Literature DB >> 24113873

Human neuroimaging as a "Big Data" science.

John Darrell Van Horn1, Arthur W Toga.   

Abstract

The maturation of in vivo neuroimaging has led to incredible quantities of digital information about the human brain. While much is made of the data deluge in science, neuroimaging represents the leading edge of this onslaught of "big data". A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Yet few, if any, common solutions exist to support the science of neuroimaging. In this article, we discuss how modern neuroimaging research represents a multifactorial and broad ranging data challenge, involving the growing size of the data being acquired; sociological and logistical sharing issues; infrastructural challenges for multi-site, multi-datatype archiving; and the means by which to explore and mine these data. As neuroimaging advances further, e.g. aging, genetics, and age-related disease, new vision is needed to manage and process this information while marshalling of these resources into novel results. Thus, "big data" can become "big" brain science.

Entities:  

Mesh:

Year:  2014        PMID: 24113873      PMCID: PMC3983169          DOI: 10.1007/s11682-013-9255-y

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  61 in total

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4.  Is it time to re-prioritize neuroimaging databases and digital repositories?

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7.  The NIH MRI study of normal brain development (Objective-2): newborns, infants, toddlers, and preschoolers.

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9.  Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging.

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10.  Visual systems for interactive exploration and mining of large-scale neuroimaging data archives.

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Journal:  Front Neuroinform       Date:  2012-04-23       Impact factor: 4.081

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  54 in total

1.  Big biomedical data as the key resource for discovery science.

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Journal:  J Am Med Inform Assoc       Date:  2015-07-21       Impact factor: 4.497

Review 2.  Big data in medical science--a biostatistical view.

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Journal:  Dtsch Arztebl Int       Date:  2015-02-27       Impact factor: 5.594

3.  MRI quality control for the Italian Neuroimaging Network Initiative: moving towards big data in multiple sclerosis.

Authors:  Loredana Storelli; Maria A Rocca; Patrizia Pantano; Elisabetta Pagani; Nicola De Stefano; Gioacchino Tedeschi; Paola Zaratin; Massimo Filippi
Journal:  J Neurol       Date:  2019-08-17       Impact factor: 4.849

4.  Cellular Automata Tractography: Fast Geodesic Diffusion MR Tractography and Connectivity Based Segmentation on the GPU.

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Journal:  Neuroinformatics       Date:  2020-01

Review 5.  Is advanced neuroimaging for neuroradiologists? A systematic review of the scientific literature of the last decade.

Authors:  Sirio Cocozza; Camilla Russo; Giuseppe Pontillo; Lorenzo Ugga; Antonio Macera; Amedeo Cervo; Maria De Liso; Nilde Di Paolo; Maria Isabella Ginocchio; Flavio Giordano; Giuseppe Leone; Giovanni Rusconi; Arnaldo Stanzione; Francesco Briganti; Mario Quarantelli; Ferdinando Caranci; Alessandra D'Amico; Andrea Elefante; Enrico Tedeschi; Arturo Brunetti
Journal:  Neuroradiology       Date:  2016-11-08       Impact factor: 2.804

6.  Neuroimaging Research: From Null-Hypothesis Falsification to Out-of-Sample Generalization.

Authors:  Danilo Bzdok; Gaël Varoquaux; Bertrand Thirion
Journal:  Educ Psychol Meas       Date:  2016-10-06       Impact factor: 2.821

7.  Big data and biomedical informatics: a challenging opportunity.

Authors:  R Bellazzi
Journal:  Yearb Med Inform       Date:  2014-05-22

8.  Democratizing data science through data science training.

Authors:  John Darrell Van Horn; Lily Fierro; Jeana Kamdar; Jonathan Gordon; Crystal Stewart; Avnish Bhattrai; Sumiko Abe; Xiaoxiao Lei; Caroline O'Driscoll; Aakanchha Sinha; Priyambada Jain; Gully Burns; Kristina Lerman; José Luis Ambite
Journal:  Pac Symp Biocomput       Date:  2018

9.  Virtual Connectomic Datasets in Alzheimer's Disease and Aging Using Whole-Brain Network Dynamics Modelling.

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Journal:  eNeuro       Date:  2021-07-06

Review 10.  Functional brain imaging in neuropsychology over the past 25 years.

Authors:  David R Roalf; Ruben C Gur
Journal:  Neuropsychology       Date:  2017-11       Impact factor: 3.295

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