The WU-Minn Human Connectome Project: An overview

Essen, David C. Van; Smith, Stephen M.; Deanna, M; Behrens, Timothy E.J.; Yacoub, Essa; Uğurbil, Kâmil

doi:10.1016/j.neuroimage.2013.05.041

Cited by 5,016 publications

(5,192 citation statements)

References 61 publications

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“…The results in this paper represent the foundations of a surface-constrained set of functional and diffusion analysis pipelines, inspired by frameworks proposed by the HCP (Glasser et al, 2013;Van Essen et al, 2013), and based on FreeSurfer methods for surface extraction (Fischl et al, 1999b;Fischl, 2012). Studies have shown that surface-constrained analyses: improve the localisation of functional units along the cortical surface Glasser et al, 2013Glasser et al, , 2016bVan Essen et al, 2012); reduce the mixing of white and grey matter fMRI signals during smoothing (Glasser et al, 2013); and increase the alignment of functional areas during registration (Durrleman et al, 2009;Fischl et al, 1999c;Lombaert et al, 2013;Robinson et al, 2014;Wright et al, 2015;Yeo et al, 2010).…”

Section: Discussionmentioning

confidence: 97%

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

et al. 2018

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The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline * Corresponding author Email address: a.makropoulos11@imperial.ac.uk (Antonios Makropoulos) 1 These authors contributed equally Preprint submitted to NeuroImage January 7, 2018peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/125526 doi: bioRxiv preprint first posted online Apr. 10, 2017; consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

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Section: Discussionmentioning

confidence: 97%

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

et al. 2018

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“…Although continued development of prospective methods will improve the way that future studies use structural imaging to study anatomy [see Zaitsev et al, 2015], development of such innovations is not applicable to a number of extremely valuable legacy datasets and to many other on‐going large‐scale data collection initiatives [e.g., ABIDE, ADHD‐200, ADNI, Betula, DLBS, FCON1000, HCP, HABS, NIMH adolescents, PNC, SLS; ADHD‐200‐Consortium, 2012; Biswal et al, 2010; Chan et al, 2014; Dagley et al, 2015; Di Martino et al, 2014; Giedd et al, 1999; Jack et al, 2008; Nilsson et al, 1997, 2004; Park et al, 2012; Satterthwaite et al, 2014; Schaie and Willis, 2010; Van Essen et al, 2012b, 2013]. While many studies have led efforts to correct the motion‐related bias in EPI, less work has demonstrated a suitable technique for mitigating the motion‐related bias on T1w imaging.…”

Section: Discussionmentioning

confidence: 99%

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

Savalia

Agres

Chan

et al. 2016

Human Brain Mapping

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Motion‐contaminated T1‐weighted (T1w) magnetic resonance imaging (MRI) results in misestimates of brain structure. Because conventional T1w scans are not collected with direct measures of head motion, a practical alternative is needed to identify potential motion‐induced bias in measures of brain anatomy. Head movements during functional MRI (fMRI) scanning of 266 healthy adults (20–89 years) were analyzed to reveal stable features of in‐scanner head motion. The magnitude of head motion increased with age and exhibited within‐participant stability across different fMRI scans. fMRI head motion was then related to measurements of both quality control (QC) and brain anatomy derived from a T1w structural image from the same scan session. A procedure was adopted to “flag” individuals exhibiting excessive head movement during fMRI or poor T1w quality rating. The flagging procedure reliably reduced the influence of head motion on estimates of gray matter thickness across the cortical surface. Moreover, T1w images from flagged participants exhibited reduced estimates of gray matter thickness and volume in comparison to age‐ and gender‐matched samples, resulting in inflated effect sizes in the relationships between regional anatomical measures and age. Gray matter thickness differences were noted in numerous regions previously reported to undergo prominent atrophy with age. Recommendations are provided for mitigating this potential confound, and highlight how the procedure may lead to more accurate measurement and comparison of anatomical features. Hum Brain Mapp 38:472–492, 2017. © 2016 Wiley Periodicals, Inc.

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“…The study was approved by the Hammersmith and Queen Charlotte's and Chelsea Research ethics committee. For the structural connectivity analysis, the first ten subjects from the Human Connectome Project [Van Essen et al, 2013] were included (5 male, age range 22–35). The preprocessed version of the data was used [Glasser et al, 2013].…”

Section: Methodsmentioning

confidence: 99%

Auditory and visual connectivity gradients in frontoparietal cortex

Braga

Hellyer

Wise

et al. 2016

Human Brain Mapping

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A frontoparietal network of brain regions is often implicated in both auditory and visual information processing. Although it is possible that the same set of multimodal regions subserves both modalities, there is increasing evidence that there is a differentiation of sensory function within frontoparietal cortex. Magnetic resonance imaging (MRI) in humans was used to investigate whether different frontoparietal regions showed intrinsic biases in connectivity with visual or auditory modalities. Structural connectivity was assessed with diffusion tractography and functional connectivity was tested using functional MRI. A dorsal–ventral gradient of function was observed, where connectivity with visual cortex dominates dorsal frontal and parietal connections, while connectivity with auditory cortex dominates ventral frontal and parietal regions. A gradient was also observed along the posterior–anterior axis, although in opposite directions in prefrontal and parietal cortices. The results suggest that the location of neural activity within frontoparietal cortex may be influenced by these intrinsic biases toward visual and auditory processing. Thus, the location of activity in frontoparietal cortex may be influenced as much by stimulus modality as the cognitive demands of a task. It was concluded that stimulus modality was spatially encoded throughout frontal and parietal cortices, and was speculated that such an arrangement allows for top–down modulation of modality‐specific information to occur within higher‐order cortex. This could provide a potentially faster and more efficient pathway by which top–down selection between sensory modalities could occur, by constraining modulations to within frontal and parietal regions, rather than long‐range connections to sensory cortices. Hum Brain Mapp 38:255–270, 2017. © 2016 Wiley Periodicals, Inc.

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The WU-Minn Human Connectome Project: An overview

Cited by 5,016 publications

References 61 publications

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

Auditory and visual connectivity gradients in frontoparietal cortex

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