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A systematic review of fMRI neurofeedback reporting and effects in clinical populations
Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724376/ https://www.ncbi.nlm.nih.gov/pubmed/33395987 http://dx.doi.org/10.1016/j.nicl.2020.102496 |
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author | Tursic, Anita Eck, Judith Lührs, Michael Linden, David E.J. Goebel, Rainer |
author_facet | Tursic, Anita Eck, Judith Lührs, Michael Linden, David E.J. Goebel, Rainer |
author_sort | Tursic, Anita |
collection | PubMed |
description | Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting. |
format | Online Article Text |
id | pubmed-7724376 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-77243762020-12-13 A systematic review of fMRI neurofeedback reporting and effects in clinical populations Tursic, Anita Eck, Judith Lührs, Michael Linden, David E.J. Goebel, Rainer Neuroimage Clin Articles from the Special Issue on "Clinical applications of imaging-based neurofeedback" Edited by Heidi Johansen-Berg and Kymberly Young Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting. Elsevier 2020-11-11 /pmc/articles/PMC7724376/ /pubmed/33395987 http://dx.doi.org/10.1016/j.nicl.2020.102496 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles from the Special Issue on "Clinical applications of imaging-based neurofeedback" Edited by Heidi Johansen-Berg and Kymberly Young Tursic, Anita Eck, Judith Lührs, Michael Linden, David E.J. Goebel, Rainer A systematic review of fMRI neurofeedback reporting and effects in clinical populations |
title | A systematic review of fMRI neurofeedback reporting and effects in clinical populations |
title_full | A systematic review of fMRI neurofeedback reporting and effects in clinical populations |
title_fullStr | A systematic review of fMRI neurofeedback reporting and effects in clinical populations |
title_full_unstemmed | A systematic review of fMRI neurofeedback reporting and effects in clinical populations |
title_short | A systematic review of fMRI neurofeedback reporting and effects in clinical populations |
title_sort | systematic review of fmri neurofeedback reporting and effects in clinical populations |
topic | Articles from the Special Issue on "Clinical applications of imaging-based neurofeedback" Edited by Heidi Johansen-Berg and Kymberly Young |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724376/ https://www.ncbi.nlm.nih.gov/pubmed/33395987 http://dx.doi.org/10.1016/j.nicl.2020.102496 |
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