rois.svg">
    349. 

  349.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    350. 

  350.                             </div>
    351. 

  351.                             <div class="elem-filename">
    352. 

  352.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_rois.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_rois.svg</a>
    353. 

  353.                             </div>
    354. 

  354. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    355. 

  355.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_bbregister.svg">
    356. 

  356.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    357. 

  357.                             </div>
    358. 

  358.                             <div class="elem-filename">
    359. 

  359.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_bbregister.svg</a>
    360. 

  360.                             </div>
    361. 

  361. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    362. 

  362.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_carpetplot.svg">
    363. 

  363.                             Problem loading figure sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    364. 

  364.                             </div>
    365. 

  365.                             <div class="elem-filename">
    366. 

  366.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-01_task-rest_rec-prenorm_run-pre_carpetplot.svg</a>
    367. 

  367.                             </div>
    368. 

  368.             </div>
    369. 

  369.             <div id="ses-02_task-highspeed_rec-prenorm_run-01">
    370. 

  370.                 <h2 class="run-title">Reports for  Session: 02 Task: highspeed Reconstruction: prenorm Run: 01</h2>
    371. 

  371. <h3 class="elem-title">Summary</h3>
    372. 

  372. 		<ul class="elem-desc">
    373. 

  373. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    374. 

  374. 			<li>Slice timing correction: Applied</li>
    375. 

  375. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    376. 

  376. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    377. 

  377. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    378. 

  378. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, non_steady_state_outlier00, non_steady_state_outlier01, non_steady_state_outlier02, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    379. 

  379. 		</ul><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    380. 

  380.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_sdc_epi.svg">
    381. 

  381.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    382. 

  382.                             </div>
    383. 

  383.                             <div class="elem-filename">
    384. 

  384.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_sdc_epi.svg</a>
    385. 

  385.                             </div>
    386. 

  386. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    387. 

  387.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_rois.svg">
    388. 

  388.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    389. 

  389.                             </div>
    390. 

  390.                             <div class="elem-filename">
    391. 

  391.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_rois.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_rois.svg</a>
    392. 

  392.                             </div>
    393. 

  393. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    394. 

  394.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_bbregister.svg">
    395. 

  395.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    396. 

  396.                             </div>
    397. 

  397.                             <div class="elem-filename">
    398. 

  398.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_bbregister.svg</a>
    399. 

  399.                             </div>
    400. 

  400. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    401. 

  401.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_carpetplot.svg">
    402. 

  402.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    403. 

  403.                             </div>
    404. 

  404.                             <div class="elem-filename">
    405. 

  405.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-01_carpetplot.svg</a>
    406. 

  406.                             </div>
    407. 

  407.             </div>
    408. 

  408.             <div id="ses-02_task-highspeed_rec-prenorm_run-02">
    409. 

  409.                 <h2 class="run-title">Reports for  Session: 02 Task: highspeed Reconstruction: prenorm Run: 02</h2>
    410. 

  410. <h3 class="elem-title">Summary</h3>
    411. 

  411. 		<ul class="elem-desc">
    412. 

  412. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    413. 

  413. 			<li>Slice timing correction: Applied</li>
    414. 

  414. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    415. 

  415. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    416. 

  416. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    417. 

  417. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    418. 

  418. 		</ul><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    419. 

  419.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_sdc_epi.svg">
    420. 

  420.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    421. 

  421.                             </div>
    422. 

  422.                             <div class="elem-filename">
    423. 

  423.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_sdc_epi.svg</a>
    424. 

  424.                             </div>
    425. 

  425. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    426. 

  426.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_rois.svg">
    427. 

  427.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    428. 

  428.                             </div>
    429. 

  429.                             <div class="elem-filename">
    430. 

  430.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_rois.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_rois.svg</a>
    431. 

  431.                             </div>
    432. 

  432. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    433. 

  433.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_bbregister.svg">
    434. 

  434.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    435. 

  435.                             </div>
    436. 

  436.                             <div class="elem-filename">
    437. 

  437.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_bbregister.svg</a>
    438. 

  438.                             </div>
    439. 

  439. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    440. 

  440.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_carpetplot.svg">
    441. 

  441.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    442. 

  442.                             </div>
    443. 

  443.                             <div class="elem-filename">
    444. 

  444.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-02_carpetplot.svg</a>
    445. 

  445.                             </div>
    446. 

  446.             </div>
    447. 

  447.             <div id="ses-02_task-highspeed_rec-prenorm_run-03">
    448. 

  448.                 <h2 class="run-title">Reports for  Session: 02 Task: highspeed Reconstruction: prenorm Run: 03</h2>
    449. 

  449. <h3 class="elem-title">Summary</h3>
    450. 

  450. 		<ul class="elem-desc">
    451. 

  451. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    452. 

  452. 			<li>Slice timing correction: Applied</li>
    453. 

  453. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    454. 

  454. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    455. 

  455. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    456. 

  456. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    457. 

  457. 		</ul><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    458. 

  458.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_sdc_epi.svg">
    459. 

  459.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    460. 

  460.                             </div>
    461. 

  461.                             <div class="elem-filename">
    462. 

  462.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_sdc_epi.svg</a>
    463. 

  463.                             </div>
    464. 

  464. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    465. 

  465.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_rois.svg">
    466. 

  466.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    467. 

  467.                             </div>
    468. 

  468.                             <div class="elem-filename">
    469. 

  469.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_rois.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_rois.svg</a>
    470. 

  470.                             </div>
    471. 

  471. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    472. 

  472.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_bbregister.svg">
    473. 

  473.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    474. 

  474.                             </div>
    475. 

  475.                             <div class="elem-filename">
    476. 

  476.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_bbregister.svg</a>
    477. 

  477.                             </div>
    478. 

  478. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    479. 

  479.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_carpetplot.svg">
    480. 

  480.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    481. 

  481.                             </div>
    482. 

  482.                             <div class="elem-filename">
    483. 

  483.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-03_carpetplot.svg</a>
    484. 

  484.                             </div>
    485. 

  485.             </div>
    486. 

  486.             <div id="ses-02_task-highspeed_rec-prenorm_run-04">
    487. 

  487.                 <h2 class="run-title">Reports for  Session: 02 Task: highspeed Reconstruction: prenorm Run: 04</h2>
    488. 

  488. <h3 class="elem-title">Summary</h3>
    489. 

  489. 		<ul class="elem-desc">
    490. 

  490. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    491. 

  491. 			<li>Slice timing correction: Applied</li>
    492. 

  492. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    493. 

  493. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    494. 

  494. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    495. 

  495. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, cosine03, cosine04, cosine05, cosine06, cosine07, cosine08, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    496. 

  496. 		</ul><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    497. 

