The minimal preprocessing pipelines for the Human Connectome Project

Glasser, Matthew F.; Sotiropoulos, Stamatios N.; Wilson, Joshua; Coalson, Timothy S.; Fischl, Bruce; Andersson, Jesper; Xu, Junqian; Jbabdi, Saâd; Webster, Matthew; Polimeni, Jon̈athan R.; Essen, David C. Van; Jenkinson, Mark

doi:10.1016/j.neuroimage.2013.04.127

Cited by 4,275 publications

(4,165 citation statements)

References 62 publications

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“…The image data were preprocessed using HCP's Minimal Preprocessing Pipeline 42, 43. This pipeline starts with intensity normalization across the diffusion scan based on the zero b ‐value images.…”

Section: Methodsmentioning

confidence: 99%

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Kaden

Kruggel

Alexander

2015

Magnetic Resonance in Med

194

284

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PurposeThis article presents a simple method for estimating the effective diffusion coefficients parallel and perpendicular to the axons unconfounded by the intravoxel fiber orientation distribution. We also call these parameters the per‐axon or microscopic diffusion coefficients.Theory and MethodsDiffusion MR imaging is used to probe the underlying tissue material. The key observation is that for a fixed b‐value the spherical mean of the diffusion signal over the gradient directions does not depend on the axon orientation distribution. By exploiting this invariance property, we propose a simple, fast, and robust estimator of the per‐axon diffusion coefficients, which we refer to as the spherical mean technique.ResultsWe demonstrate quantitative maps of the axon‐scale diffusion process, which has factored out the effects due to fiber dispersion and crossing, in human brain white matter. These microscopic diffusion coefficients are estimated in vivo using a widely available off‐the‐shelf pulse sequence featuring multiple b‐shells and high‐angular gradient resolution.ConclusionThe estimation of the per‐axon diffusion coefficients is essential for the accurate recovery of the fiber orientation distribution. In addition, the spherical mean technique enables us to discriminate microscopic tissue features from fiber dispersion, which potentially improves the sensitivity and/or specificity to various neurological conditions. Magn Reson Med, 2015. Magn Reson Med 75:1752–1763, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc.

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Section: Methodsmentioning

confidence: 99%

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Kaden

Kruggel

Alexander

2015

Magnetic Resonance in Med

194

284

View full text Add to dashboard Cite

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“…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]. The number of subjects used in the diffusion data was limited to 10 due to the large computational load of the unconstrained probabilistic tractography analysis.…”

Section: Methodsmentioning

confidence: 99%

“…Preprocessed versions of the data from the Human Connectome Project [Glasser et al, 2013] were used. In brief, EPI distortion was corrected within raw dMRI data, using TOPUP followed by eddy correction using EDDY from the FMRIB software library [Smith et al, 2009].…”

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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“…Gradient nonlinearity results in geometric distortion of the images and is the same for all imaging sequences. Since nonlinearity is part of the gradient system design, it does not vary with the patient and, given detailed information about the gradient design, can be corrected on the scanner or offline 94 .…”

Section: Field Inhomogeneitiesmentioning

confidence: 99%

Studying neuroanatomy using MRI

et al. 2017

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The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro-and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works.

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The minimal preprocessing pipelines for the Human Connectome Project

Cited by 4,275 publications

References 62 publications

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Auditory and visual connectivity gradients in frontoparietal cortex

Studying neuroanatomy using MRI

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