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13 results for “freesurfer”
Freesurfer Dataset
<p>This is simulated data created for test and demonstration purposes for decentralized algorithms for <a href="https://github.com/trendscenter/coinstac">COINSTAC</a>.</p> <p>There is a CSV file with the two columns of demographic data and a column of filenames containing the volumes of the regions of interest (ROIs) of the subjects' brains. These volumes are typically produced by segmentation using <code>recon-all</code> in the <a href="https://surfer.nmr.mgh.harvard.edu">FreeSurfer</a> program.</p> <p>Data dictionary</p> <ul> <li>freesurferfile: filename associated with subject containing volumes of ROIs, as typically produced by FreeSurfer segmentation</li> <li>age (float): subject's age</li> <li>isControl (Boolean): whether subject was a control (True) or had a medical condition (False)</li> </ul> <p>There are a total of 72 subjects.</p> <p>The volumes were simulated with equations of the following form:</p> <p>y = B0 + B1 x age + B2 x isControl + B3 x e</p> <p>where e ~ N(0,1)</p> <p>Each volume was given a fixed intercept (B0) (e.g., 48466.3 for Right-Cerebellum-Cortex). The effect of age (B1) was selected randomly from the range [-300, -100], and the effect of diagnosis (isControl, B2) was selected randomly from the range [500, 1000] for each pseudo subject. A standard unit Gaussian noise multiplied by a random index from the range [1800, 2200] was added subsequently.</p> <p>This data was created on Feb 2, 2017 by Jing Ming at the Mind Research Network and presented in this paper:</p> <p>Ming J, Verner E, Sarwate A et al. COINSTAC: Decentralizing the future of brain imaging analysis [version 1; peer review: 2 approved]. F1000Research 2017, 6:1512 (<a href="https://doi.org/10.12688/f1000research.12353.1">https://doi.org/10.12688/f1000research.12353.1</a>)</p>
High frequency somatosensory MEG: evoked responses, FreeSurfer reconstruction
<p>This dataset contains somatosensory evoked responses recorded with Elekta TRIUX magnetoencephalography (MEG) system. The purpose of the measurements was to examine high-frequency (HF) somatosensory responses. To this end, a large number of responses (couple of thousand) were recorded with a short interstimulus interval (randomized between 300-350 ms). A constant-current electric stimulator was used, with the electrodes placed around the median nerve at the right wrist. The magnitude of the current was individually determined so that the stimulation was slightly below motor threshold; it was approximately 7 mA. The length of the current pulse was set at 200 microseconds.</p> <p>Measurements from two subjects are included. The dataset also contains anatomical MRIs and FreeSurfer reconstructions. Only evoked (averaged) MEG data is included; raw MEG data is in a separate dataset at https://doi.org/10.5281/zenodo.889295</p> <p> </p>
Brain surfaces computed with FreeSurfer 6 for all ABIDE I subjects
<p># ABIDE I FreeSurfer 6 'surfaces' data</p> <p><br> This archive contains the following ABIDE I FreeSurfer 6 meshes / surfaces:<br> white, orig, sphere</p> <p>Note that the pial surface is part of the ABIDE I pial lgi dataset:</p> <p> https://zenodo.org/record/7132610<br> DOI: 10.5281/zenodo.7132610</p> <p> </p> <p><br> ## Credits</p> <p>This data is derived from the MRI scans of the ABIDE I dataset:</p> <p>* ABIDE I dataset: https://fcon_1000.projects.nitrc.org/indi/abide/</p> <p>Quoting from that website:</p> <p> "The Autism Brain Imaging Data Exchange I (ABIDE I) represents the first<br> ABIDE initiative. Started as a grass roots effort, ABIDE I involved 17<br> international sites, sharing previously collected resting state functional<br> magnetic resonance imaging (R-fMRI), anatomical and phenotypic datasets<br> made available for data sharing with the broader scientific community.<br> This effort yielded 1112 dataset, including 539 from individuals with<br> ASD and 573 from typical controls (ages 7-64 years, median 14.7 years<br> across groups). This aggregate was released in August 2012. Its<br> establishment demonstrated the feasibility of aggregating resting<br> state fMRI and structural MRI data across sites; the rate of these<br> data use and resulting publications (see Manuscripts) have shown its<br> utility for capturing whole brain and regional properties of the brain<br> connectome in Autism Spectrum Disorder (ASD). In accordance with<br> HIPAA guidelines and 1000 Functional Connectomes Project / INDI<br> protocols, all datasets have been anonymized, with no protected<br> health information included."