  497.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_sdc_epi.svg">
    498. 

  498.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    499. 

  499.                             </div>
    500. 

  500.                             <div class="elem-filename">
    501. 

  501.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_sdc_epi.svg</a>
    502. 

  502.                             </div>
    503. 

  503. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    504. 

  504.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_rois.svg">
    505. 

  505.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    506. 

  506.                             </div>
    507. 

  507.                             <div class="elem-filename">
    508. 

  508.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_rois.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_rois.svg</a>
    509. 

  509.                             </div>
    510. 

  510. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    511. 

  511.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_bbregister.svg">
    512. 

  512.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    513. 

  513.                             </div>
    514. 

  514.                             <div class="elem-filename">
    515. 

  515.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_bbregister.svg</a>
    516. 

  516.                             </div>
    517. 

  517. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    518. 

  518.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_carpetplot.svg">
    519. 

  519.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    520. 

  520.                             </div>
    521. 

  521.                             <div class="elem-filename">
    522. 

  522.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-highspeed_rec-prenorm_run-04_carpetplot.svg</a>
    523. 

  523.                             </div>
    524. 

  524.             </div>
    525. 

  525.             <div id="ses-02_task-rest_rec-prenorm_run-post">
    526. 

  526.                 <h2 class="run-title">Reports for  Session: 02 Task: rest Reconstruction: prenorm Run: post</h2>
    527. 

  527. <h3 class="elem-title">Summary</h3>
    528. 

  528. 		<ul class="elem-desc">
    529. 

  529. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    530. 

  530. 			<li>Slice timing correction: Applied</li>
    531. 

  531. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    532. 

  532. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    533. 

  533. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    534. 

  534. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    535. 

  535. 		</ul><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    536. 

  536.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_sdc_epi.svg">
    537. 

  537.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    538. 

  538.                             </div>
    539. 

  539.                             <div class="elem-filename">
    540. 

  540.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_sdc_epi.svg</a>
    541. 

  541.                             </div>
    542. 

  542. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    543. 

  543.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_rois.svg">
    544. 

  544.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    545. 

  545.                             </div>
    546. 

  546.                             <div class="elem-filename">
    547. 

  547.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_rois.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_rois.svg</a>
    548. 

  548.                             </div>
    549. 

  549. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    550. 

  550.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_bbregister.svg">
    551. 

  551.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    552. 

  552.                             </div>
    553. 

  553.                             <div class="elem-filename">
    554. 

  554.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_bbregister.svg</a>
    555. 

  555.                             </div>
    556. 

  556. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    557. 

  557.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_carpetplot.svg">
    558. 

  558.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    559. 

  559.                             </div>
    560. 

  560.                             <div class="elem-filename">
    561. 

  561.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-post_carpetplot.svg</a>
    562. 

  562.                             </div>
    563. 

  563.             </div>
    564. 

  564.             <div id="ses-02_task-rest_rec-prenorm_run-pre">
    565. 

  565.                 <h2 class="run-title">Reports for  Session: 02 Task: rest Reconstruction: prenorm Run: pre</h2>
    566. 

  566. <h3 class="elem-title">Summary</h3>
    567. 

  567. 		<ul class="elem-desc">
    568. 

  568. 			<li>Phase-encoding (PE) direction: Anterior-Posterior</li>
    569. 

  569. 			<li>Slice timing correction: Applied</li>
    570. 

  570. 			<li>Susceptibility distortion correction: PEB/PEPOLAR (phase-encoding based / PE-POLARity)</li>
    571. 

  571. 			<li>Registration: FreeSurfer <code>bbregister</code> (boundary-based registration, BBR) - 6 dof</li>
    572. 

  572. 			<li>Functional series resampled to spaces: T1w, fsnative, template, fsaverage</li>
    573. 

  573. 			<li>Confounds collected: csf, white_matter, global_signal, std_dvars, dvars, framewise_displacement, t_comp_cor_00, t_comp_cor_01, t_comp_cor_02, t_comp_cor_03, t_comp_cor_04, t_comp_cor_05, a_comp_cor_00, a_comp_cor_01, a_comp_cor_02, a_comp_cor_03, a_comp_cor_04, a_comp_cor_05, cosine00, cosine01, cosine02, non_steady_state_outlier00, non_steady_state_outlier01, trans_x, trans_y, trans_z, rot_x, rot_y, rot_z</li>
    574. 

  574. 		</ul><h3 class="elem-title">Susceptibility distortion correction</h3><p class="elem-desc">Results of performing susceptibility distortion correction (SDC) on the EPI<p>                            <div class="elem-image">
    575. 

  575.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_sdc_epi.svg">
    576. 

  576.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_sdc_epi.svg. If the link below works, please try reloading the report in your browser.</object>
    577. 

  577.                             </div>
    578. 

  578.                             <div class="elem-filename">
    579. 

  579.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_sdc_epi.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_sdc_epi.svg</a>
    580. 

  580.                             </div>
    581. 

  581. <h3 class="elem-title">ROIs in BOLD space</h3><p class="elem-desc">Brain mask calculated on the BOLD signal (red contour), along with the masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative CSF and white-matter mask for extracting physiological and movement confounds. <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels within a heavily-eroded brain-mask.<p>                            <div class="elem-image">
    582. 

  582.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_rois.svg">
    583. 

  583.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_rois.svg. If the link below works, please try reloading the report in your browser.</object>
    584. 

  584.                             </div>
    585. 

  585.                             <div class="elem-filename">
    586. 

  586.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_rois.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_rois.svg</a>
    587. 

  587.                             </div>
    588. 

  588. <h3 class="elem-title">EPI to T1 registration</h3><p class="elem-desc"><code>bbregister</code> was used to generate transformations from EPI-space to T1w-space<p>                            <div class="elem-image">
    589. 

  589.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_bbregister.svg">
    590. 

  590.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_bbregister.svg. If the link below works, please try reloading the report in your browser.</object>
    591. 

  591.                             </div>
    592. 

  592.                             <div class="elem-filename">
    593. 

  593.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_bbregister.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_bbregister.svg</a>
    594. 

  594.                             </div>
    595. 

  595. <h3 class="elem-title">BOLD Summary</h3><p class="elem-desc">Summary statistics are plotted, which may reveal trends or artifacts in the BOLD data. Global signals calculated within the whole-brain (GS), within the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD signal in their corresponding masks. DVARS and FD show the standardized DVARS and framewise-displacement measures for each time point.<br />A carpet plot shows the time series for all voxels within the brain mask. Voxels are grouped into cortical (blue), and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF (red), indicated by the color map on the left-hand side.<p>                            <div class="elem-image">
    596. 

