The minimal preprocessing pipelines for the Human Connectome Project.

doi:10.1016/J.NEUROIMAGE.2013.04.127

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The minimal preprocessing pipelines for the Human Connectome Project.

Journal Article•DOI•

The minimal preprocessing pipelines for the Human Connectome Project.

Matthew F. Glasser¹, Stamatios N. Sotiropoulos², J. Anthony Wilson¹, Timothy S. Coalson¹, Bruce Fischl³, Jesper L. R. Andersson², Junqian Xu⁴, Saâd Jbabdi², Matthew A. Webster², Jonathan R. Polimeni³, David C. Van Essen¹, Mark Jenkinson² - Show less +8 more•Institutions (4)

Washington University in St. Louis¹, University of Oxford², Harvard University³, University of Minnesota⁴

15 Oct 2013-NeuroImage (Neuroimage)-Vol. 80, pp 105-124

TL;DR: The minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space are described.

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About: This article is published in NeuroImage.The article was published on 2013-10-15 and is currently open access. It has received 3992 citations till now.

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Journal Article•DOI•

The WU-Minn Human Connectome Project: An Overview

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David C. Van Essen¹, Stephen M. Smith², M Deanna¹, Timothy E.J. Behrens², Essa Yacoub³, Kamil Ugurbil³ - Show less +2 more•Institutions (3)

Washington University in St. Louis¹, University of Oxford², University of Minnesota³

15 Oct 2013-NeuroImage

TL;DR: Progress made during the first half of the Human Connectome Project project in refining the methods for data acquisition and analysis provides grounds for optimism that the HCP datasets and associated methods and software will become increasingly valuable resources for characterizing human brain connectivity and function, their relationship to behavior, and their heritability and genetic underpinnings.

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4,388 citations

Cites background or methods from "The minimal preprocessing pipelines..."

...The HCP minimal preprocessing pipelines are described in detail in four other articles in this special issue (Barch et al., 2013; Glasser et al., 2013b; Smith et al., 2013; Sotiropoulos et al., 2013c) and are summarized only briefly below....
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...Workbench is especially well suited for handling grayordinate representations (surface vertices and gray-matter voxels) in the CIFTI format (see Glasser et al., 2013b; Marcus et al., 2013)....
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...%) of the total temporal variance in the minimally preprocessed datasets (Glasser et al., 2013b; Marcus et al., 2013)....
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...Structural scans include a pair of T1-weighted and a pair of T2-weighted images, all acquired at 0.7 mm isotropic resolution (Glasser et al., 2013b), plus ancillary scans, for a session duration of ~40 min....
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...These refinements have been consolidated into a set of well-defined preprocessing pipelines that consistently and reliably carry out distortion correction and spatial alignment for each of the four imaging modalities (Glasser et al., 2013b)....
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Journal Article•DOI•

A multi-modal parcellation of human cerebral cortex

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Matthew F. Glasser¹, Timothy S. Coalson¹, Emma C. Robinson², Emma C. Robinson³, Carl D. Hacker¹, John W. Harwell¹, Essa Yacoub⁴, Kamil Ugurbil⁴, Jesper L. R. Andersson⁵, Christian F. Beckmann², Mark Jenkinson⁵, Stephen Smith⁵, David C. Van Essen¹ - Show less +9 more•Institutions (5)

Washington University in St. Louis¹, University of Oxford², Imperial College London³, University of Minnesota⁴, John Radcliffe Hospital⁵

11 Aug 2016-Nature

TL;DR: Using multi-modal magnetic resonance images from the Human Connectome Project and an objective semi-automated neuroanatomical approach, 180 areas per hemisphere are delineated bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults.

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Abstract: Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

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3,414 citations

Cites background from "The minimal preprocessing pipelines..."

