Human Connectome Project informatics: Quality control, database services, and data visualization

Marcus, Daniel S.; Harms, Michael P.; Snyder, Abraham Z.; Jenkinson, Mark; Wilson, Joshua; Glasser, Matthew F.; Deanna, M; Archie, Kevin A.; Burgess, Gregory C.; Ramaratnam, Mohana; Hodge, Michael R.; Horton, William A.; Herrick, Rick; Olsen, Timothy R.; McKay, Michael T.; House, Matthew; Hileman, Michael; Reid, Erin; Harwell, John; Coalson, Timothy S.; Schindler, J. L.; Elam, Jennifer Stine; Curtiss, Sandra W.; Essen, David C. Van

doi:10.1016/j.neuroimage.2013.05.077

Cited by 374 publications

(292 citation statements)

References 29 publications

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“…Surface nodes, serving as positional coordinates along the cortical midthickness, then were used as seeds initiating for track lines, whose distribution throughout the cerebral hemisphere was of principal interest. All data were imported into the Connectome Workbench software (www.humanconnectome.org/software) for analysis and visualization (58). To evaluate the penetrance of gray matter seeding over the cortical surface, we computed the voxel VIC, corresponding to a normalized measure of track line distribution throughout the hemisphere from each position.…”

Section: Methodsmentioning

confidence: 99%

Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography

Reveley

Seth

Pierpaoli

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

391

387

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In vivo tractography based on diffusion magnetic resonance imaging (dMRI) has opened new doors to study structure-function relationships in the human brain. Initially developed to map the trajectory of major white matter tracts, dMRI is used increasingly to infer long-range anatomical connections of the cortex. Because axonal projections originate and terminate in the gray matter but travel mainly through the deep white matter, the success of tractography hinges on the capacity to follow fibers across this transition. Here we demonstrate that the complex arrangement of white matter fibers residing just under the cortical sheet poses severe challenges for long-range tractography over roughly half of the brain. We investigate this issue by comparing dMRI from very-high-resolution ex vivo macaque brain specimens with histological analysis of the same tissue. Using probabilistic tracking from pure gray and white matter seeds, we found that ∼50% of the cortical surface was effectively inaccessible for long-range diffusion tracking because of dense white matter zones just beneath the infragranular layers of the cortex. Analysis of the corresponding myelin-stained sections revealed that these zones colocalized with dense and uniform sheets of axons running mostly parallel to the cortical surface, most often in sulcal regions but also in many gyral crowns. Tracer injection into the sulcal cortex demonstrated that at least some axonal fibers pass directly through these fiber systems. Current and future high-resolution dMRI studies of the human brain will need to develop methods to overcome the challenges posed by superficial white matter systems to determine long-range anatomical connections accurately. diffusion MRI | tractography | neuroanatomy | white matter | connectome T he primate cerebral cortex consists of dozens of areas distinguished by their cytoarchitectonic profiles (1), sensory maps (2), functional specialization (3), and spontaneous activity covariation (4). Attention within neuroscience has increasingly focused on understanding how connectivity among these regions underpins brain function in health and in disease (5). The macaque monkey (Macaca mulatta) has been a fruitful neuroscientific model because the functional organization of its brain is similar in many ways to that of the human (6-8). Tracer injections in the macaque have revealed that virtually all cortical areas give rise to long-range connections, many of which project to other cortical areas, potentially to form processing hierarchies (9). This understanding continues to shape views of functional organization in the human brain. However, studying long-range connections through tracer injections is time consuming, inefficient, and prone to sampling biases, because a given experiment can measure connectivity to only one or a small number of cortical sites. Moreover, although in many respects the macaque brain is a good approximation of the human brain, both species have undergone profound evolutionary changes since the time of their most recent...

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Section: Methodsmentioning

confidence: 99%

Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography

Reveley

Seth

Pierpaoli

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

391

387

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“…Software used by this pipeline included FSL (FMRIB’s Software Library) (Jenkinson et al, 2012), FreeSurfer (Fischl, 2012), and the Connectome Workbench (Marcus et al, 2013). Specifically, the processing of structural MRI comprised the PreFreeSurfer (Jovicich et al, 2006; van der Kouwe et al, 2008), FreeSurfer recon-all (Dale et al, 1999; Fischl et al, 1999a,b, 2001, 2002; Ségonne et al, 2007) and PostFreeSurfer steps (Glasser et al, 2014), and the cortical and subcortical fMRI signals were processed separately in fMRISurface (Glasser et al, 2013) and fMRIVolume (Andersson et al, 2003; Greve and Fischl, 2009) pipelines.…”

Section: Methodsmentioning

confidence: 99%

Functional density and edge maps: Characterizing functional architecture in individuals and improving cross-subject registration

Tong

Aganj

et al. 2017

NeuroImage

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Population-level inferences and individual-level analyses are two important aspects in functional magnetic resonance imaging (fMRI) studies. Extracting reliable and informative features from fMRI data that capture biologically meaningful inter-subject variation is critical for aligning and comparing functional networks across subjects, and connecting the properties of functional brain organization with variations in behavior, cognition and genetics. In this study, we derive two new measures, which we term functional density map and edge map, and demonstrate their usefulness in characterizing the function of individual brains. Specifically, using data from the Human Connectome Project (HCP), we show that (1) both functional maps capture intrinsic properties of the functional connectivity pattern in individuals while exhibiting large variation across subjects; (2) functional maps derived from either resting-state or task-evoked fMRI can be used to accurately identify subjects from a population; and (3) cross-subject alignment using these functional maps considerably reduces functional variation and improves functional correspondence across subjects over state-of-the-art multimodal registration algorithms. Our results suggest that the proposed functional density and edge maps are promising features in characterizing the functional architecture in individuals and provide an alternative way to explore the functional variation across subjects.

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“…Cardiac and respiratory cycles can also modulate signal via several mechanisms. A fuller accounting of the various sources of artifact is beyond the scope of this review (see (Murphy et al, 2013)), but the magnitude of the problem is captured by the following statistic: in Human Connectome Project data, which are high-quality and undergo an advanced denoising procedure, of the roughly 200 signals identified per subject, only ~23 on average are considered to reflect neural activity, constituting ~4% of the variance (Marcus et al, 2013). …”

Section: Obtaining Correlates Of Spontaneous Neural Activity With Fmrimentioning

confidence: 99%

Studying Brain Organization via Spontaneous fMRI Signal

Power

Schlaggar

Petersen

2014

Neuron

234

199

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In recent years, some substantial advances in understanding human (and non-human) brain organization have emerged from a relatively unusual approach: the observation of spontaneous activity, and correlated patterns in spontaneous activity, in the “resting” brain. Most commonly, spontaneous neural activity is measured indirectly via fMRI signal in subjects who are lying quietly in the scanner, the so-called “resting state”. This Primer introduces the fMRI-based study of spontaneous brain activity, some of the methodological issues active in the field, and some ways in which resting state fMRI has been used to delineate aspects of area-level and supra-areal brain organization.

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Human Connectome Project informatics: Quality control, database services, and data visualization

Cited by 374 publications

References 29 publications

Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography

Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractography

Functional density and edge maps: Characterizing functional architecture in individuals and improving cross-subject registration

Studying Brain Organization via Spontaneous fMRI Signal

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