  596.                             <object class="svg-reportlet" type="image/svg+xml" data="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_carpetplot.svg">
    597. 

  597.                             Problem loading figure sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_carpetplot.svg. If the link below works, please try reloading the report in your browser.</object>
    598. 

  598.                             </div>
    599. 

  599.                             <div class="elem-filename">
    600. 

  600.                                 Get figure file: <a href="./sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_carpetplot.svg" target="_blank">sub-34/figures/sub-34_ses-02_task-rest_rec-prenorm_run-pre_carpetplot.svg</a>
    601. 

  601.                             </div>
    602. 

  602.             </div>
    603. 

  603.     </div>
    604. 

  604.     <div id="About">
    605. 

  605.     <h1 class="sub-report-title">About</h1>
    606. 

  606. <ul>
    607. 

  607. 		<li>FMRIPrep version: 1.2.2</li>
    608. 

  608. 		<li>FMRIPrep command: <code>/usr/local/miniconda/bin/fmriprep --fs-license-file /utilities/fs_600_license.txt /input/ /output/ participant --participant_label 34 -w /work/ --mem_mb 35000 --nthreads 8 --omp-nthreads 8 --write-graph --stop-on-first-crash --output-space T1w fsnative template fsaverage --notrack --verbose --resource-monitor</code></li>
    609. 

  609. 		<li>Date preprocessed: 2020-09-20 19:41:34 +0000</li>
    610. 

  610. 	</ul>
    611. 

  611. </div>    </div>
    612. 

  612. 

  613. <div id="boilerplate">
    614. 

  614.     <h1 class="sub-report-title">Methods</h1>
    615. 

  615.     <p>We kindly ask to report results preprocessed with fMRIPrep using the following
    616. 

  616.        boilerplate</p>
    617. 

  617.     <ul class="nav nav-tabs" id="myTab" role="tablist">
    618. 

  618.         <li class="nav-item">
    619. 

  619.             <a class="nav-link active" id="HTML-tab" data-toggle="tab" href="#HTML" role="tab" aria-controls="HTML" aria-selected="true">HTML</a>
    620. 

  620.         </li>
    621. 

  621.         <li class="nav-item">
    622. 

  622.             <a class="nav-link " id="Markdown-tab" data-toggle="tab" href="#Markdown" role="tab" aria-controls="Markdown" aria-selected="false">Markdown</a>
    623. 

  623.         </li>
    624. 

  624.         <li class="nav-item">
    625. 

  625.             <a class="nav-link " id="LaTeX-tab" data-toggle="tab" href="#LaTeX" role="tab" aria-controls="LaTeX" aria-selected="false">LaTeX</a>
    626. 

  626.         </li>
    627. 

  627.     </ul>
    628. 

  628.     <div class="tab-content" id="myTabContent">
    629. 

  629.       <div class="tab-pane fade active show" id="HTML" role="tabpanel" aria-labelledby="HTML-tab"><div class="boiler-html"><p>Results included in this manuscript come from preprocessing performed using <em>fMRIPprep</em> 1.2.2 (<span class="citation" data-cites="fmriprep1">Esteban, Markiewicz, et al. (2018)</span>; <span class="citation" data-cites="fmriprep2">Esteban, Blair, et al. (2018)</span>; RRID:SCR_016216), which is based on <em>Nipype</em> 1.1.5 (<span class="citation" data-cites="nipype1">Gorgolewski et al. (2011)</span>; <span class="citation" data-cites="nipype2">Gorgolewski et al. (2018)</span>; RRID:SCR_002502).</p>
    630. 

  630. <dl>
    631. 

  631. <dt>Anatomical data preprocessing</dt>
    632. 

  632. <dd><p>A total of 2 T1-weighted (T1w) images were found within the input BIDS dataset. All of them were corrected for intensity non-uniformity (INU) using <code>N4BiasFieldCorrection</code> <span class="citation" data-cites="n4">(Tustison et al. 2010, ANTs 2.2.0)</span>. A T1w-reference map was computed after registration of 2 T1w images (after INU-correction) using <code>mri_robust_template</code> <span class="citation" data-cites="fs_template">(FreeSurfer 6.0.1, Reuter, Rosas, and Fischl 2010)</span>. The T1w-reference was then skull-stripped using <code>antsBrainExtraction.sh</code> (ANTs 2.2.0), using OASIS as target template. Brain surfaces were reconstructed using <code>recon-all</code> <span class="citation" data-cites="fs_reconall">(FreeSurfer 6.0.1, RRID:SCR_001847, Dale, Fischl, and Sereno 1999)</span>, and the brain mask estimated previously was refined with a custom variation of the method to reconcile ANTs-derived and FreeSurfer-derived segmentations of the cortical gray-matter of Mindboggle <span class="citation" data-cites="mindboggle">(RRID:SCR_002438, Klein et al. 2017)</span>. Spatial normalization to the ICBM 152 Nonlinear Asymmetrical template version 2009c <span class="citation" data-cites="mni">(Fonov et al. 2009, RRID:SCR_008796)</span> was performed through nonlinear registration with <code>antsRegistration</code> <span class="citation" data-cites="ants">(ANTs 2.2.0, RRID:SCR_004757, Avants et al. 2008)</span>, using brain-extracted versions of both T1w volume and template. Brain tissue segmentation of cerebrospinal fluid (CSF), white-matter (WM) and gray-matter (GM) was performed on the brain-extracted T1w using <code>fast</code> <span class="citation" data-cites="fsl_fast">(FSL 5.0.9, RRID:SCR_002823, Zhang, Brady, and Smith 2001)</span>.</p>
    633. 

  633. </dd>
    634. 

  634. <dt>Functional data preprocessing</dt>
    635. 

