Literature DB >> 25666423

Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment.

Carinna M Torgerson1, Catherine Quinn, Ivo Dinov, Zhizhong Liu, Petros Petrosyan, Kevin Pelphrey, Christian Haselgrove, David N Kennedy, Arthur W Toga, John Darrell Van Horn.   

Abstract

Under the umbrella of the National Database for Clinical Trials (NDCT) related to mental illnesses, the National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline workflow design and execution environment to enable large-scale analyses of cortical architecture and function via local, cluster, or "cloud"-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources. We discuss the utility of such database and workflow processing interactivity as a motivation for the sharing of additional primary data in ASD research and elsewhere.

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Year:  2015        PMID: 25666423      PMCID: PMC4447326          DOI: 10.1007/s11682-015-9354-z

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


  42 in total

1.  The evaluation of preprocessing choices in single-subject BOLD fMRI using NPAIRS performance metrics.

Authors:  Stephen LaConte; Jon Anderson; Suraj Muley; James Ashe; Sally Frutiger; Kelly Rehm; Lars Kai Hansen; Essa Yacoub; Xiaoping Hu; David Rottenberg; Stephen Strother
Journal:  Neuroimage       Date:  2003-01       Impact factor: 6.556

Review 2.  Sharing heterogeneous data: the national database for autism research.

Authors:  Dan Hall; Michael F Huerta; Matthew J McAuliffe; Gregory K Farber
Journal:  Neuroinformatics       Date:  2012-10

3.  Construction of a 3D probabilistic atlas of human cortical structures.

Authors:  David W Shattuck; Mubeena Mirza; Vitria Adisetiyo; Cornelius Hojatkashani; Georges Salamon; Katherine L Narr; Russell A Poldrack; Robert M Bilder; Arthur W Toga
Journal:  Neuroimage       Date:  2007-11-26       Impact factor: 6.556

4.  Automated extraction of the cortical sulci based on a supervised learning approach.

Authors:  Zhuowen Tu; Songfeng Zheng; Alan L Yuille; Allan L Reiss; Rebecca A Dutton; Agatha D Lee; Albert M Galaburda; Ivo Dinov; Paul M Thompson; Arthur W Toga
Journal:  IEEE Trans Med Imaging       Date:  2007-04       Impact factor: 10.048

5.  Provenance in neuroimaging.

Authors:  Allan J Mackenzie-Graham; John D Van Horn; Roger P Woods; Karen L Crawford; Arthur W Toga
Journal:  Neuroimage       Date:  2008-04-25       Impact factor: 6.556

6.  Changes in the sulcal size associated with autism spectrum disorder revealed by sulcal morphometry.

Authors:  Mahsa Shokouhi; Justin H G Williams; Gordon D Waiter; Barrie Condon
Journal:  Autism Res       Date:  2012-06-01       Impact factor: 5.216

7.  Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

Authors:  Krzysztof Gorgolewski; Christopher D Burns; Cindee Madison; Dav Clark; Yaroslav O Halchenko; Michael L Waskom; Satrajit S Ghosh
Journal:  Front Neuroinform       Date:  2011-08-22       Impact factor: 4.081

8.  A meta-algorithm for brain extraction in MRI.

Authors:  David E Rex; David W Shattuck; Roger P Woods; Katherine L Narr; Eileen Luders; Kelly Rehm; Sarah E Stoltzner; Sarah E Stolzner; David A Rottenberg; Arthur W Toga
Journal:  Neuroimage       Date:  2004-10       Impact factor: 6.556

9.  The effect of diagnosis, age, and symptom severity on cortical surface area in the cingulate cortex and insula in autism spectrum disorders.

Authors:  Krissy A R Doyle-Thomas; Azadeh Kushki; Emma G Duerden; Margot J Taylor; Jason P Lerch; Latha V Soorya; A Ting Wang; Jin Fan; Evdokia Anagnostou
Journal:  J Child Neurol       Date:  2012-07-25       Impact factor: 1.987

10.  Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline.

Authors:  Ivo Dinov; Kamen Lozev; Petros Petrosyan; Zhizhong Liu; Paul Eggert; Jonathan Pierce; Alen Zamanyan; Shruthi Chakrapani; John Van Horn; D Stott Parker; Rico Magsipoc; Kelvin Leung; Boris Gutman; Roger Woods; Arthur Toga
Journal:  PLoS One       Date:  2010-09-28       Impact factor: 3.240

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  4 in total

Review 1.  Can data repositories help find effective treatments for complex diseases?

Authors:  Gregory K Farber
Journal:  Prog Neurobiol       Date:  2016-03-24       Impact factor: 11.685

2.  National Database for Autism Research (NDAR): Big Data Opportunities for Health Services Research and Health Technology Assessment.

Authors:  Nalin Payakachat; J Mick Tilford; Wendy J Ungar
Journal:  Pharmacoeconomics       Date:  2016-02       Impact factor: 4.981

Review 3.  Big data sharing and analysis to advance research in post-traumatic epilepsy.

Authors:  Dominique Duncan; Paul Vespa; Asla Pitkänen; Adebayo Braimah; Niina Lapinlampi; Arthur W Toga
Journal:  Neurobiol Dis       Date:  2018-06-01       Impact factor: 5.996

4.  Improving functional magnetic resonance imaging reproducibility.

Authors:  Cyril Pernet; Jean-Baptiste Poline
Journal:  Gigascience       Date:  2015-03-31       Impact factor: 6.524

  4 in total

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