Quality and denoising in real‐time functional magnetic resonance imaging neurofeedback: A methods review

Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non‐invasive treatment option in neuropsychiatric and neurocognitive disorders, alt...

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Published inHuman brain mapping Vol. 41; no. 12; pp. 3439 - 3467
Main Authors Heunis, Stephan, Lamerichs, Rolf, Zinger, Svitlana, Caballero‐Gaudes, Cesar, Jansen, Jacobus F. A., Aldenkamp, Bert, Breeuwer, Marcel
Format Journal Article
LanguageEnglish
Published Hoboken, USA John Wiley & Sons, Inc 15.08.2020
Subjects
Biofeedback
Biofeedback training
Brain mapping
Cognition
Control methods
Data retrieval
denoising
Electroencephalography
Feedback
fMRI
Functional magnetic resonance imaging
Functional Neuroimaging - methods
Functional Neuroimaging - standards
Humans
Image Processing, Computer-Assisted - methods
Image Processing, Computer-Assisted - standards
Learning strategies
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Magnetic Resonance Imaging - standards
Mental disorders
neurofeedback
Neurofeedback - methods
Neuroimaging
Noise reduction
quality
Quality Control
real‐time
Reproducibility
Resonance
Review
Signal quality
Software
denoising
fMRI
real-time
reproducibility
neurofeedback
quality
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Abstract Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non‐invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI‐NF studies. We found: (a) that less than a third of the studies reported implementing standard real‐time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI‐NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI‐NF studies: (a) report implementation of a set of standard real‐time fMRI denoising steps according to a proposed COBIDAS‐style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community‐informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open‐source rtfMRI‐NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality‐and‐denoising‐in‐rtfmri‐nf.
AbstractList Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non‐invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI‐NF studies. We found: (a) that less than a third of the studies reported implementing standard real‐time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI‐NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI‐NF studies: (a) report implementation of a set of standard real‐time fMRI denoising steps according to a proposed COBIDAS‐style checklist ( https://osf.io/kjwhf/ ), (b) ensure the quality of the neurofeedback signal by calculating and reporting community‐informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open‐source rtfMRI‐NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality‐and‐denoising‐in‐rtfmri‐nf.
Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI-NF studies. We found: (a) that less than a third of the studies reported implementing standard real-time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI-NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open-source rtfMRI-NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality-and-denoising-in-rtfmri-nf.Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI-NF studies. We found: (a) that less than a third of the studies reported implementing standard real-time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI-NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open-source rtfMRI-NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality-and-denoising-in-rtfmri-nf.
Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI-NF studies. We found: (a) that less than a third of the studies reported implementing standard real-time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI-NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open-source rtfMRI-NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality-and-denoising-in-rtfmri-nf.
Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI-NF studies. We found: (a) that less than a third of the studies reported implementing standard real-time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI-NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (
Audience Academic
Author Lamerichs, Rolf
Aldenkamp, Bert
Zinger, Svitlana
Heunis, Stephan
Caballero‐Gaudes, Cesar
Jansen, Jacobus F. A.