  635. <dd><p>For each of the 12 BOLD runs found per subject (across all tasks and sessions), the following preprocessing was performed. First, a reference volume and its skull-stripped version were generated using a custom methodology of <em>fMRIPrep</em>. A deformation field to correct for susceptibility distortions was estimated based on two echo-planar imaging (EPI) references with opposing phase-encoding directions, using <code>3dQwarp</code> <span class="citation" data-cites="afni">Cox and Hyde (1997)</span> (AFNI 20160207). Based on the estimated susceptibility distortion, an unwarped BOLD reference was calculated for a more accurate co-registration with the anatomical reference. The BOLD reference was then co-registered to the T1w reference using <code>bbregister</code> (FreeSurfer) which implements boundary-based registration <span class="citation" data-cites="bbr">(Greve and Fischl 2009)</span>. Co-registration was configured with nine degrees of freedom to account for distortions remaining in the BOLD reference. Head-motion parameters with respect to the BOLD reference (transformation matrices, and six corresponding rotation and translation parameters) are estimated before any spatiotemporal filtering using <code>mcflirt</code> <span class="citation" data-cites="mcflirt">(FSL 5.0.9, Jenkinson et al. 2002)</span>. BOLD runs were slice-time corrected using <code>3dTshift</code> from AFNI 20160207 <span class="citation" data-cites="afni">(Cox and Hyde 1997, RRID:SCR_005927)</span>. The BOLD time-series (including slice-timing correction when applied) were resampled onto their original, native space by applying a single, composite transform to correct for head-motion and susceptibility distortions. These resampled BOLD time-series will be referred to as <em>preprocessed BOLD in original space</em>, or just <em>preprocessed BOLD</em>. The BOLD time-series were resampled to MNI152NLin2009cAsym standard space, generating a <em>preprocessed BOLD run in MNI152NLin2009cAsym space</em>. First, a reference volume and its skull-stripped version were generated using a custom methodology of <em>fMRIPrep</em>. Several confounding time-series were calculated based on the <em>preprocessed BOLD</em>: framewise displacement (FD), DVARS and three region-wise global signals. FD and DVARS are calculated for each functional run, both using their implementations in <em>Nipype</em> <span class="citation" data-cites="power_fd_dvars">(following the definitions by Power et al. 2014)</span>. The three global signals are extracted within the CSF, the WM, and the whole-brain masks. Additionally, a set of physiological regressors were extracted to allow for component-based noise correction <span class="citation" data-cites="compcor">(<em>CompCor</em>, Behzadi et al. 2007)</span>. Principal components are estimated after high-pass filtering the <em>preprocessed BOLD</em> time-series (using a discrete cosine filter with 128s cut-off) for the two <em>CompCor</em> variants: temporal (tCompCor) and anatomical (aCompCor). Six tCompCor components are then calculated from the top 5% variable voxels within a mask covering the subcortical regions. This subcortical mask is obtained by heavily eroding the brain mask, which ensures it does not include cortical GM regions. For aCompCor, six components are calculated within the intersection of the aforementioned mask and the union of CSF and WM masks calculated in T1w space, after their projection to the native space of each functional run (using the inverse BOLD-to-T1w transformation). The head-motion estimates calculated in the correction step were also placed within the corresponding confounds file. The BOLD time-series, were resampled to surfaces on the following spaces: <em>fsnative</em>, <em>fsaverage</em>. All resamplings can be performed with <em>a single interpolation step</em> by composing all the pertinent transformations (i.e. head-motion transform matrices, susceptibility distortion correction when available, and co-registrations to anatomical and template spaces). Gridded (volumetric) resamplings were performed using <code>antsApplyTransforms</code> (ANTs), configured with Lanczos interpolation to minimize the smoothing effects of other kernels <span class="citation" data-cites="lanczos">(Lanczos 1964)</span>. Non-gridded (surface) resamplings were performed using <code>mri_vol2surf</code> (FreeSurfer).</p>
    636. 

  636. </dd>
    637. 

  637. </dl>
    638. 

  638. <p>Many internal operations of <em>fMRIPrep</em> use <em>Nilearn</em> 0.4.2 <span class="citation" data-cites="nilearn">(Abraham et al. 2014, RRID:SCR_001362)</span>, mostly within the functional processing workflow. For more details of the pipeline, see <a href="https://fmriprep.readthedocs.io/en/latest/workflows.html" title="FMRIPrep&#39;s documentation">the section corresponding to workflows in <em>fMRIPrep</em>’s documentation</a>.</p>
    639. 

  639. <h3 id="references" class="unnumbered">References</h3>
    640. 

  640. <div id="refs" class="references">
    641. 

  641. <div id="ref-nilearn">
    642. 

  642. <p>Abraham, Alexandre, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, and Gael Varoquaux. 2014. “Machine Learning for Neuroimaging with Scikit-Learn.” <em>Frontiers in Neuroinformatics</em> 8. <a href="https://doi.org/10.3389/fninf.2014.00014" class="uri">https://doi.org/10.3389/fninf.2014.00014</a>.</p>
    643. 

  643. </div>
    644. 

  644. <div id="ref-ants">
    645. 

  645. <p>Avants, B.B., C.L. Epstein, M. Grossman, and J.C. Gee. 2008. “Symmetric Diffeomorphic Image Registration with Cross-Correlation: Evaluating Automated Labeling of Elderly and Neurodegenerative Brain.” <em>Medical Image Analysis</em> 12 (1): 26–41. <a href="https://doi.org/10.1016/j.media.2007.06.004" class="uri">https://doi.org/10.1016/j.media.2007.06.004</a>.</p>
    646. 

  646. </div>
    647. 

  647. <div id="ref-compcor">
    648. 

  648. <p>Behzadi, Yashar, Khaled Restom, Joy Liau, and Thomas T. Liu. 2007. “A Component Based Noise Correction Method (CompCor) for BOLD and Perfusion Based fMRI.” <em>NeuroImage</em> 37 (1): 90–101. <a href="https://doi.org/10.1016/j.neuroimage.2007.04.042" class="uri">https://doi.org/10.1016/j.neuroimage.2007.04.042</a>.</p>
    649. 

  649. </div>
    650. 

  650. <div id="ref-afni">
    651. 

  651. <p>Cox, Robert W., and James S. Hyde. 1997. “Software Tools for Analysis and Visualization of fMRI Data.” <em>NMR in Biomedicine</em> 10 (4-5): 171–78. <a href="https://doi.org/10.1002/(SICI)1099-1492(199706/08)10:4/5&lt;171::AID-NBM453&gt;3.0.CO;2-L" class="uri">https://doi.org/10.1002/(SICI)1099-1492(199706/08)10:4/5&lt;171::AID-NBM453&gt;3.0.CO;2-L</a>.</p>
    652. 

  652. </div>
    653. 

  653. <div id="ref-fs_reconall">
    654. 

  654. <p>Dale, Anders M., Bruce Fischl, and Martin I. Sereno. 1999. “Cortical Surface-Based Analysis: I. Segmentation and Surface Reconstruction.” <em>NeuroImage</em> 9 (2): 179–94. <a href="https://doi.org/10.1006/nimg.1998.0395" class="uri">https://doi.org/10.1006/nimg.1998.0395</a>.</p>
    655. 

  655. </div>
    656. 

  656. <div id="ref-fmriprep2">
    657. 

  657. <p>Esteban, Oscar, Ross Blair, Christopher J. Markiewicz, Shoshana L. Berleant, Craig Moodie, Feilong Ma, Ayse Ilkay Isik, et al. 2018. “FMRIPrep 1.2.2.” <em>Software</em>. Zenodo. <a href="https://doi.org/10.5281/zenodo.852659" class="uri">https://doi.org/10.5281/zenodo.852659</a>.</p>
    658. 

