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Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study

The resting‐state human brain is a dynamic system that shows frequency‐dependent characteristics. Recent studies demonstrate that coactivation pattern (CAP) analysis can identify recurring brain states with similar coactivation configurations. However, it is unclear whether and how CAPs depend on th...

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Autores principales: Yang, Hang, Zhang, Hong, Meng, Chun, Wohlschläger, Afra, Brandl, Felix, Di, Xin, Wang, Shuai, Tian, Lin, Biswal, Bharat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294298/
https://www.ncbi.nlm.nih.gov/pubmed/35475569
http://dx.doi.org/10.1002/hbm.25884
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author Yang, Hang
Zhang, Hong
Meng, Chun
Wohlschläger, Afra
Brandl, Felix
Di, Xin
Wang, Shuai
Tian, Lin
Biswal, Bharat
author_facet Yang, Hang
Zhang, Hong
Meng, Chun
Wohlschläger, Afra
Brandl, Felix
Di, Xin
Wang, Shuai
Tian, Lin
Biswal, Bharat
author_sort Yang, Hang
collection PubMed
description The resting‐state human brain is a dynamic system that shows frequency‐dependent characteristics. Recent studies demonstrate that coactivation pattern (CAP) analysis can identify recurring brain states with similar coactivation configurations. However, it is unclear whether and how CAPs depend on the frequency bands. The current study investigated the spatial and temporal characteristics of CAPs in the four frequency sub‐bands from slow‐5 (0.01–0.027 Hz), slow‐4 (0.027–0.073 Hz), slow‐3 (0.073–0.198 Hz), to slow‐2 (0.198–0.25 Hz), in addition to the typical low‐frequency range (0.01–0.08 Hz). In the healthy subjects, six CAP states were obtained at each frequency band in line with our prior study. Similar spatial patterns with the typical range were observed in slow‐5, 4, and 3, but not in slow‐2. While the frequency increased, all CAP states displayed shorter persistence, which caused more between‐state transitions. Specifically, from slow‐5 to slow‐4, the coactivation not only changed significantly in distributed cortical networks, but also increased in the basal ganglia as well as the amygdala. Schizophrenia patients showed significant alteration in the persistence of CAPs of slow‐5. Using leave‐one‐pair‐out, hold‐out and resampling validations, the highest classification accuracy (84%) was achieved by slow‐4 among different frequency bands. In conclusion, our findings provide novel information about spatial and temporal characteristics of CAP states at different frequency bands, which contributes to a better understanding of the frequency aspect of biomarkers for schizophrenia and other disorders.
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spelling pubmed-92942982022-07-20 Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study Yang, Hang Zhang, Hong Meng, Chun Wohlschläger, Afra Brandl, Felix Di, Xin Wang, Shuai Tian, Lin Biswal, Bharat Hum Brain Mapp Research Articles The resting‐state human brain is a dynamic system that shows frequency‐dependent characteristics. Recent studies demonstrate that coactivation pattern (CAP) analysis can identify recurring brain states with similar coactivation configurations. However, it is unclear whether and how CAPs depend on the frequency bands. The current study investigated the spatial and temporal characteristics of CAPs in the four frequency sub‐bands from slow‐5 (0.01–0.027 Hz), slow‐4 (0.027–0.073 Hz), slow‐3 (0.073–0.198 Hz), to slow‐2 (0.198–0.25 Hz), in addition to the typical low‐frequency range (0.01–0.08 Hz). In the healthy subjects, six CAP states were obtained at each frequency band in line with our prior study. Similar spatial patterns with the typical range were observed in slow‐5, 4, and 3, but not in slow‐2. While the frequency increased, all CAP states displayed shorter persistence, which caused more between‐state transitions. Specifically, from slow‐5 to slow‐4, the coactivation not only changed significantly in distributed cortical networks, but also increased in the basal ganglia as well as the amygdala. Schizophrenia patients showed significant alteration in the persistence of CAPs of slow‐5. Using leave‐one‐pair‐out, hold‐out and resampling validations, the highest classification accuracy (84%) was achieved by slow‐4 among different frequency bands. In conclusion, our findings provide novel information about spatial and temporal characteristics of CAP states at different frequency bands, which contributes to a better understanding of the frequency aspect of biomarkers for schizophrenia and other disorders. John Wiley & Sons, Inc. 2022-04-27 /pmc/articles/PMC9294298/ /pubmed/35475569 http://dx.doi.org/10.1002/hbm.25884 Text en © 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Yang, Hang
Zhang, Hong
Meng, Chun
Wohlschläger, Afra
Brandl, Felix
Di, Xin
Wang, Shuai
Tian, Lin
Biswal, Bharat
Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study
title Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study
title_full Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study
title_fullStr Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study
title_full_unstemmed Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study
title_short Frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: An fMRI study
title_sort frequency‐specific coactivation patterns in resting‐state and their alterations in schizophrenia: an fmri study
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294298/
https://www.ncbi.nlm.nih.gov/pubmed/35475569
http://dx.doi.org/10.1002/hbm.25884
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