Breeuwer, Marcel
AuthorAffiliation 1 Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands
6 School for Mental Health and Neuroscience Maastricht The Netherlands
9 Department of Biomedical Engineering Eindhoven University of Technology Eindhoven The Netherlands
8 Department of Neurology Maastricht University Medical Center Maastricht The Netherlands
10 Philips Healthcare Best The Netherlands
5 Department of Radiology Maastricht University Medical Centre Maastricht The Netherlands
4 Basque Center on Cognition Brain and Language San Sebastian Spain
7 Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Ghent University Hospital Ghent Belgium
2 Department of Research and Development Epilepsy Centre Kempenhaeghe Heeze The Netherlands
3 Philips Research Eindhoven The Netherlands
AuthorAffiliation_xml – name: 9 Department of Biomedical Engineering Eindhoven University of Technology Eindhoven The Netherlands
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– name: 2 Department of Research and Development Epilepsy Centre Kempenhaeghe Heeze The Netherlands
– name: 7 Laboratory for Clinical and Experimental Neurophysiology, Neurobiology and Neuropsychology Ghent University Hospital Ghent Belgium
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– name: 1 Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/32333624$$D View this record in MEDLINE/PubMed
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Cites_doi 10.1016/j.neuroimage.2018.10.021
10.1523/JNEUROSCI.3098-14.2015
10.1371/journal.pcbi.1005681
10.1016/j.neuroimage.2013.08.048
10.1002/(SICI)1522-2594(199907)42:1<87::AID-MRM13>3.0.CO;2-O
10.1073/pnas.0505210102
10.1016/j.neuroimage.2005.02.050
10.1016/S1053-8119(09)72192-5
10.1016/j.neuroimage.2010.06.052
10.1016/j.neuroimage.2018.12.006
10.1002/hbm.23584
10.1002/mrm.27146
10.1016/j.neuroimage.2010.07.060
10.1002/mrm.21136
10.1016/j.neuroimage.2005.01.007
10.1016/j.mri.2007.02.007
10.1016/j.appet.2017.01.032
10.1016/j.neuroimage.2012.09.043
10.1002/mrm.20261
10.1093/ntr/ntt122
10.1016/j.cub.2012.05.022
10.3389/fnhum.2016.00183
10.1002/1522-2594(200007)44:1<162::AID-MRM23>3.0.CO;2-E
10.1016/j.neuroimage.2011.10.018
10.1002/1522-2594(200102)45:2<289::AID-MRM1038>3.0.CO;2-U
10.1016/j.neuroimage.2016.10.048
10.1016/j.neuroimage.2016.12.024
10.1016/j.neuroimage.2013.03.033
10.1002/mrm.1910350312
10.1016/j.mri.2006.09.042
10.3389/fnbeh.2015.00003
10.1126/scitranslmed.aaf5027
10.1371/journal.pone.0085929
10.1002/jmri.20935
10.1016/j.neuroimage.2016.12.018
10.1016/j.neuroimage.2003.08.012
10.1016/j.neuroimage.2017.06.039
10.1016/j.jneumeth.2008.08.013
10.1371/journal.pone.0038115
10.1016/j.neuroimage.2014.03.034
10.1002/mrm.1222
10.1371/journal.pone.0077089
10.1016/j.neuroimage.2012.02.015
10.1371/journal.pbio.1002546
10.1016/j.neuroimage.2006.10.026
10.1126/science.1212003
10.1162/jocn_a_00802
10.1016/j.tics.2017.09.010
10.1523/JNEUROSCI.5911-12.2013
10.1016/j.neuroimage.2014.03.073
10.1016/j.neuroimage.2016.09.008