  658. </div>
    659. 

  659. <div id="ref-fmriprep1">
    660. 

  660. <p>Esteban, Oscar, Christopher Markiewicz, Ross W Blair, Craig Moodie, Ayse Ilkay Isik, Asier Erramuzpe Aliaga, James Kent, et al. 2018. “FMRIPrep: A Robust Preprocessing Pipeline for Functional MRI.” <em>bioRxiv</em>. <a href="https://doi.org/10.1101/306951" class="uri">https://doi.org/10.1101/306951</a>.</p>
    661. 

  661. </div>
    662. 

  662. <div id="ref-mni">
    663. 

  663. <p>Fonov, VS, AC Evans, RC McKinstry, CR Almli, and DL Collins. 2009. “Unbiased Nonlinear Average Age-Appropriate Brain Templates from Birth to Adulthood.” <em>NeuroImage</em>, Organization for human brain mapping 2009 annual meeting, 47, Supplement 1: S102. <a href="https://doi.org/10.1016/S1053-8119(09)70884-5" class="uri">https://doi.org/10.1016/S1053-8119(09)70884-5</a>.</p>
    664. 

  664. </div>
    665. 

  665. <div id="ref-nipype1">
    666. 

  666. <p>Gorgolewski, K., C. D. Burns, C. Madison, D. Clark, Y. O. Halchenko, M. L. Waskom, and S. Ghosh. 2011. “Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python.” <em>Frontiers in Neuroinformatics</em> 5: 13. <a href="https://doi.org/10.3389/fninf.2011.00013" class="uri">https://doi.org/10.3389/fninf.2011.00013</a>.</p>
    667. 

  667. </div>
    668. 

  668. <div id="ref-nipype2">
    669. 

  669. <p>Gorgolewski, Krzysztof J., Oscar Esteban, Christopher J. Markiewicz, Erik Ziegler, David Gage Ellis, Michael Philipp Notter, Dorota Jarecka, et al. 2018. “Nipype.” <em>Software</em>. Zenodo. <a href="https://doi.org/10.5281/zenodo.596855" class="uri">https://doi.org/10.5281/zenodo.596855</a>.</p>
    670. 

  670. </div>
    671. 

  671. <div id="ref-bbr">
    672. 

  672. <p>Greve, Douglas N, and Bruce Fischl. 2009. “Accurate and Robust Brain Image Alignment Using Boundary-Based Registration.” <em>NeuroImage</em> 48 (1): 63–72. <a href="https://doi.org/10.1016/j.neuroimage.2009.06.060" class="uri">https://doi.org/10.1016/j.neuroimage.2009.06.060</a>.</p>
    673. 

  673. </div>
    674. 

  674. <div id="ref-mcflirt">
    675. 

  675. <p>Jenkinson, Mark, Peter Bannister, Michael Brady, and Stephen Smith. 2002. “Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images.” <em>NeuroImage</em> 17 (2): 825–41. <a href="https://doi.org/10.1006/nimg.2002.1132" class="uri">https://doi.org/10.1006/nimg.2002.1132</a>.</p>
    676. 

  676. </div>
    677. 

  677. <div id="ref-mindboggle">
    678. 

  678. <p>Klein, Arno, Satrajit S. Ghosh, Forrest S. Bao, Joachim Giard, Yrjö Häme, Eliezer Stavsky, Noah Lee, et al. 2017. “Mindboggling Morphometry of Human Brains.” <em>PLOS Computational Biology</em> 13 (2): e1005350. <a href="https://doi.org/10.1371/journal.pcbi.1005350" class="uri">https://doi.org/10.1371/journal.pcbi.1005350</a>.</p>
    679. 

  679. </div>
    680. 

  680. <div id="ref-lanczos">
    681. 

  681. <p>Lanczos, C. 1964. “Evaluation of Noisy Data.” <em>Journal of the Society for Industrial and Applied Mathematics Series B Numerical Analysis</em> 1 (1): 76–85. <a href="https://doi.org/10.1137/0701007" class="uri">https://doi.org/10.1137/0701007</a>.</p>
    682. 

  682. </div>
    683. 

  683. <div id="ref-power_fd_dvars">
    684. 

  684. <p>Power, Jonathan D., Anish Mitra, Timothy O. Laumann, Abraham Z. Snyder, Bradley L. Schlaggar, and Steven E. Petersen. 2014. “Methods to Detect, Characterize, and Remove Motion Artifact in Resting State fMRI.” <em>NeuroImage</em> 84 (Supplement C): 320–41. <a href="https://doi.org/10.1016/j.neuroimage.2013.08.048" class="uri">https://doi.org/10.1016/j.neuroimage.2013.08.048</a>.</p>
    685. 

  685. </div>
    686. 

  686. <div id="ref-fs_template">
    687. 

  687. <p>Reuter, Martin, Herminia Diana Rosas, and Bruce Fischl. 2010. “Highly Accurate Inverse Consistent Registration: A Robust Approach.” <em>NeuroImage</em> 53 (4): 1181–96. <a href="https://doi.org/10.1016/j.neuroimage.2010.07.020" class="uri">https://doi.org/10.1016/j.neuroimage.2010.07.020</a>.</p>
    688. 

  688. </div>
    689. 

  689. <div id="ref-n4">
    690. 

  690. <p>Tustison, N. J., B. B. Avants, P. A. Cook, Y. Zheng, A. Egan, P. A. Yushkevich, and J. C. Gee. 2010. “N4ITK: Improved N3 Bias Correction.” <em>IEEE Transactions on Medical Imaging</em> 29 (6): 1310–20. <a href="https://doi.org/10.1109/TMI.2010.2046908" class="uri">https://doi.org/10.1109/TMI.2010.2046908</a>.</p>
    691. 

  691. </div>
    692. 

  692. <div id="ref-fsl_fast">
    693. 

  693. <p>Zhang, Y., M. Brady, and S. Smith. 2001. “Segmentation of Brain MR Images Through a Hidden Markov Random Field Model and the Expectation-Maximization Algorithm.” <em>IEEE Transactions on Medical Imaging</em> 20 (1): 45–57. <a href="https://doi.org/10.1109/42.906424" class="uri">https://doi.org/10.1109/42.906424</a>.</p>
    694. 

  694. </div>
    695. 

  695. </div></div></div>
    696. 

  696.       <div class="tab-pane fade " id="Markdown" role="tabpanel" aria-labelledby="Markdown-tab"><pre>
    697. 

  697. Results included in this manuscript come from preprocessing
    698. 

  698. performed using *fMRIPprep* 1.2.2
    699. 

