LISA improves statistical analysis for fMRI
Functional magnetic resonance imaging (fMRI) is a powerful technique for measuring human brain activity, but the statistical analysis of fMRI data can be difficult. Here, the authors introduce a new fMRI analysis tool, LISA, which provides increased statistical power compared to existing techniques.
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Nature Publishing Group
2018-10-01
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Online Access: | https://doi.org/10.1038/s41467-018-06304-z |
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doaj-7f07805dbd994058bbc72fc35d55f56c2021-05-11T09:32:00ZengNature Publishing GroupNature Communications2041-17232018-10-01911910.1038/s41467-018-06304-zLISA improves statistical analysis for fMRIGabriele Lohmann0Johannes Stelzer1Eric Lacosse2Vinod J. Kumar3Karsten Mueller4Esther Kuehn5Wolfgang Grodd6Klaus Scheffler7Department of Biomedical Magnetic Resonance Imaging, University Hospital TübingenDepartment of Biomedical Magnetic Resonance Imaging, University Hospital TübingenMagnetic Resonance Centre, Max-Planck-Institute for Biological CyberneticsMagnetic Resonance Centre, Max-Planck-Institute for Biological CyberneticsMethods & Development Group Nuclear Magnetic Resonance, Max-Planck-Institute for Human Cognitive and Brain SciencesGerman Center for Neurodegenerative Diseases (DZNE)Magnetic Resonance Centre, Max-Planck-Institute for Biological CyberneticsDepartment of Biomedical Magnetic Resonance Imaging, University Hospital TübingenFunctional magnetic resonance imaging (fMRI) is a powerful technique for measuring human brain activity, but the statistical analysis of fMRI data can be difficult. Here, the authors introduce a new fMRI analysis tool, LISA, which provides increased statistical power compared to existing techniques.https://doi.org/10.1038/s41467-018-06304-z |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gabriele Lohmann Johannes Stelzer Eric Lacosse Vinod J. Kumar Karsten Mueller Esther Kuehn Wolfgang Grodd Klaus Scheffler |
spellingShingle |
Gabriele Lohmann Johannes Stelzer Eric Lacosse Vinod J. Kumar Karsten Mueller Esther Kuehn Wolfgang Grodd Klaus Scheffler LISA improves statistical analysis for fMRI Nature Communications |
author_facet |
Gabriele Lohmann Johannes Stelzer Eric Lacosse Vinod J. Kumar Karsten Mueller Esther Kuehn Wolfgang Grodd Klaus Scheffler |
author_sort |
Gabriele Lohmann |
title |
LISA improves statistical analysis for fMRI |
title_short |
LISA improves statistical analysis for fMRI |
title_full |
LISA improves statistical analysis for fMRI |
title_fullStr |
LISA improves statistical analysis for fMRI |
title_full_unstemmed |
LISA improves statistical analysis for fMRI |
title_sort |
lisa improves statistical analysis for fmri |
publisher |
Nature Publishing Group |
series |
Nature Communications |
issn |
2041-1723 |
publishDate |
2018-10-01 |
description |
Functional magnetic resonance imaging (fMRI) is a powerful technique for measuring human brain activity, but the statistical analysis of fMRI data can be difficult. Here, the authors introduce a new fMRI analysis tool, LISA, which provides increased statistical power compared to existing techniques. |
url |
https://doi.org/10.1038/s41467-018-06304-z |
work_keys_str_mv |
AT gabrielelohmann lisaimprovesstatisticalanalysisforfmri AT johannesstelzer lisaimprovesstatisticalanalysisforfmri AT ericlacosse lisaimprovesstatisticalanalysisforfmri AT vinodjkumar lisaimprovesstatisticalanalysisforfmri AT karstenmueller lisaimprovesstatisticalanalysisforfmri AT estherkuehn lisaimprovesstatisticalanalysisforfmri AT wolfganggrodd lisaimprovesstatisticalanalysisforfmri AT klausscheffler lisaimprovesstatisticalanalysisforfmri |
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1721449663844843520 |