Scene: Supplemental Figure S3
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 S3
DESCRIPTION:
Panels A – D show the probabilistic map of cortical gray matter, using the partial-volume method at 0.7 mm, in four parasagittal slices through the 210V average T1w volume. In many regions a clear red/orange ribbon is evident, indicating locations where alignment of the cortical grey matter ribbon is reasonably high (gray-matter probability > 0.8). These regions include most of the cortex along the medial aspect of the hemisphere (panel A), plus the insula, orbitofrontal and anterior and inferior temporal cortex, and the central sulcus. More laterally (panels B through D), many sulcal regions and some gyral regions have only modest cortical gray matter probabilities (0.5 - 0.7; green, yellow), particularly over much of prefrontal and parietal cortex. These lower probabilities indicate extensive residual mixing of tissue classes across subjects that were not well aligned by volume-based registration. Panel E shows a histogram of the probabilities across the whole volume. The average probability of cortex where cortex is more probable than other classes is 0.730. In contrast, when data is analyzed on the surface using ribbon mapping, the only tissue mixing effects are from partial volume effects due to the acquisition resolution or surface placement problems, as each subject’s surfaces are used to extract cortical signal from each subject’s own volume files and the comparable value is 0.92 (for 0.7 mm resolution data). See Supplemental Methods Sections M2 and M5.
TAGS:
Modality:T1-weighted