...(5) Confidence was increased if prior literature described a corresponding areal border....
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Journal Article•DOI•

Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity

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Emily S. Finn¹, Xilin Shen¹, Dustin Scheinost¹, Monica D. Rosenberg¹, Jessica S. Huang¹, Marvin M. Chun¹, Xenophon Papademetris¹, R. Todd Constable¹ - Show less +4 more•Institutions (1)

Yale University¹

01 Nov 2015-Nature Neuroscience

TL;DR: In this article, the authors show that every individual has a unique pattern of functional connections between brain regions, which act as a fingerprint that can accurately identify the individual from a large group.

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Abstract: This study shows that every individual has a unique pattern of functional connections between brain regions. This functional connectivity profile acts as a ‘fingerprint’ that can accurately identify the individual from a large group. Furthermore, an individual's connectivity profile can predict his or her level of fluid intelligence.

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2,121 citations

Journal Article•DOI•

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture

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Lingzhong Fan, Hai Li, Junjie Zhuo¹, Yu Zhang, Jiaojian Wang¹, Liangfu Chen, Zhengyi Yang, Congying Chu, Sangma Xie, Angela R. Laird², Peter T. Fox³, Simon B. Eickhoff⁴, Chunshui Yu⁵, Tianzi Jiang¹ - Show less +10 more•Institutions (5)

University of Electronic Science and Technology of China¹, Florida International University², University of Texas Health Science Center at San Antonio³, University of Düsseldorf⁴, Tianjin Medical University General Hospital⁵

01 Aug 2016-Cerebral Cortex

TL;DR: A connectivity-based parcellation framework is designed that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture and provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections.

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Abstract: The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.

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1,717 citations

Cites methods from "The minimal preprocessing pipelines..."

...The details of this pipeline have been described previously (Jenkinson et al. 2002, 2012; Glasser et al. 2013; Smith et al. 2013) and are only summarized in the supplement for completeness....
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...details of this pipeline have been described previously (Jenkinson et al. 2002, 2012; Glasser et al. 2013; Smith et al. 2013) and are only summarized in the supplement for completeness....
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Journal Article•DOI•

Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI

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Alexander Schaefer¹, Ru Kong¹, Evan M. Gordon, Timothy O. Laumann², Xi-Nian Zuo³, Avram J. Holmes⁴, Simon B. Eickhoff⁵, B.T. Thomas Yeo⁶, B.T. Thomas Yeo¹ - Show less +5 more•Institutions (6)

National University of Singapore¹, Washington University in St. Louis², Chinese Academy of Sciences³, Yale University⁴, University of Düsseldorf⁵, Harvard University⁶

01 Sep 2018-Cerebral Cortex

TL;DR: The 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.

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Abstract: 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).

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1,567 citations

Cites methods from "The minimal preprocessing pipelines..."

...Details of the HCP data collection, preprocessing and functional connectivity matrix computation can be found elsewhere (HCP S900 manual; Van Essen et al. 2012b; Glasser et al. 2013; Smith et al. 2013)....
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...Details of the HCP data collection, preprocessing, and functional connectivity matrix computation can be found elsewhere (HCP S900 manual; Van Essen et al. 2012b; Glasser et al. 2013; Smith et al. 2013)....
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References

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Open Access

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Journal Article•DOI•

Advances in functional and structural MR image analysis and implementation as FSL.

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Stephen M. Smith¹, Mark Jenkinson¹, Mark W. Woolrich¹, Mark W. Woolrich², Christian F. Beckmann¹, Behrens Tej.¹, Heidi Johansen-Berg¹, Peter R. Bannister¹, M De Luca¹, Ivana Drobnjak¹, D E Flitney¹, Rami K. Niazy¹, J Saunders¹, J Vickers¹, Yongyue Zhang¹, N. De Stefano², J M Brady³, Paul M. Matthews¹ - Show less +14 more•Institutions (3)

John Radcliffe Hospital¹, University of Siena², University of Oxford³

01 Jan 2004-NeuroImage

TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.

