Literature DB >> 28369458

The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions.

David O'Connor1,2, Natan Vega Potler1, Meagan Kovacs1, Ting Xu1, Lei Ai1, John Pellman1,2, Tamara Vanderwal3, Lucas C Parra4, Samantha Cohen5, Satrajit Ghosh6, Jasmine Escalera1, Natalie Grant-Villegas1, Yael Osman1, Anastasia Bui1, R Cameron Craddock1,2, Michael P Milham1,2.   

Abstract

Background: Although typically measured during the resting state, a growing literature is illustrating the ability to map intrinsic connectivity with functional MRI during task and naturalistic viewing conditions. These paradigms are drawing excitement due to their greater tolerability in clinical and developing populations and because they enable a wider range of analyses (e.g., inter-subject correlations). To be clinically useful, the test-retest reliability of connectivity measured during these paradigms needs to be established. This resource provides data for evaluating test-retest reliability for full-brain connectivity patterns detected during each of four scan conditions that differ with respect to level of engagement (rest, abstract animations, movie clips, flanker task). Data are provided for 13 participants, each scanned in 12 sessions with 10 minutes for each scan of the four conditions. Diffusion kurtosis imaging data was also obtained at each session. Findings: Technical validation and demonstrative reliability analyses were carried out at the connection-level using the Intraclass Correlation Coefficient and at network-level representations of the data using the Image Intraclass Correlation Coefficient. Variation in intrinsic functional connectivity across sessions was generally found to be greater than that attributable to scan condition. Between-condition reliability was generally high, particularly for the frontoparietal and default networks. Between-session reliabilities obtained separately for the different scan conditions were comparable, though notably lower than between-condition reliabilities. Conclusions: This resource provides a test-bed for quantifying the reliability of connectivity indices across subjects, conditions and time. The resource can be used to compare and optimize different frameworks for measuring connectivity and data collection parameters such as scan length. Additionally, investigators can explore the unique perspectives of the brain's functional architecture offered by each of the scan conditions.
© The Author 2017. Published by Oxford University Press.

Entities:  

Keywords:  Data sharing; Reliability; fMRI

Mesh:

Year:  2017        PMID: 28369458      PMCID: PMC5466711          DOI: 10.1093/gigascience/giw011

Source DB:  PubMed          Journal:  Gigascience        ISSN: 2047-217X            Impact factor:   6.524


  59 in total

Review 1.  Brain graphs: graphical models of the human brain connectome.

Authors:  Edward T Bullmore; Danielle S Bassett
Journal:  Annu Rev Clin Psychol       Date:  2011       Impact factor: 18.561

2.  A method for using blocked and event-related fMRI data to study "resting state" functional connectivity.

Authors:  Damien A Fair; Bradley L Schlaggar; Alexander L Cohen; Francis M Miezin; Nico U F Dosenbach; Kristin K Wenger; Michael D Fox; Abraham Z Snyder; Marcus E Raichle; Steven E Petersen
Journal:  Neuroimage       Date:  2007-01-18       Impact factor: 6.556

Review 3.  Advances in functional and structural MR image analysis and implementation as FSL.

Authors:  Stephen M Smith; Mark Jenkinson; Mark W Woolrich; Christian F Beckmann; Timothy E J Behrens; Heidi Johansen-Berg; Peter R Bannister; Marilena De Luca; Ivana Drobnjak; David E Flitney; Rami K Niazy; James Saunders; John Vickers; Yongyue Zhang; Nicola De Stefano; J Michael Brady; Paul M Matthews
Journal:  Neuroimage       Date:  2004       Impact factor: 6.556

4.  A technique for the deidentification of structural brain MR images.

Authors:  Amanda Bischoff-Grethe; I Burak Ozyurt; Evelina Busa; Brian T Quinn; Christine Fennema-Notestine; Camellia P Clark; Shaunna Morris; Mark W Bondi; Terry L Jernigan; Anders M Dale; Gregory G Brown; Bruce Fischl
Journal:  Hum Brain Mapp       Date:  2007-09       Impact factor: 5.038

5.  Correcting brain-wide correlation differences in resting-state FMRI.

Authors:  Ziad S Saad; Richard C Reynolds; Hang Joon Jo; Stephen J Gotts; Gang Chen; Alex Martin; Robert W Cox
Journal:  Brain Connect       Date:  2013-07-31

Review 6.  Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective.

Authors:  Xi-Nian Zuo; Xiu-Xia Xing
Journal:  Neurosci Biobehav Rev       Date:  2014-05-27       Impact factor: 8.989

7.  Gleaning multicomponent T1 and T2 information from steady-state imaging data.

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8.  Automatic quality assessment in structural brain magnetic resonance imaging.