10.1016/j.neuroimage.2019.02.058
10.1002/hbm.20997
10.1016/j.neuroimage.2015.09.042
10.1006/nimg.2001.0900
10.1002/1097-0193(200101)12:1<25::AID-HBM30>3.0.CO;2-H
10.1038/nn.4500
10.1093/cercor/bhx177
10.1007/s10548-014-0384-4
10.1146/annurev.biophys.27.1.447
10.1016/j.cmpb.2011.07.007
10.1523/JNEUROSCI.23-10-03963.2003
10.1073/pnas.1720985115
10.1016/j.neuroimage.2017.08.025
10.1016/j.neuroimage.2017.12.071
10.3389/fninf.2011.00027
10.1016/j.neuroimage.2016.11.052
10.1002/mrm.10259
10.1016/j.tics.2007.08.014
10.1016/j.neuroscience.2016.09.026
10.1016/j.eurpsy.2017.10.011
10.1007/s12021-013-9176-3
10.1016/j.yebeh.2010.08.004
10.1109/TBME.2004.827063
10.1097/00001756-200208070-00005
10.1002/hbm.20326
10.1016/j.neuroimage.2011.06.078
10.1371/journal.pone.0170795
10.1016/j.jneumeth.2015.08.033
10.1016/S1053-8119(03)00081-8
10.1371/journal.pone.0118890
10.1111/j.1552-6569.2010.00529.x
10.1016/j.neuroimage.2013.05.115
10.1016/j.dib.2017.07.049
10.1002/mrm.24314
10.1016/j.neuroimage.2011.07.044
10.1016/j.neuroscience.2016.12.050
10.1002/1522-2594(200101)45:1<167::AID-MRM1023>3.0.CO;2-M
10.1002/mrm.25770
10.1016/j.neuroimage.2016.08.009
10.1006/nimg.2002.1132
10.1007/s10548-009-0121-6
10.1007/s12529-011-9165-6
10.1006/nimg.1999.0457
10.3389/fnbeh.2015.00341
10.1371/journal.pone.0088785
10.1038/nn.4499
10.1016/j.neuroimage.2008.09.029
10.1002/mrm.1910330213
10.1016/j.neuroimage.2017.03.033
10.1002/mrm.20900
10.1002/mrm.1240
10.1038/nrn.2016.164
10.1016/j.neuroimage.2017.10.031
10.1016/j.nicl.2016.12.023
10.1016/j.neuroimage.2005.04.039
10.1002/1522-2594(200012)44:6<925::AID-MRM14>3.0.CO;2-M
10.1002/(SICI)1522-2594(199912)42:6<1014::AID-MRM4>3.0.CO;2-F
10.1016/j.neuroimage.2003.08.041
10.1016/j.neuroimage.2006.09.032
10.1016/j.neuroimage.2018.01.023
10.1016/S1053-8119(03)00058-2
10.1016/j.neuroimage.2013.06.010
10.1016/j.neuroimage.2010.12.016
10.1177/1073858411407205
10.1002/(SICI)1522-2594(200002)43:2<259::AID-MRM13>3.0.CO;2-P
10.1016/j.neuroimage.2004.10.012
10.1371/journal.pone.0184661
10.1002/hbm.21427
10.1016/j.neuroimage.2006.02.048
10.1016/j.neuroimage.2013.04.001
10.1109/ICIP.1994.413892
10.1093/scan/nsq024
10.1016/S1053-8119(02)00016-2
10.2463/mrms.5.157
10.1002/mrm.1910310307
10.1016/j.neuroimage.2016.09.038
10.1002/hbm.22307
10.1097/00006123-200009000-00037
10.1016/j.neuroimage.2013.05.030
10.1016/j.pscychresns.2016.01.016
10.1016/j.neuroimage.2013.05.010
10.1038/s41562-016-0021
10.1371/journal.pone.0027638
10.1016/j.ejrad.2011.09.025
10.1016/j.neuroimage.2012.02.059
10.1016/j.nicl.2014.07.002
10.1016/j.neuroimage.2011.07.076
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ISSN 1065-9471
1097-0193
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IsDoiOpenAccess true
IsOpenAccess true
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IsScholarly true
Issue 12
Keywords denoising
fMRI
real-time
reproducibility
neurofeedback
quality
Language English
License Attribution
2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.
