The Brain Analysis Library of Spatial maps and Atlases (BALSA) database

Essen, David C. Van; Smith, J. Torquil; Glasser, Matthew F.; Elam, Jennifer Stine; Donahue, Chad J.; Dierker, Donna L.; Reid, Erin; Coalson, Timothy S.; Harwell, John

doi:10.1016/j.neuroimage.2016.04.002

Cited by 88 publications

(65 citation statements)

References 16 publications

(16 reference statements)

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“…Importantly, Workbench allows such complex displays to be saved as “scenes” that can be quickly re-opened, edited, re-saved, and exported as publication-ready images. Data from such figures can be shared by uploading the scene file to the BALSA database (http://balsa.wustl.edu; 10 directly from Workbench, together with basic information about the publication. Scene-specific URLs enable one-click linking from a published figure to the corresponding page in BALSA (see Figure legends).…”

Section: Tenet 7: Routine Data Sharing and Advanced Informatics For Dmentioning

confidence: 99%

“…The seven tenets of the HCP-style paradigm span the domains of acquisition, analysis, and sharing of MRI-based data: (1) acquiring large amounts of high quality, multi-modal data on as many subjects as feasible to measure architectural, functional, connectional, and topographical information 4 (2) acquiring this MRI data with high spatial, temporal, and angular resolution for structural, functional, and diffusion MRI using cutting-edge accelerated acquisition protocols 5 ;(3) minimizing blurring introduced by preprocessing and removing distortions, noise, and temporal artifacts as selectively and completely as possible 6,7 ; (4) representing cortical data (surface vertices) and subcortical data (volume voxels) in a common geometrical framework (“CIFTI grayordinates”) that is optimal for each 6 ; (5) accurately aligning corresponding brain areas across subjects and studies using “areal features” related to connectivity and architecture 8,9 ; (6) using structurally and functionally relevant brain parcellations (preferably based on multiple modalities) to provide a strong neuroanatomical framework for condensing complex neuroimaging data and enhancing statistical sensitivity and power without blurring across areal boundaries 8 ; and (7) routine sharing of extensively analyzed results such as statistical maps 10 (plus raw and preprocessed data when feasible 11 ) together with the code used for the analysis, so that other neuroscientists can make precise comparisons across studies, along with replicating and extending findings.…”

Section: Introductionmentioning

confidence: 99%

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The Human Connectome Project's neuroimaging approach

et al. 2016

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Non-invasive human neuroimaging has yielded many exciting discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis, and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The “HCP-style” paradigm has seven core tenets: (1) collect multimodal imaging data from many subjects; (2) acquire data at high spatial and temporal resolution; (3) preprocess data to minimize distortions, blurring, and temporal artifacts; (4) represent data using the natural geometry of cortical and subcortical structures; (5) accurately align corresponding brain areas across subjects and studies; (6) analyze data using neurobiologically accurate brain parcellations; and (7) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP datasets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease.

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Section: Tenet 7: Routine Data Sharing and Advanced Informatics For Dmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Human Connectome Project's neuroimaging approach

et al. 2016

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“…Regions outside these domains are labelled as 'none'. The atlas was downloaded from the Brain Analysis Library of Spatial Maps and Atlases database (https://balsa.wustl.edu; Van Essen et al, 2017). Whole-brain coverage consisted of 333 cortical regions (161 and 162 regions from left and right hemispheres respectively), and one subcortical volume corresponding to the thalamus.…”