  699. (@fmriprep1; @fmriprep2; RRID:SCR_016216),
    700. 

  700. which is based on *Nipype* 1.1.5
    701. 

  701. (@nipype1; @nipype2; RRID:SCR_002502).
    702. 

  702. 

  703. Anatomical data preprocessing
    704. 

  704. 

  705. : A total of 2 T1-weighted (T1w) images were found within the input
    706. 

  706. BIDS dataset.
    707. 

  707. All of them were corrected for intensity non-uniformity (INU)
    708. 

  708. using `N4BiasFieldCorrection` [@n4, ANTs 2.2.0].
    709. 

  709. A T1w-reference map was computed after registration of
    710. 

  710. 2 T1w images (after INU-correction) using
    711. 

  711. `mri_robust_template` [FreeSurfer 6.0.1, @fs_template].
    712. 

  712. The T1w-reference was then skull-stripped using `antsBrainExtraction.sh`
    713. 

  713. (ANTs 2.2.0), using OASIS as target template.
    714. 

  714. Brain surfaces were reconstructed using `recon-all` [FreeSurfer 6.0.1,
    715. 

  715. RRID:SCR_001847, @fs_reconall], and the brain mask estimated
    716. 

  716. previously was refined with a custom variation of the method to reconcile
    717. 

  717. ANTs-derived and FreeSurfer-derived segmentations of the cortical
    718. 

  718. gray-matter of Mindboggle [RRID:SCR_002438, @mindboggle].
    719. 

  719. Spatial normalization to the ICBM 152 Nonlinear Asymmetrical
    720. 

  720. template version 2009c [@mni, RRID:SCR_008796] was performed
    721. 

  721. through nonlinear registration with `antsRegistration`
    722. 

  722. [ANTs 2.2.0, RRID:SCR_004757, @ants], using
    723. 

  723. brain-extracted versions of both T1w volume and template.
    724. 

  724. Brain tissue segmentation of cerebrospinal fluid (CSF),
    725. 

  725. white-matter (WM) and gray-matter (GM) was performed on
    726. 

  726. the brain-extracted T1w using `fast` [FSL 5.0.9, RRID:SCR_002823,
    727. 

  727. @fsl_fast].
    728. 

  728. 

  729. 

  730. Functional data preprocessing
    731. 

  731. 

  732. : For each of the 12 BOLD runs found per subject (across all
    733. 

  733. tasks and sessions), the following preprocessing was performed.
    734. 

  734. First, a reference volume and its skull-stripped version were generated
    735. 

  735. using a custom methodology of *fMRIPrep*.
    736. 

  736. A deformation field to correct for susceptibility distortions was estimated
    737. 

  737. based on two echo-planar imaging (EPI) references with opposing phase-encoding
    738. 

  738. directions, using `3dQwarp` @afni (AFNI 20160207).
    739. 

  739. Based on the estimated susceptibility distortion, an
    740. 

  740. unwarped BOLD reference was calculated for a more accurate
    741. 

  741. co-registration with the anatomical reference.
    742. 

  742. The BOLD reference was then co-registered to the T1w reference using
    743. 

  743. `bbregister` (FreeSurfer) which implements boundary-based registration [@bbr].
    744. 

  744. Co-registration was configured with nine degrees of freedom to account
    745. 

  745. for distortions remaining in the BOLD reference.
    746. 

  746. Head-motion parameters with respect to the BOLD reference
    747. 

  747. (transformation matrices, and six corresponding rotation and translation
    748. 

  748. parameters) are estimated before any spatiotemporal filtering using
    749. 

  749. `mcflirt` [FSL 5.0.9, @mcflirt].
    750. 

  750. BOLD runs were slice-time corrected using `3dTshift` from
    751. 

  751. AFNI 20160207 [@afni, RRID:SCR_005927].
    752. 

  752. The BOLD time-series (including slice-timing correction when applied)
    753. 

  753. were resampled onto their original, native space by applying
    754. 

  754. a single, composite transform to correct for head-motion and
    755. 

  755. susceptibility distortions.
    756. 

  756. These resampled BOLD time-series will be referred to as *preprocessed
    757. 

  757. BOLD in original space*, or just *preprocessed BOLD*.
    758. 

  758. The BOLD time-series were resampled to MNI152NLin2009cAsym standard space,
    759. 

  759. generating a *preprocessed BOLD run in MNI152NLin2009cAsym space*.
    760. 

  760. First, a reference volume and its skull-stripped version were generated
    761. 

  761. using a custom methodology of *fMRIPrep*.
    762. 

  762. Several confounding time-series were calculated based on the
    763. 

  763. *preprocessed BOLD*: framewise displacement (FD), DVARS and
    764. 

  764. three region-wise global signals.
    765. 

  765. FD and DVARS are calculated for each functional run, both using their
    766. 

  766. implementations in *Nipype* [following the definitions by @power_fd_dvars].
    767. 

  767. The three global signals are extracted within the CSF, the WM, and
    768. 

  768. the whole-brain masks.
    769. 

  769. Additionally, a set of physiological regressors were extracted to
    770. 

  770. allow for component-based noise correction [*CompCor*, @compcor].
    771. 

  771. Principal components are estimated after high-pass filtering the
    772. 

  772. *preprocessed BOLD* time-series (using a discrete cosine filter with
    773. 

  773. 128s cut-off) for the two *CompCor* variants: temporal (tCompCor)
    774. 

  774. and anatomical (aCompCor).
    775. 

  775. Six tCompCor components are then calculated from the top 5% variable
    776. 

  776. voxels within a mask covering the subcortical regions.
    777. 

  777. This subcortical mask is obtained by heavily eroding the brain mask,
    778. 

  778. which ensures it does not include cortical GM regions.
    779. 

  779. For aCompCor, six components are calculated within the intersection of
    780. 

  780. the aforementioned mask and the union of CSF and WM masks calculated
    781. 

  781. in T1w space, after their projection to the native space of each
    782. 

  782. functional run (using the inverse BOLD-to-T1w transformation).
    783. 

  783. The head-motion estimates calculated in the correction step were also
    784. 

  784. placed within the corresponding confounds file.
    785. 

  785. The BOLD time-series, were resampled to surfaces on the following
    786. 

  786. spaces: *fsnative*, *fsaverage*.
    787. 

  787. All resamplings can be performed with *a single interpolation
    788. 

  788. step* by composing all the pertinent transformations (i.e. head-motion
    789. 

  789. transform matrices, susceptibility distortion correction when available,
    790. 

  790. and co-registrations to anatomical and template spaces).
    791. 

  791. Gridded (volumetric) resamplings were performed using `antsApplyTransforms` (ANTs),
    792. 

  792. configured with Lanczos interpolation to minimize the smoothing
    793. 

