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The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions
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 a...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5466711/ https://www.ncbi.nlm.nih.gov/pubmed/28369458 http://dx.doi.org/10.1093/gigascience/giw011 |
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author | O’Connor, David Potler, Natan Vega Kovacs, Meagan Xu, Ting Ai, Lei Pellman, John Vanderwal, Tamara Parra, Lucas C. Cohen, Samantha Ghosh, Satrajit Escalera, Jasmine Grant-Villegas, Natalie Osman, Yael Bui, Anastasia Craddock, R. Cameron Milham, Michael P. |
author_facet | O’Connor, David Potler, Natan Vega Kovacs, Meagan Xu, Ting Ai, Lei Pellman, John Vanderwal, Tamara Parra, Lucas C. Cohen, Samantha Ghosh, Satrajit Escalera, Jasmine Grant-Villegas, Natalie Osman, Yael Bui, Anastasia Craddock, R. Cameron Milham, Michael P. |
author_sort | O’Connor, David |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5466711 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54667112017-06-19 The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions O’Connor, David Potler, Natan Vega Kovacs, Meagan Xu, Ting Ai, Lei Pellman, John Vanderwal, Tamara Parra, Lucas C. Cohen, Samantha Ghosh, Satrajit Escalera, Jasmine Grant-Villegas, Natalie Osman, Yael Bui, Anastasia Craddock, R. Cameron Milham, Michael P. Gigascience Data Note 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. Oxford University Press 2017-01-07 /pmc/articles/PMC5466711/ /pubmed/28369458 http://dx.doi.org/10.1093/gigascience/giw011 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Data Note O’Connor, David Potler, Natan Vega Kovacs, Meagan Xu, Ting Ai, Lei Pellman, John Vanderwal, Tamara Parra, Lucas C. Cohen, Samantha Ghosh, Satrajit Escalera, Jasmine Grant-Villegas, Natalie Osman, Yael Bui, Anastasia Craddock, R. Cameron Milham, Michael P. The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions |
title | The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions |
title_full | The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions |
title_fullStr | The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions |
title_full_unstemmed | The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions |
title_short | The Healthy Brain Network Serial Scanning Initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions |
title_sort | healthy brain network serial scanning initiative: a resource for evaluating inter-individual differences and their reliabilities across scan conditions and sessions |
topic | Data Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5466711/ https://www.ncbi.nlm.nih.gov/pubmed/28369458 http://dx.doi.org/10.1093/gigascience/giw011 |
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