Scene: Supplemental Figure S8
Data Use Terms
WU-Minn HCP Consortium Open Access Data Use Terms
1. I will not attempt to establish the identity of or attempt to contact any of the included human subjects.
2. I understand that under no circumstances will the code that would link these data to Protected Health Information be given to me, nor will any additional information about individual human subjects be released to me under these Open Access Data Use Terms.
3. I will comply with all relevant rules and regulations imposed by my institution. This may mean that I need my research to be approved or declared exempt by a committee that oversees research on human subjects, e.g. my IRB or Ethics Committee. The released HCP data are not considered de-identified, insofar as certain combinations of HCP Restricted Data (available through a separate process) might allow identification of individuals. Different committees operate under different national, state and local laws and may interpret regulations differently, so it is important to ask about this. If needed and upon request, the HCP will provide a certificate stating that you have accepted the HCP Open Access Data Use Terms.
4. I may redistribute original WU-Minn HCP Open Access data and any derived data as long as the data are redistributed under these same Data Use Terms.
5. I will acknowledge the use of WU-Minn HCP data and data derived from WU-Minn HCP data when publicly presenting any results or algorithms that benefitted from their use.
1. Papers, book chapters, books, posters, oral presentations, and all other printed and digital presentations of results derived from HCP data should contain the following wording in the acknowledgments section: "Data were provided [in part] by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University."
2. Authors of publications or presentations using WU-Minn HCP data should cite relevant publications describing the methods used by the HCP to acquire and process the data. The specific publications that are appropriate to cite in any given study will depend on what HCP data were used and for what purposes. An annotated and appropriately up-to-date list of publications that may warrant consideration is available at http://www.humanconnectome.org/about/acknowledgehcp.html
3. The WU-Minn HCP Consortium as a whole should not be included as an author of publications or presentations if this authorship would be based solely on the use of WU-Minn HCP data.
6. Failure to abide by these guidelines will result in termination of my privileges to access WU-Minn HCP data.
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Files
study:
The Impact of Traditional Neuroimaging Methods on the Spatial Localization of Cortical Areas
SCENE FILE:
Coalson_et_al_2018_suppl
SCENE:
Supplemental Figure S8
DESCRIPTION:
This figure shows the separability of ideal upper versus lower laminar signal. For every subject, a layer 4 surface is approximated by the equal volume method (locally, the same amount of cortical volume is superficial to the new surface as is deeper than it), and used to create volumetric simulated signal maps of the superficial and deep layers at several resolutions. These volumes are then mapped back onto the same surfaces with the ribbon mapping technique (the “Superficial Surfaces” side uses the pial and approximate layer 4 surfaces, the “Deep Surfaces” side uses the approximate layer 4 and white matter surfaces) and then averaged across subjects. The use of a large group and surface-based techniques enables some separation of laminar level effects at relatively low resolutions (2 mm). In individual subject data, however, these maps contain significant noise from geometric effects of surface/voxel intersection. At higher resolutions, the separation between peaks in the histograms is larger, signifying better potential separation of signal between laminae in surface-based group analysis. See Supplemental Methods Section M2.
TAGS:
Surface Mesh:32k fs LR, Registration:MSMAll