Authors:  Bénédicte Mortamet; Matt A Bernstein; Clifford R Jack; Jeffrey L Gunter; Chadwick Ward; Paula J Britson; Reto Meuli; Jean-Philippe Thiran; Gunnar Krueger
Journal:  Magn Reson Med       Date:  2009-08       Impact factor: 4.668

Review 9.  Imaging human connectomes at the macroscale.

Authors:  R Cameron Craddock; Saad Jbabdi; Chao-Gan Yan; Joshua T Vogelstein; F Xavier Castellanos; Adriana Di Martino; Clare Kelly; Keith Heberlein; Stan Colcombe; Michael P Milham
Journal:  Nat Methods       Date:  2013-06       Impact factor: 28.547

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Journal:  PLoS One       Date:  2014-05-30       Impact factor: 3.240

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  31 in total

1.  The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions.

Authors:  David O'Connor; Natan Vega Potler; Meagan Kovacs; Ting Xu; Lei Ai; John Pellman; Tamara Vanderwal; Lucas C Parra; Samantha Cohen; Satrajit Ghosh; Jasmine Escalera; Natalie Grant-Villegas; Yael Osman; Anastasia Bui; R Cameron Craddock; Michael P Milham
Journal:  Gigascience       Date:  2017-02-01       Impact factor: 6.524

2.  Test-retest reliability of functional connectivity networks during naturalistic fMRI paradigms.

Authors:  Jiahui Wang; Yudan Ren; Xintao Hu; Vinh Thai Nguyen; Lei Guo; Junwei Han; Christine Cong Guo
Journal:  Hum Brain Mapp       Date:  2017-01-17       Impact factor: 5.038

Review 3.  Nature abhors a paywall: How open science can realize the potential of naturalistic stimuli.

Authors:  Elizabeth DuPre; Michael Hanke; Jean-Baptiste Poline
Journal:  Neuroimage       Date:  2019-11-05       Impact factor: 6.556

4.  Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms.

Authors:  Hengyi Cao; Sarah C McEwen; Jennifer K Forsyth; Dylan G Gee; Carrie E Bearden; Jean Addington; Bradley Goodyear; Kristin S Cadenhead; Heline Mirzakhanian; Barbara A Cornblatt; Ricardo E Carrión; Daniel H Mathalon; Thomas H McGlashan; Diana O Perkins; Aysenil Belger; Larry J Seidman; Heidi Thermenos; Ming T Tsuang; Theo G M van Erp; Elaine F Walker; Stephan Hamann; Alan Anticevic; Scott W Woods; Tyrone D Cannon
Journal:  Cereb Cortex       Date:  2019-03-01       Impact factor: 5.357

Review 5.  Defining Individual-Specific Functional Neuroanatomy for Precision Psychiatry.

Authors:  Caterina Gratton; Brian T Kraus; Deanna J Greene; Evan M Gordon; Timothy O Laumann; Steven M Nelson; Nico U F Dosenbach; Steven E Petersen
Journal:  Biol Psychiatry       Date:  2019-11-07       Impact factor: 13.382

6.  Functional connectivity of the anterior insula associated with intolerance of uncertainty in youth.

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7.  Bagging improves reproducibility of functional parcellation of the human brain.

Authors:  Aki Nikolaidis; Anibal Solon Heinsfeld; Ting Xu; Pierre Bellec; Joshua Vogelstein; Michael Milham
Journal:  Neuroimage       Date:  2020-02-29       Impact factor: 6.556

8.  The open EEGLAB portal Interface: High-Performance computing with EEGLAB.

Authors:  Ramón Martínez-Cancino; Arnaud Delorme; Dung Truong; Fiorenzo Artoni; Kenneth Kreutz-Delgado; Subhashini Sivagnanam; Kenneth Yoshimoto; Amitava Majumdar; Scott Makeig
Journal:  Neuroimage       Date:  2020-04-11       Impact factor: 6.556

9.  Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior.

Authors:  Ru Kong; Qing Yang; Evan Gordon; Aihuiping Xue; Xiaoxuan Yan; Csaba Orban; Xi-Nian Zuo; Nathan Spreng; Tian Ge; Avram Holmes; Simon Eickhoff; B T Thomas Yeo
Journal:  Cereb Cortex       Date:  2021-08-26       Impact factor: 5.357

10.  Delineating the Macroscale Areal Organization of the Macaque Cortex In Vivo.

Authors:  Ting Xu; Arnaud Falchier; Elinor L Sullivan; Gary Linn; Julian S B Ramirez; Deborah Ross; Eric Feczko; Alexander Opitz; Jennifer Bagley; Darrick Sturgeon; Eric Earl; Oscar Miranda-Domínguez; Anders Perrone; R Cameron Craddock; Charles E Schroeder; Stan Colcombe; Damien A Fair; Michael P Milham
Journal:  Cell Rep       Date:  2018-04-10       Impact factor: 9.423

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