</p> <p>Citation: Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., ... & Milham, M. P. (2014).<br> The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 19(6), 659-667.</p> <p>## How this data was produced</p> <p>The following steps were used to create the data:</p> <p>* We downloaded all available MRI scans for the ABIDE I subjects (1035 subjects).<br> * We pre-processed all subjects in FreeSurfer version 6 (https://freesurfer.net) by running the full recon-all pipeline for each subject.<br> - We did not run any quality metrics on the scans or exclude any subjects.</p> <p><br> ## Contained files</p> <p>* In order to reduce the size of this dataset, for each subject, we only included the following files:<br> - <subject>/surf/lh.white : the white surface for the left hemisphere<br> - <subject>/surf/rh.white : the white surface for the right hemisphere<br> - <subject>/surf/lh.orig : the orig surface for the left hemisphere<br> - <subject>/surf/rh.orig : the orig surface for the right hemisphere<br> - <subject>/surf/lh.sphere : the sphere surface for the left hemisphere<br> - <subject>/surf/rh.sphere : the sphere surface for the right hemisphere</p> <p>All files are in binary FreeSurfer surf format and represent triangular meshes.<br> All surfaces are full resolution.</p> <p><br> ## What is NOT contained</p> <p>* The ABIDE demographics information (metadata on the subjects, like age, ...) is not included, you can get it from the ABIDE website.<br> * The pial surface is not included, get it from https://zenodo.org/record/7132610 instead.</p> <p>## Author and License</p> <p>Note: For the authors of the original ABIDE I dataset, see the Credits section above.</p> <p>This lgi data was created by:</p> <p> Dr. Tim Schäfer<br> Postdoc Computational Neuroimaging<br> Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy<br> University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany<br> http://rcmd.org/ts</p> <p>The data is published under the following license:</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode.txt or the file LICENSE for the full legal code.</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/ for an easy explanation of what this license means for you.</p> <p> </p>
Native space mesh descriptors computed with FreeSurfer 6 for all ABIDE I subjects
<p># ABIDE I FreeSurfer 6 'native space descriptors' data</p> <p><br> This archive contains the following ABIDE I FreeSurfer 6 native space mesh descriptors:<br> thickness, area, volume, sulc, curv, jacobian_white.</p> <p><br> ## Credits</p> <p>This data is derived from the MRI scans of the ABIDE I dataset:</p> <p>* ABIDE I dataset: https://fcon_1000.projects.nitrc.org/indi/abide/</p> <p>Quoting from that website:</p> <p> "The Autism Brain Imaging Data Exchange I (ABIDE I) represents the first<br> ABIDE initiative. Started as a grass roots effort, ABIDE I involved 17<br> international sites, sharing previously collected resting state functional<br> magnetic resonance imaging (R-fMRI), anatomical and phenotypic datasets<br> made available for data sharing with the broader scientific community.<br> This effort yielded 1112 dataset, including 539 from individuals with<br> ASD and 573 from typical controls (ages 7-64 years, median 14.7 years<br> across groups). This aggregate was released in August 2012. Its<br> establishment demonstrated the feasibility of aggregating resting<br> state fMRI and structural MRI data across sites; the rate of these<br> data use and resulting publications (see Manuscripts) have shown its<br> utility for capturing whole brain and regional properties of the brain<br> connectome in Autism Spectrum Disorder (ASD). In accordance with<br> HIPAA guidelines and 1000 Functional Connectomes Project / INDI<br> protocols, all datasets have been anonymized, with no protected<br> health information included."</p> <p>Citation: Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., ... & Milham, M. P. (2014).<br> The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 19(6), 659-667.</p> <p>## How this data was produced</p> <p>The following steps were used to create the data:</p> <p>* We downloaded all available MRI scans for the ABIDE I subjects (1035 subjects).<br> * We pre-processed all subjects in FreeSurfer version 6 (https://freesurfer.net) by running the full recon-all pipeline for each subject.<br> - We did not run any quality metrics on the scans or exclude any subjects.