Study: Perspective for NHP_NNP
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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The NonHuman Primate Neuroimaging & Neuroanatomy Project
Macaque, Human, Chimpanzee
The scenes for this study were created using a newer version of wb_view, they will not display properly using wb_view v1.4.2. Please keep an eye out for the new wb_view release coming early 2021.
Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how "functional connectivity" from fMRI and "tractographic connectivity" from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.
- Takuya Hayashi
- Yujie Hou
- Matthew F Glasser
- Joonas A Autio
- Kenneth Knoblauch
- Miho Inoue-Murayama
- Tim Coalson
- Essa Yacoub
- Stephen Smith
- Henry Kennedy
- David C Van Essen
- Oxford University
- Institute of Neuroscience, Shanghai
- University of Lyon
- Washington University in St. Louis
- Kyoto University
- University of Minnesota
- Fig. 1 Cortical thickness in human, chimpanzee, macaque and marmoset
- Fig. 2 Cross-species comparison of individual’s cortical surface, average and variability
- Fig. 3 Standardized venous sinus maps for each species of human, macaque and marmoset
- Fig. 4A Default mode network in human
- Fig. 4B Default mode network in macaque.
- Fig. 8 Results of simulation for partial volume/geometric effects in ‘layer’ fMRI analysis at various resolutions in macaque cerebral cortex.