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12,097 citations

"The minimal preprocessing pipelines..." refers background or methods in this paper

...FSL is expected to include full CIFTI support in the future, but will provide surface analysis support via GIFTI files in the short-term (e.g. Barch et al., 2013–this issue)....
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...For example, the 2 mm MNI space brain mask distributed with FSL (Smith et al., 2004) contains 228,483 voxels....
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...Subsequently, any repeated runs of T1w and T2w images are aligned with a 6 degree of freedom (DOF) rigid body transformation using FSL's FLIRT (Jenkinson and Smith, 2001; Jenkinson et al., 2002) and averaged (any number of averages are supported)....
[...]
...If knowledge of the spatial relationships needs to be preserved in the external software (an example is FSL's film_gls tool for task fMRI analysis), a CIFTI file can be split into GIFTI surface data and NIFTI volume data, analyzed in separate parts, and then recombined into a CIFTI file....
[...]
...Examples where this is useful include ICA analysis of a CIFTI dense timeseries in FSL's melodic, or element-wise task fMRI analyses with FSL's contrast_mgr or flameo executables....
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Journal Article•DOI•

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

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Rahul S. Desikan¹, Florent Ségonne², Bruce Fischl³, Bruce Fischl², Brian T. Quinn³, Bradford C. Dickerson³, Deborah Blacker³, Randy L. Buckner⁴, Randy L. Buckner³, Anders M. Dale⁵, R. Paul Maguire⁶, Bradley T. Hyman³, Marilyn S. Albert⁷, Ronald J. Killiany¹ - Show less +10 more•Institutions (7)

Boston University¹, Massachusetts Institute of Technology², Harvard University³, Howard Hughes Medical Institute⁴, University of California, San Diego⁵, Pfizer⁶, Johns Hopkins University School of Medicine⁷

01 Jul 2006-NeuroImage

TL;DR: An automated labeling system for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable and may be useful for both morphometric and functional studies of the cerebral cortex.

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9,940 citations

"The minimal preprocessing pipelines..." refers background in this paper

..., 1999b), and automated segmentation of sulci and gyri (Desikan et al., 2006) are among the steps done during this recon-all stage....
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...Spherical inflation of the white matter surface (Fischl et al., 1999a), registration to the fsaverage surface template based on cortical folding patterns (Fischl et al., 1999b), and automated segmentation of sulci and gyri (Desikan et al., 2006) are among the steps done during this recon-all stage....
[...]

Journal Article•DOI•

Fast robust automated brain extraction

[...]

Stephen M. Smith¹•Institutions (1)

John Radcliffe Hospital¹

01 Nov 2002-Human Brain Mapping

TL;DR: An automated method for segmenting magnetic resonance head images into brain and non‐brain has been developed and described and examples of results and the results of extensive quantitative testing against “gold‐standard” hand segmentations, and two other popular automated methods.

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Abstract: An automated method for segmenting magnetic resonance head images into brain and non-brain has been developed. It is very robust and accurate and has been tested on thousands of data sets from a wide variety of scanners and taken with a wide variety of MR sequences. The method, Brain Extraction Tool (BET), uses a deformable model that evolves to fit the brain's surface by the application of a set of locally adaptive model forces. The method is very fast and requires no preregistration or other pre-processing before being applied. We describe the new method and give examples of results and the results of extensive quantitative testing against "gold-standard" hand segmentations, and two other popular automated methods.

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9,887 citations

"The minimal preprocessing pipelines..." refers methods in this paper

...We provide a brief high-level description of all the pipelines, followed by a detailed description of each, including the rationale for choices made in the pipelines and descriptions of the novel methods used in them....
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...We found that this method of bringing the atlas brain mask to the individual's space outperforms other common brain extraction methods like FSL's BET (Smith, 2002), albeit at the cost of increased processing time....
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Journal Article•DOI•

Cortical surface-based analysis. I. Segmentation and surface reconstruction

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Anders M. Dale¹, Bruce Fischl¹, Martin I. Sereno²•Institutions (2)

Harvard University¹, University of California, San Diego²

01 Feb 1999-NeuroImage

TL;DR: A set of automated procedures for obtaining accurate reconstructions of the cortical surface are described, which have been applied to data from more than 100 subjects, requiring little or no manual intervention.

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9,599 citations

Journal Article•DOI•

Improved optimization for the robust and accurate linear registration and motion correction of brain images

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