This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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MergedId FETCHMERGED-LOGICAL-c5100-183ce032d9a54c3a8c0d0fb7df9f85d40f8b94671dab204945b86dac95a7897d3
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LSH‐TKI, Grant/Award Number: LSHM16053‐SGF; Philips Research
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content type line 14
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Funding information LSH‐TKI, Grant/Award Number: LSHM16053‐SGF; Philips Research
ORCID 0000-0003-3503-9872
0000-0002-5271-8060
OpenAccessLink https://proxy.k.utb.cz/login?url=https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fhbm.25010
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PublicationTitle Human brain mapping
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References 2004; 21
2002; 17
2018; 166
2006; 31
2018; 168
2002; 13
2013; 64
1995; 33
2011; 55
2012; 19
2011; 54
2016; 143
2012; 18
1999; 42
2011; 56
2017; 154
2011; 58
2001; 45
2013; 8
2001; 46
2010; 23
2018; 171
2018; 172
2000; 12
2005; 102
2015; 256
2017; 161
2014; 96
2014; 95
2010; 5
2012; 22
2010; 32
2019; 191
2017b; 27
2006; 55
2013; 83
2016; 10
1998
1994
2019; 185
2011; 6
2007; 11
2012; 105
2019; 188
2016; 14
2004; 52
2004; 51
2013; 76
2018; 115
2013; 80
2013; 82
2013; 81
2014; 35
2017; 146
2003; 20
2016; 8
2003; 23
2015; 35
2012; 61
2009; 44
2009; 47
2017; 1
2000; 47
2000; 43
2000; 44
2016; 75
2018; 80
2003; 18
2003; 19
2012; 59
2005; 26
2005; 27
1996; 35
2017; 112
2007; 34
2005; 24
2007; 28
2002; 48
2013; 15
2014; 5
2013; 11
2000
2017; 38
2018; 378
2011; 20
1999; 10
2017c; 14
2012; 69
2014; 9
2001; 14
2007; 25
1994; 31
2012; 62
1998; 27
2017; 20
2017a; 156
2011; 334
2012
2011
2017; 27
2017; 21
2015; 10
2016; 124
2006; 5
2016; 249
2015; 9
2014; 84
2007; 57
2004; 98
2015; 28
2015; 27
2013; 33
2017; 14
2020
2013; 34
2017; 13
2017; 12
2019
2018
2017
2016
2017; 18
2014
2018; 50
2012; 7
2008; 175
e_1_2_13_120_1
e_1_2_13_24_1
e_1_2_13_47_1
e_1_2_13_20_1
e_1_2_13_66_1
e_1_2_13_101_1
e_1_2_13_147_1
e_1_2_13_43_1
e_1_2_13_124_1
e_1_2_13_85_1
e_1_2_13_8_1
e_1_2_13_62_1
e_1_2_13_81_1
Weiskopf N. (e_1_2_13_143_1) 2004; 98
e_1_2_13_92_1
e_1_2_13_117_1
e_1_2_13_17_1
e_1_2_13_13_1
e_1_2_13_36_1
e_1_2_13_59_1
Hellrung L. (e_1_2_13_51_1) 2018
e_1_2_13_131_1
e_1_2_13_32_1
e_1_2_13_55_1
e_1_2_13_78_1
e_1_2_13_135_1
e_1_2_13_74_1
e_1_2_13_70_1
e_1_2_13_150_1
e_1_2_13_4_1
e_1_2_13_105_1
e_1_2_13_88_1
e_1_2_13_128_1
e_1_2_13_29_1
e_1_2_13_109_1
e_1_2_13_25_1
e_1_2_13_48_1
e_1_2_13_100_1
e_1_2_13_142_1
e_1_2_13_21_1
e_1_2_13_44_1
e_1_2_13_67_1
e_1_2_13_104_1
e_1_2_13_123_1
e_1_2_13_86_1
e_1_2_13_146_1
e_1_2_13_9_1
e_1_2_13_40_1
e_1_2_13_63_1
e_1_2_13_82_1
e_1_2_13_91_1
e_1_2_13_95_1
e_1_2_13_116_1
e_1_2_13_99_1
Posse S. (e_1_2_13_102_1) 1998
e_1_2_13_139_1
e_1_2_13_18_1
e_1_2_13_14_1
e_1_2_13_111_1
e_1_2_13_130_1
e_1_2_13_37_1
e_1_2_13_79_1
e_1_2_13_10_1
e_1_2_13_56_1
e_1_2_13_115_1
e_1_2_13_134_1
e_1_2_13_33_1
e_1_2_13_75_1
e_1_2_13_52_1
e_1_2_13_71_1
e_1_2_13_5_1
e_1_2_13_108_1
e_1_2_13_127_1
e_1_2_13_49_1
e_1_2_13_122_1
e_1_2_13_141_1
e_1_2_13_26_1
e_1_2_13_68_1
e_1_2_13_45_1
e_1_2_13_126_1
e_1_2_13_87_1
e_1_2_13_145_1
e_1_2_13_22_1
e_1_2_13_64_1
e_1_2_13_103_1
e_1_2_13_41_1
e_1_2_13_60_1
e_1_2_13_83_1
e_1_2_13_6_1
e_1_2_13_90_1
e_1_2_13_94_1
e_1_2_13_98_1
e_1_2_13_119_1
e_1_2_13_138_1
Poldrack R. A. (e_1_2_13_96_1) 2011
e_1_2_13_19_1
e_1_2_13_133_1
e_1_2_13_15_1
e_1_2_13_38_1
e_1_2_13_57_1
e_1_2_13_110_1
e_1_2_13_152_1
Wang Y. (e_1_2_13_137_1) 2016
e_1_2_13_11_1
e_1_2_13_34_1
e_1_2_13_53_1
e_1_2_13_76_1
e_1_2_13_114_1
e_1_2_13_30_1
e_1_2_13_72_1
