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Predicting individual variability in task‐evoked brain activity in schizophrenia
What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMR...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8288090/ https://www.ncbi.nlm.nih.gov/pubmed/34021674 http://dx.doi.org/10.1002/hbm.25534 |
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author | Tik, Niv Livny, Abigail Gal, Shachar Gigi, Karny Tsarfaty, Galia Weiser, Mark Tavor, Ido |
author_facet | Tik, Niv Livny, Abigail Gal, Shachar Gigi, Karny Tsarfaty, Galia Weiser, Mark Tavor, Ido |
author_sort | Tik, Niv |
collection | PubMed |
description | What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting‐state functional connectivity and brain activity during the well‐validated N‐back task differed significantly between schizophrenia patients and healthy controls. Nevertheless, using a machine‐learning approach we were able to use resting‐state functional connectivity measures extracted from healthy controls to accurately predict individual variability in the task‐evoked brain activation in the schizophrenia patients. The predictions were highly accurate, sensitive, and specific, offering novel insights regarding the strong coupling between brain connectivity and activity in schizophrenia. On a practical perspective, these findings may allow to generate task activity maps for clinical populations without the need to actually perform any tasks, thereby reducing patients inconvenience while saving time and money. |
format | Online Article Text |
id | pubmed-8288090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82880902021-07-21 Predicting individual variability in task‐evoked brain activity in schizophrenia Tik, Niv Livny, Abigail Gal, Shachar Gigi, Karny Tsarfaty, Galia Weiser, Mark Tavor, Ido Hum Brain Mapp Research Articles What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting‐state functional connectivity and brain activity during the well‐validated N‐back task differed significantly between schizophrenia patients and healthy controls. Nevertheless, using a machine‐learning approach we were able to use resting‐state functional connectivity measures extracted from healthy controls to accurately predict individual variability in the task‐evoked brain activation in the schizophrenia patients. The predictions were highly accurate, sensitive, and specific, offering novel insights regarding the strong coupling between brain connectivity and activity in schizophrenia. On a practical perspective, these findings may allow to generate task activity maps for clinical populations without the need to actually perform any tasks, thereby reducing patients inconvenience while saving time and money. John Wiley & Sons, Inc. 2021-05-22 /pmc/articles/PMC8288090/ /pubmed/34021674 http://dx.doi.org/10.1002/hbm.25534 Text en © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Tik, Niv Livny, Abigail Gal, Shachar Gigi, Karny Tsarfaty, Galia Weiser, Mark Tavor, Ido Predicting individual variability in task‐evoked brain activity in schizophrenia |
title | Predicting individual variability in task‐evoked brain activity in schizophrenia |
title_full | Predicting individual variability in task‐evoked brain activity in schizophrenia |
title_fullStr | Predicting individual variability in task‐evoked brain activity in schizophrenia |
title_full_unstemmed | Predicting individual variability in task‐evoked brain activity in schizophrenia |
title_short | Predicting individual variability in task‐evoked brain activity in schizophrenia |
title_sort | predicting individual variability in task‐evoked brain activity in schizophrenia |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8288090/ https://www.ncbi.nlm.nih.gov/pubmed/34021674 http://dx.doi.org/10.1002/hbm.25534 |
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