</p> <p><br> ## Contained files</p> <p>* In order to reduce the size of this dataset, for each subject, we only included the following files:<br> - <subject>/surf/lh.thickness : the per-vertex cortical thickness for the left hemisphere<br> - <subject>/surf/rh.thickness : the per-vertex cortical thickness for the right hemisphere<br> - <subject>/surf/lh.area : the per-vertex area of the white surface for the left hemisphere<br> - <subject>/surf/rh.area : the per-vertex area of the white surface for the right hemisphere<br> - <subject>/surf/lh.volume : the per-vertex cortical volume for the left hemisphere<br> - <subject>/surf/rh.volume : the per-vertex cortical volume for the right hemisphere<br> - <subject>/surf/lh.sulc : the per-vertex sulcal depth for the left hemisphere<br> - <subject>/surf/rh.sulc : the per-vertex sulcal depth for the right hemisphere<br> - <subject>/surf/lh.curv : the per-vertex mean curvature of the white surface for the left hemisphere<br> - <subject>/surf/rh.curv : the per-vertex mean curvature of the white surface for the right hemisphere<br> - <subject>/surf/lh.jacobian_white : the per-vertex jacobian for the left hemisphere<br> - <subject>/surf/rh.jacobian_white : the per-vertex jacobian for the right hemisphere</p> <p>All files are in binary FreeSurfer curv format.</p> <p><br> ## What is NOT contained</p> <p>* The ABIDE demographics information (metadata on the subjects, like age, ...) is not included, you can get it from the ABIDE website.</p> <p>## Author and License</p> <p>Note: For the authors of the original ABIDE I dataset, see the Credits section above.</p> <p>This lgi data was created by:</p> <p> Dr. Tim Schäfer<br> Postdoc Computational Neuroimaging<br> Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy<br> University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany<br> http://rcmd.org/ts</p> <p>The data is published under the following license:</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode.txt or the file LICENSE for the full legal code.</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/ for an easy explanation of what this license means for you.</p> <p> </p>
Brain labels computed with FreeSurfer 6 for all ABIDE I subjects
<p># ABIDE I FreeSurfer 6 'label' data</p> <p><br> This archive contains the following ABIDE I FreeSurfer 6 labels:<br> cortex, aparc, aparc.a2009s.</p> <p><br> ## Credits</p> <p>This data is derived from the MRI scans of the ABIDE I dataset:</p> <p>* ABIDE I dataset: https://fcon_1000.projects.nitrc.org/indi/abide/</p> <p>Quoting from that website:</p> <p> "The Autism Brain Imaging Data Exchange I (ABIDE I) represents the first<br> ABIDE initiative. Started as a grass roots effort, ABIDE I involved 17<br> international sites, sharing previously collected resting state functional<br> magnetic resonance imaging (R-fMRI), anatomical and phenotypic datasets<br> made available for data sharing with the broader scientific community.<br> This effort yielded 1112 dataset, including 539 from individuals with<br> ASD and 573 from typical controls (ages 7-64 years, median 14.7 years<br> across groups). This aggregate was released in August 2012. Its<br> establishment demonstrated the feasibility of aggregating resting<br> state fMRI and structural MRI data across sites; the rate of these<br> data use and resulting publications (see Manuscripts) have shown its<br> utility for capturing whole brain and regional properties of the brain<br> connectome in Autism Spectrum Disorder (ASD). In accordance with<br> HIPAA guidelines and 1000 Functional Connectomes Project / INDI<br> protocols, all datasets have been anonymized, with no protected<br> health information included."</p> <p>Citation: Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., ... & Milham, M. P. (2014).<br> The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 19(6), 659-667.</p> <p>## How this data was produced</p> <p>The following steps were used to create the data:</p> <p>* We downloaded all available MRI scans for the ABIDE I subjects (1035 subjects).<br> * We pre-processed all subjects in FreeSurfer version 6 (https://freesurfer.net) by running the full recon-all pipeline for each subject.<br> - We did not run any quality metrics on the scans or exclude any subjects.</p> <p><br> ## Contained files</p> <p>* In order to reduce the size of this dataset, for each subject, we only included the following files:<br> - <subject>/label/lh.cortex.label : label identifying which mesh vertices belong to cortex versus medial wall, for left hemisphere.<br> - <subject>/label/rh.cortex.label : label identifying which mesh vertices belong to cortex versus medial wall, for right hemisphere.<br> - <subject>/label/lh.aparc.annot : Desikan atlas surface parcellation for left hemisphere.<br> - <subject>/label/rh.aparc.annot : Desikan atlas surface parcellation for right hemisphere.