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タイトル: The nonhuman primate neuroimaging and neuroanatomy project
著者: Hayashi, Takuya
Hou, Yujie
Glasser, Matthew F
Autio, Joonas A
Knoblauch, Kenneth
Inoue-Murayama, Miho
Coalson, Tim
Yacoub, Essa
Smith, Stephen
Kennedy, Henry
Van Essen, David C
著者名の別形: 林, 拓也
村山, 美穂
キーワード: Functional MRI
Diffusion MRI
Retrograde tracer
Connectivity
Connectome
Hierarchy
Marmoset
Macaque
Human
発行日: Apr-2021
出版者: Elsevier BV
誌名: NeuroImage
巻: 229
論文番号: 117726
抄録: 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.
著作権等: © 2021 The Author(s). Published by Elsevier Inc.
This is an open access article under the Creative Commons Attribution 4.0 International license.
URI: http://hdl.handle.net/2433/275905
DOI(出版社版): 10.1016/j.neuroimage.2021.117726
PubMed ID: 33484849
出現コレクション:学術雑誌掲載論文等

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