e_1_2_13_2_1
Koush Y. (e_1_2_13_69_1) 2017; 27
e_1_2_13_107_1
Ros T. (e_1_2_13_112_1) 2020
e_1_2_13_149_1
e_1_2_13_121_1
e_1_2_13_144_1
e_1_2_13_27_1
e_1_2_13_46_1
e_1_2_13_125_1
e_1_2_13_148_1
e_1_2_13_23_1
e_1_2_13_42_1
e_1_2_13_65_1
e_1_2_13_84_1
e_1_2_13_7_1
e_1_2_13_61_1
e_1_2_13_80_1
e_1_2_13_140_1
Thesen S. (e_1_2_13_129_1) 2000
e_1_2_13_93_1
e_1_2_13_97_1
e_1_2_13_118_1
e_1_2_13_39_1
e_1_2_13_132_1
e_1_2_13_35_1
e_1_2_13_16_1
e_1_2_13_58_1
e_1_2_13_113_1
e_1_2_13_136_1
e_1_2_13_31_1
e_1_2_13_77_1
e_1_2_13_12_1
e_1_2_13_54_1
e_1_2_13_73_1
e_1_2_13_50_1
e_1_2_13_151_1
e_1_2_13_3_1
e_1_2_13_106_1
e_1_2_13_89_1
e_1_2_13_28_1
References_xml – volume: 146
  start-page: 609
  year: 2017
  end-page: 625
  article-title: Sources and implications of whole‐brain fMRI signals in humans
  publication-title: NeuroImage
– start-page: 1242
  year: 2016
  end-page: 1251
  article-title: Real‐time full correlation matrix analysis of fMRI data
  publication-title: IEEE International Conference on Big Data (Big Data), IEEE
– volume: 175
  start-page: 154
  year: 2008
  end-page: 162
  article-title: A new concept of a unified parameter management, experiment control, and data analysis in fMRI: Application to real‐time fMRI at 3 T and 7 T
  publication-title: Journal of Neuroscience Methods
– volume: 1
  start-page: 0021
  year: 2017
  article-title: A manifesto for reproducible science
  publication-title: Nature Human Behaviour
– volume: 26
  start-page: 243
  year: 2005
  end-page: 250
  article-title: Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters
  publication-title: NeuroImage
– volume: 80
  start-page: 1697
  year: 2018
  end-page: 1713
  article-title: Hemodynamic response function (HRF) variability confounds resting‐state fMRI functional connectivity
  publication-title: Magnetic Resonance in Medicine
– volume: 23
  start-page: 3963
  year: 2003
  end-page: 3971
  article-title: The underpinnings of the BOLD functional magnetic resonance imaging signal
  publication-title: The Journal of Neuroscience
– volume: 69
  start-page: 621
  year: 2012
  end-page: 636
  article-title: Prospective motion correction in brain imaging: A review
  publication-title: Magnetic Resonance in Medicine
– volume: 5
  start-page: 157
  year: 2006
  end-page: 165
  article-title: Real‐time functional MRI: Development and emerging applications
  publication-title: Magnetic Resonance in Medical Sciences
– volume: 5
  start-page: 245
  year: 2014
  end-page: 255
  article-title: Optimizing real time fMRI neurofeedback for therapeutic discovery and development
  publication-title: NeuroImage
– volume: 45
  start-page: 289
  year: 2001
  end-page: 298
  article-title: Real‐time multiple linear regression for fMRI supported by time‐aware acquisition and processing
  publication-title: Magnetic Resonance in Medicine
– volume: 42
  start-page: 1014
  year: 1999
  end-page: 1018
  article-title: Real‐time 3D image registration for functional MRI
  publication-title: Magnetic Resonance in Medicine
– volume: 28
  start-page: 1033
  year: 2007
  end-page: 1044
  article-title: Real‐time fMRI using brain‐state classification
  publication-title: Human Brain Mapping
– volume: 25
  start-page: 989
  year: 2007
  end-page: 1003
  article-title: Real‐time functional magnetic resonance imaging: Methods and applications
  publication-title: Magnetic Resonance Imaging
– volume: 5
  start-page: 98
  year: 2010
  end-page: 107
  article-title: It's in your eyes—Using gaze‐contingent stimuli to create truly interactive paradigms for social cognitive and affective neuroscience