  793. effects of other kernels [@lanczos].
    794. 

  794. Non-gridded (surface) resamplings were performed using `mri_vol2surf`
    795. 

  795. (FreeSurfer).
    796. 

  796. 

  797. 

  798. Many internal operations of *fMRIPrep* use
    799. 

  799. *Nilearn* 0.4.2 [@nilearn, RRID:SCR_001362],
    800. 

  800. mostly within the functional processing workflow.
    801. 

  801. For more details of the pipeline, see [the section corresponding
    802. 

  802. to workflows in *fMRIPrep*'s documentation](https://fmriprep.readthedocs.io/en/latest/workflows.html "FMRIPrep's documentation").
    803. 

  803. 

  804. 

  805. ### References
    806. 

  806. 

  807. </pre>
    808. 

  808. </div>
    809. 

  809.       <div class="tab-pane fade " id="LaTeX" role="tabpanel" aria-labelledby="LaTeX-tab"><pre>Results included in this manuscript come from preprocessing performed
    810. 

  810. using \emph{fMRIPprep} 1.2.2 (\citet{fmriprep1}; \citet{fmriprep2};
    811. 

  811. RRID:SCR\_016216), which is based on \emph{Nipype} 1.1.5
    812. 

  812. (\citet{nipype1}; \citet{nipype2}; RRID:SCR\_002502).
    813. 

  813. 

  814. \begin{description}
    815. 

  815. \item[Anatomical data preprocessing]
    816. 

  816. A total of 2 T1-weighted (T1w) images were found within the input BIDS
    817. 

  817. dataset. All of them were corrected for intensity non-uniformity (INU)
    818. 

  818. using \texttt{N4BiasFieldCorrection} \citep[ANTs 2.2.0]{n4}. A
    819. 

  819. T1w-reference map was computed after registration of 2 T1w images (after
    820. 

  820. INU-correction) using \texttt{mri\_robust\_template} \citep[FreeSurfer
    821. 

  821. 6.0.1,][]{fs_template}. The T1w-reference was then skull-stripped using
    822. 

  822. \texttt{antsBrainExtraction.sh} (ANTs 2.2.0), using OASIS as target
    823. 

  823. template. Brain surfaces were reconstructed using \texttt{recon-all}
    824. 

  824. \citep[FreeSurfer 6.0.1, RRID:SCR\_001847,][]{fs_reconall}, and the
    825. 

  825. brain mask estimated previously was refined with a custom variation of
    826. 

  826. the method to reconcile ANTs-derived and FreeSurfer-derived
    827. 

  827. segmentations of the cortical gray-matter of Mindboggle
    828. 

  828. \citep[RRID:SCR\_002438,][]{mindboggle}. Spatial normalization to the
    829. 

  829. ICBM 152 Nonlinear Asymmetrical template version 2009c
    830. 

  830. \citep[RRID:SCR\_008796]{mni} was performed through nonlinear
    831. 

  831. registration with \texttt{antsRegistration} \citep[ANTs 2.2.0,
    832. 

  832. RRID:SCR\_004757,][]{ants}, using brain-extracted versions of both T1w
    833. 

  833. volume and template. Brain tissue segmentation of cerebrospinal fluid
    834. 

  834. (CSF), white-matter (WM) and gray-matter (GM) was performed on the
    835. 

  835. brain-extracted T1w using \texttt{fast} \citep[FSL 5.0.9,
    836. 

  836. RRID:SCR\_002823,][]{fsl_fast}.
    837. 

  837. \item[Functional data preprocessing]
    838. 

  838. For each of the 12 BOLD runs found per subject (across all tasks and
    839. 

  839. sessions), the following preprocessing was performed. First, a reference
    840. 

  840. volume and its skull-stripped version were generated using a custom
    841. 

  841. methodology of \emph{fMRIPrep}. A deformation field to correct for
    842. 

  842. susceptibility distortions was estimated based on two echo-planar
    843. 

  843. imaging (EPI) references with opposing phase-encoding directions, using
    844. 

  844. \texttt{3dQwarp} \citet{afni} (AFNI 20160207). Based on the estimated
    845. 

  845. susceptibility distortion, an unwarped BOLD reference was calculated for
    846. 

  846. a more accurate co-registration with the anatomical reference. The BOLD
    847. 

  847. reference was then co-registered to the T1w reference using
    848. 

  848. \texttt{bbregister} (FreeSurfer) which implements boundary-based
    849. 

  849. registration \citep{bbr}. Co-registration was configured with nine
    850. 

  850. degrees of freedom to account for distortions remaining in the BOLD
    851. 

  851. reference. Head-motion parameters with respect to the BOLD reference
    852. 

  852. (transformation matrices, and six corresponding rotation and translation
    853. 

  853. parameters) are estimated before any spatiotemporal filtering using
    854. 

  854. \texttt{mcflirt} \citep[FSL 5.0.9,][]{mcflirt}. BOLD runs were
    855. 

  855. slice-time corrected using \texttt{3dTshift} from AFNI 20160207
    856. 

  856. \citep[RRID:SCR\_005927]{afni}. The BOLD time-series (including
    857. 

  857. slice-timing correction when applied) were resampled onto their
    858. 

  858. original, native space by applying a single, composite transform to
    859. 

  859. correct for head-motion and susceptibility distortions. These resampled
    860. 

  860. BOLD time-series will be referred to as \emph{preprocessed BOLD in
    861. 

  861. original space}, or just \emph{preprocessed BOLD}. The BOLD time-series
    862. 

  862. were resampled to MNI152NLin2009cAsym standard space, generating a
    863. 

  863. \emph{preprocessed BOLD run in MNI152NLin2009cAsym space}. First, a
    864. 

  864. reference volume and its skull-stripped version were generated using a
    865. 

  865. custom methodology of \emph{fMRIPrep}. Several confounding time-series
    866. 

  866. were calculated based on the \emph{preprocessed BOLD}: framewise
    867. 

  867. displacement (FD), DVARS and three region-wise global signals. FD and
    868. 

  868. DVARS are calculated for each functional run, both using their
    869. 

  869. implementations in \emph{Nipype} \citep[following the definitions
    870. 

  870. by][]{power_fd_dvars}. The three global signals are extracted within the
    871. 

  871. CSF, the WM, and the whole-brain masks. Additionally, a set of
    872. 

  872. physiological regressors were extracted to allow for component-based
    873. 

  873. noise correction \citep[\emph{CompCor},][]{compcor}. Principal
    874. 

  874. components are estimated after high-pass filtering the
    875. 

  875. \emph{preprocessed BOLD} time-series (using a discrete cosine filter
    876. 

  876. with 128s cut-off) for the two \emph{CompCor} variants: temporal
    877. 