<br> - <subject>/label/lh.aparc.a2009s.annot : Destrieux atlas surface parcellation for left hemisphere.<br> - <subject>/label/rh.aparc.a2900s.annot : Destrieux atlas surface parcellation for right hemisphere.</p> <p><br> All files are in ASCII FreeSurfer label format.<br> For the annot files, see FreeSurferColorLut.txt that comes with FreeSurfer for meaning of integers specifying a region.</p> <p>## What is NOT contained</p> <p>* The ABIDE demographics information (metadata on the subjects, like age, ...) is not included, you can get it from the ABIDE website.</p> <p>## Author and License</p> <p>Note: For the authors of the original ABIDE I dataset, see the Credits section above.</p> <p>This label data was created by:</p> <p> Dr. Tim Schäfer<br> Postdoc Computational Neuroimaging<br> Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy<br> University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany<br> http://rcmd.org/ts</p> <p>The data is published under the following license:</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode.txt or the file LICENSE for the full legal code.</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/ for an easy explanation of what this license means for you.</p> <p> </p>
Brain volumes computed with FreeSurfer 6 for all ABIDE I subjects
<p># ABIDE I FreeSurfer 6 'brain volume' data</p> <p><br> This archive contains the following ABIDE I FreeSurfer 6 volumes:<br> mri/brain.mgz, mri/brain_mask.mgz, mri/aseg.mgz, mri/wm.mgz.</p> <p><br> ## Credits</p> <p>This data is derived from the MRI scans of the ABIDE I dataset:</p> <p>* ABIDE I dataset: https://fcon_1000.projects.nitrc.org/indi/abide/</p> <p>Quoting from that website:</p> <p> "The Autism Brain Imaging Data Exchange I (ABIDE I) represents the first<br> ABIDE initiative. Started as a grass roots effort, ABIDE I involved 17<br> international sites, sharing previously collected resting state functional<br> magnetic resonance imaging (R-fMRI), anatomical and phenotypic datasets<br> made available for data sharing with the broader scientific community.<br> This effort yielded 1112 dataset, including 539 from individuals with<br> ASD and 573 from typical controls (ages 7-64 years, median 14.7 years<br> across groups). This aggregate was released in August 2012. Its<br> establishment demonstrated the feasibility of aggregating resting<br> state fMRI and structural MRI data across sites; the rate of these<br> data use and resulting publications (see Manuscripts) have shown its<br> utility for capturing whole brain and regional properties of the brain<br> connectome in Autism Spectrum Disorder (ASD). In accordance with<br> HIPAA guidelines and 1000 Functional Connectomes Project / INDI<br> protocols, all datasets have been anonymized, with no protected<br> health information included."</p> <p>Citation: Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., ... & Milham, M. P. (2014).<br> The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 19(6), 659-667.</p> <p>## How this data was produced</p> <p>The following steps were used to create the data:</p> <p>* We downloaded all available MRI scans for the ABIDE I subjects (1035 subjects).<br> * We pre-processed all subjects in FreeSurfer version 6 (https://freesurfer.net) by running the full recon-all pipeline for each subject.<br> - We did not run any quality metrics on the scans or exclude any subjects.</p> <p><br> ## Contained files</p> <p>* In order to reduce the size of this dataset, for each subject, we only included the following files:</p> <p> - <subject>/mri/brain.mgz: the full brain, in FreeSurfer standard orientation ("conformed")</p> <p> - <subject>/mri/brain_mask.mgz: binary mask separating brain from background</p> <p> - <subject>/mri/aseg.mgz: brain segmentation, assigning voxels to regions. The region code for the voxel values can be found in the FreeSurferColorLUT.txt file that comes with FreeSurfer 6.</p> <p> - <subject>/mri/wm.mgz: binary mask separating white matter from everything else</p> <p>All files are in FreeSurfer MGZ format.</p> <p>## What is NOT contained</p> <p>* The ABIDE demographics information (metadata on the subjects, like age, ...) is not included, you can get it from the ABIDE website.</p> <p>## Author and License</p> <p>Note: For the authors of the original ABIDE I dataset, see the Credits section above.</p> <p>This mri volume data was created by:</p> <p> Dr. Tim Schäfer<br> Postdoc Computational Neuroimaging<br> Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy<br> University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany<br> http://rcmd.org/ts</p> <p>The data is published under the following license:</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode.txt or the file LICENSE for the full legal code.</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/ for an easy explanation of what this license means for you.</p>