  publication-title: Social Cognitive and Affective Neuroscience
– volume: 33
  start-page: 230
  year: 1995
  end-page: 236
  article-title: Real‐time functional magnetic resonance imaging
  publication-title: Magnetic Resonance in Medicine
– year: 2020
  publication-title: Brain
– volume: 57
  start-page: 362
  year: 2007
  end-page: 368
  article-title: Real‐time shimming to compensate for respiration‐induced B0 fluctuations
  publication-title: Magnetic Resonance in Medicine
– year: 2014
– volume: 75
  start-page: 1831
  year: 2016
  end-page: 1840
  article-title: A field camera for MR sequence monitoring and system analysis
  publication-title: Magnetic Resonance in Medicine
– volume: 58
  start-page: 588
  year: 2011
  end-page: 594
  article-title: Slice‐timing effects and their correction in functional MRI
  publication-title: NeuroImage
– volume: 55
  start-page: 1298
  year: 2011
  end-page: 1305
  article-title: Improved modulation of rostrolateral prefrontal cortex using real‐time fMRI training and meta‐cognitive awareness
  publication-title: NeuroImage
– volume: 80
  start-page: 349
  year: 2013
  end-page: 359
  article-title: Resting‐state FMRI confounds and cleanup
  publication-title: NeuroImage
– volume: 6
  year: 2011
  article-title: Real‐time decoding of brain responses to visuospatial attention using 7T fMRI
  publication-title: PLoS One
– volume: 59
  start-page: 2142
  year: 2012
  end-page: 2154
  article-title: Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion
  publication-title: NeuroImage
– volume: 47
  start-page: S194
  year: 2009
  article-title: The use of neurofeedback with real‐time functional MRI to suppress physiological noise
  publication-title: NeuroImage
– volume: 188
  start-page: 322
  year: 2019
  end-page: 334
  article-title: A framework for offline evaluation and optimization of real‐time algorithms for use in neurofeedback, demonstrated on an instantaneous proxy for correlations
  publication-title: NeuroImage
– volume: 9
  year: 2015
  article-title: Enhancing motor network activity using real‐time functional MRI neurofeedback of left premotor cortex
  publication-title: Frontiers in Behavioral Neuroscience
– volume: 21
  start-page: 997
  year: 2017
  end-page: 1010
  article-title: Advances in fMRI real‐time neurofeedback
  publication-title: Trends in Cognitive Sciences
– volume: 20
  start-page: 299
  year: 2017
  end-page: 303
  article-title: Best practices in data analysis and sharing in neuroimaging using MRI (WWW document)
  publication-title: Nature Neuroscience
– volume: 50
  start-page: 28
  year: 2018
  end-page: 33
  article-title: Current practices in clinical neurofeedback with functional MRI—Analysis of a survey using the TIDieR checklist
  publication-title: European Psychiatry
– volume: 52
  start-page: 1156
  year: 2004
  end-page: 1166
  article-title: Point spread function mapping with parallel imaging techniques and high acceleration factors: Fast, robust, and flexible method for echo‐planar imaging distortion correction
  publication-title: Magnetic Resonance in Medicine
– volume: 83
  start-page: 817
  year: 2013
  end-page: 825
  article-title: Neurofeedback‐mediated self‐regulation of the dopaminergic midbrain
  publication-title: NeuroImage
– volume: 27
  start-page: 1193
  year: 2017b
  end-page: 1202
  article-title: Learning control over emotion networks through connectivity‐based neurofeedback
  publication-title: Cerebral Cortex
– volume: 64
  start-page: 526
  year: 2013
  end-page: 537
  article-title: Removing motion and physiological artifacts from intrinsic BOLD fluctuations using short echo data