  877. (tCompCor) and anatomical (aCompCor). Six tCompCor components are then
    878. 

  878. calculated from the top 5\% variable voxels within a mask covering the
    879. 

  879. subcortical regions. This subcortical mask is obtained by heavily
    880. 

  880. eroding the brain mask, which ensures it does not include cortical GM
    881. 

  881. regions. For aCompCor, six components are calculated within the
    882. 

  882. intersection of the aforementioned mask and the union of CSF and WM
    883. 

  883. masks calculated in T1w space, after their projection to the native
    884. 

  884. space of each functional run (using the inverse BOLD-to-T1w
    885. 

  885. transformation). The head-motion estimates calculated in the correction
    886. 

  886. step were also placed within the corresponding confounds file. The BOLD
    887. 

  887. time-series, were resampled to surfaces on the following spaces:
    888. 

  888. \emph{fsnative}, \emph{fsaverage}. All resamplings can be performed with
    889. 

  889. \emph{a single interpolation step} by composing all the pertinent
    890. 

  890. transformations (i.e.~head-motion transform matrices, susceptibility
    891. 

  891. distortion correction when available, and co-registrations to anatomical
    892. 

  892. and template spaces). Gridded (volumetric) resamplings were performed
    893. 

  893. using \texttt{antsApplyTransforms} (ANTs), configured with Lanczos
    894. 

  894. interpolation to minimize the smoothing effects of other kernels
    895. 

  895. \citep{lanczos}. Non-gridded (surface) resamplings were performed using
    896. 

  896. \texttt{mri\_vol2surf} (FreeSurfer).
    897. 

  897. \end{description}
    898. 

  898. 

  899. Many internal operations of \emph{fMRIPrep} use \emph{Nilearn} 0.4.2
    900. 

  900. \citep[RRID:SCR\_001362]{nilearn}, mostly within the functional
    901. 

  901. processing workflow. For more details of the pipeline, see
    902. 

  902. \href{https://fmriprep.readthedocs.io/en/latest/workflows.html}{the
    903. 

  903. section corresponding to workflows in \emph{fMRIPrep}'s documentation}.
    904. 

  904. 

  905. \hypertarget{references}{%
    906. 

  906. \subsubsection{References}\label{references}}
    907. 

  907. 

  908. \bibliography{/usr/local/miniconda/lib/python3.6/site-packages/fmriprep/data/boilerplate.bib}</pre>
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  1159.     doi = {10.1016/j.neuroimage.2007.04.042},
    1160. 

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    1162. 

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    1163. 

  1163.     pages = {90-101},
    1164. 

  1164.     title = {A component based noise correction method ({CompCor}) for {BOLD} and perfusion based fMRI},
    1165. 

  1165.     url = {http://www.sciencedirect.com/science/article/pii/S1053811907003837},
    1166. 

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  1167.     year = 2007
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  1168. }
    1169. 

  1169. 

  1170. @article{hcppipelines,
    1171. 

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    1172. 

  1172.     doi = {10.1016/j.neuroimage.2013.04.127},
    1173. 

  1173.     issn = {1053-8119},
    1174. 

  1174.     journal = {NeuroImage},
    1175. 

  1175.     pages = {105-124},
    1176. 

  1176.     series = {Mapping the Connectome},
    1177. 

  1177.     title = {The minimal preprocessing pipelines for the Human Connectome Project},
    1178. 

  1178.     url = {http://www.sciencedirect.com/science/article/pii/S1053811913005053},
    1179. 

  1179.     volume = 80,
    1180. 

  1180.     year = 2013
    1181. 

  1181. }
    1182. 

  1182. 

  1183. @article{fs_template,
    1184. 

  1184.     author = {Reuter, Martin and Rosas, Herminia Diana and Fischl, Bruce},
    1185. 

  1185.     doi = {10.1016/j.neuroimage.2010.07.020},
    1186. 

  1186.     journal = {NeuroImage},
    1187. 

  1187.     number = 4,
    1188. 

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    1189. 

  1189.     title = {Highly accurate inverse consistent registration: A robust approach},
    1190. 

  1190.     volume = 53,
    1191. 

  1191.     year = 2010
    1192. 

  1192. }
    1193. 

  1193. 

  1194. @article{afni,
    1195. 

  1195.     author = {Cox, Robert W. and Hyde, James S.},
    1196. 

  1196.     doi = {10.1002/(SICI)1099-1492(199706/08)10:4/5<171::AID-NBM453>3.0.CO;2-L},
    1197. 

  1197.     journal = {NMR in Biomedicine},
    1198. 

  1198.     number = {4-5},
    1199. 

  1199.     pages = {171-178},
    1200. 

  1200.     title = {Software tools for analysis and visualization of fMRI data},
    1201. 

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    1202. 

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    1203. 

  1203. }
    1204. 

  1204. 

  1205. @article{posse_t2s,
    1206. 

  1206.     author = {Posse, Stefan and Wiese, Stefan and Gembris, Daniel and Mathiak, Klaus and Kessler, Christoph and Grosse-Ruyken, Maria-Liisa and Elghahwagi, Barbara and Richards, Todd and Dager, Stephen R. and Kiselev, Valerij G.},
    1207. 

  1207.     doi = {10.1002/(SICI)1522-2594(199907)42:1<87::AID-MRM13>3.0.CO;2-O},
    1208. 

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    1210. 

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    1213. 

  1213.     year = 1999
    1214. 

  1214. }
    1215. 

  1215. </pre>
    1216. 

  1216. </div>
    1217. 

  1217.     </div>
    1218. 

  1218.     <p>Alternatively, an interactive <a href="http://fmriprep.readthedocs.io/en/latest/citing.html">boilerplate generator</a> is available in the <a href="https://fmriprep.org">documentation website</a>.</p>
    1219. 

  1219. </div>
    1220. 

  1220. 

  1221. <div id="errors">
    1222. 

  1222.     <h1 class="sub-report-title">Errors</h1>
    1223. 

  1223.     <ul>
    1224. 

  1224.         <li>No errors to report!</li>
    1225. 

  1225.     </ul>
    1226. 

  1226. </div>
    1227. 

  1227. 

  1228. 

  1229. <script type="text/javascript">
    1230. 

  1230.     function toggle(id) {
    1231. 

  1231.         var element = document.getElementById(id);
    1232. 

  1232.         if(element.style.display == 'block')
    1233. 

  1233.             element.style.display = 'none';
    1234. 

  1234.         else
    1235. 

  1235.             element.style.display = 'block';
    1236. 

  1236.     }
    1237. 

  1237. </script>
    1238. 

  1238. </body>
    1239. 

  1239. </html>
    1240.