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Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder
This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 1...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027814/ https://www.ncbi.nlm.nih.gov/pubmed/31637863 http://dx.doi.org/10.1002/aur.2218 |
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author | Raatikainen, Ville Korhonen, Vesa Borchardt, Viola Huotari, Niko Helakari, Heta Kananen, Janne Raitamaa, Lauri Joskitt, Leena Loukusa, Soile Hurtig, Tuula Ebeling, Hanna Uddin, Lucina Q. Kiviniemi, Vesa |
author_facet | Raatikainen, Ville Korhonen, Vesa Borchardt, Viola Huotari, Niko Helakari, Heta Kananen, Janne Raitamaa, Lauri Joskitt, Leena Loukusa, Soile Hurtig, Tuula Ebeling, Hanna Uddin, Lucina Q. Kiviniemi, Vesa |
author_sort | Raatikainen, Ville |
collection | PubMed |
description | This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default‐mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large‐scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244–258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra‐fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default‐mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder. |
format | Online Article Text |
id | pubmed-7027814 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-70278142020-02-24 Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder Raatikainen, Ville Korhonen, Vesa Borchardt, Viola Huotari, Niko Helakari, Heta Kananen, Janne Raitamaa, Lauri Joskitt, Leena Loukusa, Soile Hurtig, Tuula Ebeling, Hanna Uddin, Lucina Q. Kiviniemi, Vesa Autism Res Research Articles This study investigated whole‐brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting‐state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P‐value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default‐mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large‐scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244–258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra‐fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default‐mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder. John Wiley & Sons, Inc. 2019-10-22 2020-02 /pmc/articles/PMC7027814/ /pubmed/31637863 http://dx.doi.org/10.1002/aur.2218 Text en © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles Raatikainen, Ville Korhonen, Vesa Borchardt, Viola Huotari, Niko Helakari, Heta Kananen, Janne Raitamaa, Lauri Joskitt, Leena Loukusa, Soile Hurtig, Tuula Ebeling, Hanna Uddin, Lucina Q. Kiviniemi, Vesa Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder |
title | Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder |
title_full | Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder |
title_fullStr | Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder |
title_full_unstemmed | Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder |
title_short | Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder |
title_sort | dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027814/ https://www.ncbi.nlm.nih.gov/pubmed/31637863 http://dx.doi.org/10.1002/aur.2218 |
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