Section: Brain Parcellationmentioning

confidence: 99%

Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms

Alderson

Bokde

Kelso

et al. 2019

Preprint

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AbstractDespite resting state networks being associated with a variety of cognitive abilities, it remains unclear how these local areas act in concert to express particular cognitive operations. Theoretical and empirical accounts indicate that large-scale resting state networks reconcile dual tendencies toward integration and segregation by operating in a metastable regime of their coordination dynamics. One proposal is that metastability confers important behavioural qualities by dynamically binding distributed local areas into large-scale neurocognitive entities. We tested this hypothesis by analysing fMRI data in a large cohort of healthy individuals (N=566) and comparing the metastability of the brain’s large-scale resting network architecture at rest and during the performance of several tasks. Task-based reasoning was principally characterised by high metastability in cognitive control networks and low metastability in sensory processing areas. Although metastability between resting state networks increased during task performance, cognitive ability was more closely linked to spontaneous activity. High metastability in the intrinsic connectivity of cognitive control networks was linked to novel problem solving (or fluid intelligence) but was less important in tasks relying on prior experience (or crystallised intelligence). Crucially, subjects with resting architectures similar or ‘pre-configured’ to a task-general arrangement demonstrated superior cognitive performance. Taken together, our findings support a critical linkage between the spontaneous metastability of the large-scale networks of the cerebral cortex and cognition.

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“…We make freely available these pRF results, as well as associated stimuli and 25 analysis code, at an Open Science Framework web site (https://osf.io/bw9ec/). The pRF results are also 26 accessible via the BALSA database (http://balsa.wustl.edu; Van Essen et al, 2017), downloadable as 27 'scene files' that can be visualized using Connectome Workbench software (see Supplementary 28 Information). The neuroscience community at large can now exploit these resources for a variety of 29 purposes, such as developing normative models, mapping new brain areas, analyzing connectomics, 30 characterizing individual differences, and comparing with other suitably aligned datasets (either published 31 or ongoing).…”

mentioning

confidence: 99%

The HCP 7T Retinotopy Dataset: Description and pRF Analysis

Benson

Arcaro

et al. 2018

Preprint

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About a quarter of human cerebral cortex is tiled with maps of the visual field. These maps can be 3 measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated 4 visual stimuli, also known as 'retinotopic mapping'. One of the datasets collected by the Human 5Connectome Project (HCP) involved ultra-high-field (7 Tesla) fMRI retinotopic mapping in 181 healthy 6 adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we 7 describe the experimental paradigm and the results of model-based analysis of the fMRI data. These 8 results provide estimates of population receptive field position and size. Our analyses include both results 9 from individual subjects as well as results obtained by averaging fMRI time-series across subjects at each 10 cortical and subcortical location and then fitting models. Both the group-average and individual-subject 11 results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal 12 cortex as well as subcortical areas. The group-average results agree well with previously published 13 parcellations of visual areas. In addition, split-half analyses demonstrate strong within-subject reliability, 14 further evidencing the high quality of the data. We make publicly available the analysis results for 15 individual subjects and the group average, as well as associated stimuli and analysis code. These 16 resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical 17 organization and the properties of high-resolution fMRI. In addition, they provide a measure that can be 18 combined with other HCP measures acquired in these same participants. This enables comparisons 19 across groups, health, and age, and comparison of organization derived from a retinotopic task against 20 that derived from other measurements such as diffusion imaging and resting-state functional connectivity. 21 22. CC-BY 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/308247 doi: bioRxiv preprint first posted online Apr. 25, 2018; 3 Introduction 1 2The central nervous system maps sensory inputs onto topographically organized representations. In the 3 field of vision, researchers have successfully exploited functional magnetic resonance imaging (fMRI) to 4 noninvasively measure visual field representations ('retinotopy') in the living human brain (Engel et al., 5 1994;Sereno et al., 1995; DeYoe et al., 1996; Engel et al., 1997). These efforts enable parcellation of 6 visual cortex into distinct maps of the visual field, thereby laying the foundation for detailed investigations 7 of the properties of visual cortex (parcellation references: Abdollahi et al., 2014;Benson et al., 2014; 8 Wang et al., 2015; review references: Tootell et al., 1996;Wandell et...

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The Brain Analysis Library of Spatial maps and Atlases (BALSA) database

Cited by 88 publications

References 16 publications

The Human Connectome Project's neuroimaging approach

The Human Connectome Project's neuroimaging approach

Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms

The HCP 7T Retinotopy Dataset: Description and pRF Analysis

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