Surface transforms (sphere.reg) computed with FreeSurfer 6 for all ABIDE I subjects
<p># ABIDE I FreeSurfer 6 'surface transforms' data</p> <p><br> This archive contains files needed to map surface-based subject data to other subjects, templates or spaces.</p> <p><br> ## Credits</p> <p>This data is derived from the MRI scans of the ABIDE I dataset:</p> <p>* ABIDE I dataset: https://fcon_1000.projects.nitrc.org/indi/abide/</p> <p>Quoting from that website:</p> <p> "The Autism Brain Imaging Data Exchange I (ABIDE I) represents the first<br> ABIDE initiative. Started as a grass roots effort, ABIDE I involved 17<br> international sites, sharing previously collected resting state functional<br> magnetic resonance imaging (R-fMRI), anatomical and phenotypic datasets<br> made available for data sharing with the broader scientific community.<br> This effort yielded 1112 dataset, including 539 from individuals with<br> ASD and 573 from typical controls (ages 7-64 years, median 14.7 years<br> across groups). This aggregate was released in August 2012. Its<br> establishment demonstrated the feasibility of aggregating resting<br> state fMRI and structural MRI data across sites; the rate of these<br> data use and resulting publications (see Manuscripts) have shown its<br> utility for capturing whole brain and regional properties of the brain<br> connectome in Autism Spectrum Disorder (ASD). In accordance with<br> HIPAA guidelines and 1000 Functional Connectomes Project / INDI<br> protocols, all datasets have been anonymized, with no protected<br> health information included."</p> <p>Citation: Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., ... & Milham, M. P. (2014).<br> The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 19(6), 659-667.</p> <p>## How this data was produced</p> <p>The following steps were used to create the data:</p> <p>* We downloaded all available MRI scans for the ABIDE I subjects (1035 subjects).<br> * We pre-processed all subjects in FreeSurfer version 6 (https://freesurfer.net) by running the full recon-all pipeline for each subject.<br> - We did not run any quality metrics on the scans or exclude any subjects.</p> <p><br> ## Contained files</p> <p>* In order to reduce the size of this dataset, for each subject, we only included the following files:</p> <p> - <subject>/surf/lh.sphere.reg: spherical registration information for left hemisphere</p> <p> - <subject>/surf/rh.sphere.reg: spherical registration information for right hemisphere</p> <p>## What is NOT contained</p> <p>* The ABIDE demographics information (metadata on the subjects, like age, ...) is not included, you can get it from the ABIDE website.</p> <p>## Author and License</p> <p>Note: For the authors of the original ABIDE I dataset, see the Credits section above.</p> <p>This data was created by:</p> <p> Dr. Tim Schäfer<br> Postdoc Computational Neuroimaging<br> Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy<br> University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany<br> http://rcmd.org/ts</p> <p>The data is published under the following license:</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode.txt or the file LICENSE for the full legal code.</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/ for an easy explanation of what this license means for you.</p>
Brain cortical volume and area from Freesurfer's parcellation in a sample of healthy volunteers from South America
<p>This dataset aims to deepen the analysis of cortical gyral and sulcal asymmetry of the entire cerebral cortex of healthy adult individuals by quantifying the gray matter content of the right and left hemispheres in a reference sample from South America. The subjects were sampled from populations scarcely represented in MRI research, which tends to be biased towards groups of European ancestry from Europe and North America. In contrast, the population under study is an admixture of Native American, European, and African components that contributed to a variable extent to their gene pool. Consequently, this study will add to expanding the diversity in brain morphometric data and the construction of more population-representative references.</p>
Brain cortical volume and area from Freesurfer's parcellation in a sample of healthy volunteers from South America
Open the record for dataset details and reuse information.
