PSYCH OpenIR  > 中国科学院行为科学重点实验室
Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI
Schaefer, Alexander1,2; Kong, Ru1,2; Gordon, Evan M.3; Laumann, Timothy O.4; Zuo, Xi-Nian5,6; Holmes, Avram J.7; Eickhoff, Simon B.8,9; Thomas, B. T.1,2,10,11
第一作者Alexander Schaefer
2018-09-01
发表期刊CEREBRAL CORTEX
通讯作者邮箱thomas.yeo@nus.edu.sg
ISSN1047-3211
卷号28期号:9页码:3095-3114
摘要

A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here, we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than 4 previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured subareal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multiresolution parcellations generated from 1489 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/ tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).

关键词Brain Parcellation Brodmann Areas Cytoarchitecture Resting-state Functional Connectivity Retinotopy
DOI10.1093/cercor/bhx179
语种英语
项目资助者Singapore Ministry of Education (MOE) ; National University of Singapore (NUS) Strategic Research ; NUS School of Medicine (SOM) Aspiration Fund ; Singapore National Medical Research Council ; NUS Young Investigator Award ; Singapore National Research Foundation (NRF) ; DAAD postdoctoral fellowship ; NIMH ; National Basic Research (973) Program ; Natural Science Foundation of China ; Center for Functional Neuroimaging Technologies ; Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital ; Human Connectome Project, WU-Minn Consortium ; McDonnell Center for Systems Neuroscience at Washington University
资助项目Singapore Ministry of Education (MOE)[MOE2014-T2-2-016] ; National University of Singapore (NUS) Strategic Research[DPRT/944/09/14] ; NUS School of Medicine (SOM) Aspiration Fund[R185000271720] ; Singapore National Medical Research Council[CBRG/0088/2015] ; NUS Young Investigator Award ; Singapore National Research Foundation (NRF) ; DAAD postdoctoral fellowship ; NIMH[MH100872] ; NIMH[K01MH099232] ; National Basic Research (973) Program[2015CB351702] ; Natural Science Foundation of China[81 471 740] ; Natural Science Foundation of China[81220108014] ; Center for Functional Neuroimaging Technologies[P41EB015896] ; Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital[S10RR023401] ; Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital[S10RR023043] ; Human Connectome Project, WU-Minn Consortium[1U54MH091657] ; McDonnell Center for Systems Neuroscience at Washington University
WOS研究方向Neurosciences & Neurology
WOS类目Neurosciences
WOS记录号WOS:000443545600003
出版者OXFORD UNIV PRESS INC
关键词[WOS]Resting-state Fmri ; Independent Component Analysis ; Human Connectome Project ; Primary Motor Cortex ; Visual Area Mt ; Human Brain ; Life-span ; Network Analysis ; Individual-differences ; Association Networks
引用统计
被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/26896
专题中国科学院行为科学重点实验室
通讯作者Thomas, B. T.
作者单位1.Natl Univ Singapore, Singapore Inst Neurotechnol, ASTAR NUS Clin Imaging Res Ctr, Dept Elect & Comp Engn, Singapore, Singapore
2.Natl Univ Singapore, Memory Networks Program, Singapore, Singapore
3.VISN 17 Ctr Excellence Res Returning War Vet, Waco, TX USA
4.Washington Univ, Dept Neurol, St Louis, MO USA
5.Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing, Peoples R China
6.Univ Chinese Acad Sci, Beijing, Peoples R China
7.Yale Univ, New Haven, CT USA
8.Heinrich Heine Univ Dusseldorf, Fac Med, Inst Syst Neurosci, Dusseldorf, Germany
9.Res Ctr Julich, Inst Neurosci & Med Brain & Behav INM 7, Julich, Germany
10.Massachusetts Gen Hosp, Martinos Ctr Biomed Imaging, Charlestown, MA USA
11.Duke NUS Med Sch, Ctr Cognit Neurosci, Singapore, Singapore
推荐引用方式
GB/T 7714
Schaefer, Alexander,Kong, Ru,Gordon, Evan M.,et al. Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI[J]. CEREBRAL CORTEX,2018,28(9):3095-3114.
APA Schaefer, Alexander.,Kong, Ru.,Gordon, Evan M..,Laumann, Timothy O..,Zuo, Xi-Nian.,...&Thomas, B. T..(2018).Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI.CEREBRAL CORTEX,28(9),3095-3114.
MLA Schaefer, Alexander,et al."Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI".CEREBRAL CORTEX 28.9(2018):3095-3114.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Local-Global Parcell(1890KB)期刊论文作者接受稿限制开放CC BY-NC-SA浏览 请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Schaefer, Alexander]的文章
[Kong, Ru]的文章
[Gordon, Evan M.]的文章
百度学术
百度学术中相似的文章
[Schaefer, Alexander]的文章
[Kong, Ru]的文章
[Gordon, Evan M.]的文章
必应学术
必应学术中相似的文章
[Schaefer, Alexander]的文章
[Kong, Ru]的文章
[Gordon, Evan M.]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。