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Evidence for embracing normative modeling
In this work, we expand the normative model repository introduced in Rutherford et al., 2022a to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036120/ https://www.ncbi.nlm.nih.gov/pubmed/36912775 http://dx.doi.org/10.7554/eLife.85082 |
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author | Rutherford, Saige Barkema, Pieter Tso, Ivy F Sripada, Chandra Beckmann, Christian F Ruhe, Henricus G Marquand, Andre F |
author_facet | Rutherford, Saige Barkema, Pieter Tso, Ivy F Sripada, Chandra Beckmann, Christian F Ruhe, Henricus G Marquand, Andre F |
author_sort | Rutherford, Saige |
collection | PubMed |
description | In this work, we expand the normative model repository introduced in Rutherford et al., 2022a to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability). Across all benchmarks, we show the advantage of using normative modeling features, with the strongest statistically significant results demonstrated in the group difference testing and classification tasks. We intend for these accessible resources to facilitate the wider adoption of normative modeling across the neuroimaging community. |
format | Online Article Text |
id | pubmed-10036120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-100361202023-03-24 Evidence for embracing normative modeling Rutherford, Saige Barkema, Pieter Tso, Ivy F Sripada, Chandra Beckmann, Christian F Ruhe, Henricus G Marquand, Andre F eLife Neuroscience In this work, we expand the normative model repository introduced in Rutherford et al., 2022a to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability). Across all benchmarks, we show the advantage of using normative modeling features, with the strongest statistically significant results demonstrated in the group difference testing and classification tasks. We intend for these accessible resources to facilitate the wider adoption of normative modeling across the neuroimaging community. eLife Sciences Publications, Ltd 2023-03-13 /pmc/articles/PMC10036120/ /pubmed/36912775 http://dx.doi.org/10.7554/eLife.85082 Text en © 2023, Rutherford et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Rutherford, Saige Barkema, Pieter Tso, Ivy F Sripada, Chandra Beckmann, Christian F Ruhe, Henricus G Marquand, Andre F Evidence for embracing normative modeling |
title | Evidence for embracing normative modeling |
title_full | Evidence for embracing normative modeling |
title_fullStr | Evidence for embracing normative modeling |
title_full_unstemmed | Evidence for embracing normative modeling |
title_short | Evidence for embracing normative modeling |
title_sort | evidence for embracing normative modeling |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036120/ https://www.ncbi.nlm.nih.gov/pubmed/36912775 http://dx.doi.org/10.7554/eLife.85082 |
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