Local Gyrification Index computed with FreeSurfer 6 for all ABIDE I subjects
<p># ABIDE I FreeSurfer 6 'local gyrification index' (lGI) data</p> <p>DOI of this dataset: 10.5281/zenodo.7132610</p> <p>This directory 'abide_freesurfer6_lgi' contains the ABIDE I FreeSurfer 6 'local gyrification index' (lGI) data and meshes.</p> <p><br> ## Credits</p> <p>This data is derived from the MRI scans of the ABIDE I dataset:</p> <p>* ABIDE I dataset: https://fcon_1000.projects.nitrc.org/indi/abide/</p> <p>Quoting from that website:</p> <p> "The Autism Brain Imaging Data Exchange I (ABIDE I) represents the first<br> ABIDE initiative. Started as a grass roots effort, ABIDE I involved 17<br> international sites, sharing previously collected resting state functional<br> magnetic resonance imaging (R-fMRI), anatomical and phenotypic datasets<br> made available for data sharing with the broader scientific community.<br> This effort yielded 1112 dataset, including 539 from individuals with<br> ASD and 573 from typical controls (ages 7-64 years, median 14.7 years<br> across groups). This aggregate was released in August 2012. Its<br> establishment demonstrated the feasibility of aggregating resting<br> state fMRI and structural MRI data across sites; the rate of these<br> data use and resulting publications (see Manuscripts) have shown its<br> utility for capturing whole brain and regional properties of the brain<br> connectome in Autism Spectrum Disorder (ASD). In accordance with<br> HIPAA guidelines and 1000 Functional Connectomes Project / INDI<br> protocols, all datasets have been anonymized, with no protected<br> health information included."</p> <p>Citation: Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., ... & Milham, M. P. (2014).<br> The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular psychiatry, 19(6), 659-667.</p> <p>## How this data was produced</p> <p>The following steps were used to create the data:</p> <p>* We downloaded all available MRI scans for the ABIDE I subjects (1035 subjects).<br> * We pre-processed all subjects in FreeSurfer version 6 (https://freesurfer.net) by running the full recon-all pipeline for each subject.<br> - We did not run any quality metrics on the scans or exclude any subjects.<br> * We computed pial-lgi (Schaer et al. 2008, https://doi.org/10.1109/TMI.2007.903576) as implemented in FreeSurfer 6 for all subjects.<br> - For some of the subjects, MRI data was not available or lgi could not be computed due to very bad quality of the (or a completely failed) surface reconstruction. These subjects are listed in the file 'subjects_lgi_computation_failed.txt' (14 of 1035 subjects).<br> - All subjects for which lgi computation succeeded for both hemispheres are listed in the file 'subjects.txt' (1021 of 1035 subjects).</p> <p><br> ## Contained files</p> <p>* In order to reduce the size of this dataset, for each subject, we only included the following files:<br> - <subject>/surf/lh.pial : the pial surface mesh for the left hemisphere, in FreeSurfer surf format.<br> - <subject>/surf/rh.pial : the pial surface mesh for the right hemisphere, in FreeSurfer surf format.<br> - <subject>/surf/lh.pial_lgi : the per-vertex lgi values for the left hemisphere, in FreeSurfer curv format.<br> - <subject>/surf/rh.pial_lgi : the per-vertex lgi values for the right hemisphere, in FreeSurfer curv format.</p> <p>See the section 'How this data was produced' for information on the files 'subjects.txt' and 'subjects_lgi_computation_failed.txt'.</p> <p>## What is NOT contained</p> <p>* The ABIDE demographics information (metadata on the subjects, like age, ...) is not included, you can get it from the ABIDE website.<br> * The lgi values are only contained in native space. Standard space data is available as a separate download on Zenodo.</p> <p>## Author and License</p> <p>Note: For the authors of the original ABIDE I dataset, see the Credits section above.</p> <p>This lgi data was created by:</p> <p> Dr. Tim Schäfer<br> Postdoc Computational Neuroimaging<br> Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy<br> University Hospital Frankfurt, Goethe University Frankfurt am Main, Germany<br> http://rcmd.org/ts</p> <p>The data is published under the following license:</p> <p>Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/legalcode.txt or the file LICENSE for the full legal code.</p> <p>See https://creativecommons.org/licenses/by-nc-sa/3.0/ for an easy explanation of what this license means for you.</p> <p> </p>
Template connectome harmonics for FreeSurfer template cortical surfaces using Gibbs Tractography Dataset
<p>The folder contains connectome harmonics for template surface meshes cvs_avg35_inMNI152, fsaverage45 and fsaverage5 from Freesurfer, using the Gibbs connectome tractography streamlines.<br> The connectome harmonics framework is integrated to the SCRIPTS pipeline, and the files present here use default parameters from Table 1 in Naze et al. 2020.</p> <p>Each .mat file include:<br> - graph Laplacian (L)<br> - connectome harmonics (H)<br> - connectome harmonics projected in the Desikan-Killiany atlas (H_DSK)<br> - local connectivity adjacency matrix (A_local)<br> - long-range connectivity adjacency matrix (A_ctx)<br> - vertices and faces of the cortical surface mesh (white matter - gray matter boundary)<br> - degree matrix (of combined adjacency matrices)<br> - eigenvalues of the eigendecomposition<br> - r, the ratio of local connections over all connections (local_vs_global_ratio)<br> - average (mu_cc) and standard deviation (sigma_cc) of the long-range connectome<br> - z_C, the weight threshold applied to the high resolution conectome to obtain its adjacency matrix (ta_zsc)</p> <p><br> Reference:<br> Naze S., Proix T., Atasoy S. & Kozloski J.R. (2020) Robustness of connectome harmonics to local gray matter and long-range white matter connectivity changes. <em>Neuroimage.</em></p>
Analysis of the extent of limbic system changes in multiple sclerosis using FreeSurfer and voxel-based morphometry approaches
<p>Background and Purpose: The limbic brain is involved in diverse cognitive, emotional, and autonomic functions. Injury of the various parts of the limbic system have been correlated with clinical deficits in MS. The purpose of this study was to comprehensively examine different regions of the subcortical limbic system to assess the extent of damage within this entire system as it may be pertinent in correlating with specific aspects of cognitive and behavioral dysfunction in MS by using a fully automated, unbiased segmentation approach. </p> <p>Results: The mean [95% confidence interval] of the total limbic system volume was lower (0.22% [0.21-0.23]) in MS compared to healthy controls (0.27%, [0.25-0.29], p < .001). Pairwise comparisons of individual limbic regions between MS and controls was significant in the nucleus accumbens (0.046%, [0.043-0.050] vs. 0.059%, [0.051-0.066], p = .005), hypothalamus (0.062%, [0.059-0.065] vs. 0.074%, [0.068-0.081], p = .001), basal forebrain (0.038%, [0.036-0.040] vs. 0.047%, [0.042-0.051], p = .001), hippocampus (0.47%, [0.45-0.49] vs. 0.53%, [0.49-0.57], p = .004), and anterior thalamus (0.077%, [0.072-0.082] vs. 0.093%, [0.084-0.10], p = .001) after Bonferroni correction. Volume of several limbic regions was significantly correlated with T2 lesion burden and brain parenchymal fraction (BPF). Multiple regression model showed minimal influence of BPF on limbic brain volume and no influence of other demographic and disease state variables. VBM analysis showed cluster differences in the fornix and anterior thalamic nuclei at threshold p < 0.05 after adjusting for covariates but the results were insignificant after family-wise error corrections. </p> <p>Conclusions: The results show evidence that brain volume loss is fairly extensive in the limbic brain. Given the significance of the limbic system in many disease states including MS, such volumetric analyses can be expanded to studying cognitive and emotional disturbances in larger clinical trials. FreeSurfer ScLimbic pipeline provided an efficient and reliable methodology for examining many of the subcortical structures related to the limbic brain. </p>
Analysis of the extent of limbic system changes in multiple sclerosis using FreeSurfer and voxel-based morphometry approaches
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