  publication-title: NeuroImage
– volume: 20
  start-page: 214
  year: 2011
  end-page: 222
  article-title: Functional MRI is a valid noninvasive alternative to Wada testing
  publication-title: Epilepsy & Behavior
– volume: 98
  start-page: 357
  year: 2004
  end-page: 373
  article-title: Self‐regulation of local brain activity using real‐time functional magnetic resonance imaging (fMRI)
  publication-title: Journal of Physiology
– volume: 34
  start-page: 1487
  year: 2007
  end-page: 1496
  article-title: Dynamic causal modeling: A generative model of slice timing in fMRI
  publication-title: NeuroImage
– year: 2019
– volume: 34
  start-page: 565
  year: 2007
  end-page: 574
  article-title: How long to scan? The relationship between fMRI temporal signal to noise and necessary scan duration
  publication-title: NeuroImage
– volume: 154
  start-page: 59
  year: 2017
  end-page: 80
  article-title: Multi‐echo fMRI: A review of applications in fMRI denoising and analysis of BOLD signals
  publication-title: NeuroImage
– volume: 19
  start-page: 372
  year: 2012
  end-page: 381
  article-title: Quantification of adverse events associated with functional MRI scanning and with real‐time fMRI‐based training
  publication-title: International Journal of Behavioral Medicine
– volume: 27
  start-page: 153
  year: 2005
  end-page: 162
  article-title: Head motion suppression using real‐time feedback of motion information and its effects on task performance in fMRI
  publication-title: NeuroImage
– volume: 105
  start-page: 145
  year: 2012
  end-page: 161
  article-title: fMRI analysis on the GPU—Possibilities and challenges
  publication-title: Computer Methods and Programs in Biomedicine
– volume: 161
  start-page: 80
  year: 2017
  end-page: 93
  article-title: Real‐time motion analytics during brain MRI improve data quality and reduce costs
  publication-title: NeuroImage
– volume: 13
  year: 2017
  article-title: Self‐regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment
  publication-title: PLoS Computational Biology
– volume: 95
  start-page: 232
  year: 2014
  end-page: 247
  article-title: ICA‐based artefact removal and accelerated fMRI acquisition for improved resting state network imaging
  publication-title: NeuroImage
– volume: 18
  start-page: 487
  year: 2012
  end-page: 501
  article-title: Real‐time fMRI: A tool for local brain regulation
  publication-title: The Neuroscientist
– volume: 62
  start-page: 1017
  year: 2012
  end-page: 1023
  article-title: The continuing challenge of understanding and modeling hemodynamic variation in fMRI
  publication-title: NeuroImage
– volume: 13
  start-page: 1377
  year: 2002
  end-page: 1381
  article-title: Functional MRI for neurofeedback: Feasibility study on a hand motor task
  publication-title: Neuroreport
– volume: 81
  start-page: 422
  year: 2013
  end-page: 430
  article-title: Connectivity‐based neurofeedback: Dynamic causal modeling for real‐time fMRI
  publication-title: NeuroImage
– volume: 249
  start-page: 91
  year: 2016
  end-page: 96
  article-title: Effects of salience‐network‐node neurofeedback training on affective biases in major depressive disorder
  publication-title: Psychiatry Research: Neuroimaging
– volume: 14
  year: 2016
  article-title: Differential activation patterns in the same brain region led to opposite emotional states
  publication-title: PLoS Biology
– volume: 20
  start-page: 304
  year: 2017
  end-page: 313
  article-title: Computational approaches to fMRI analysis
  publication-title: Nature Neuroscience
– volume: 84
  start-page: 320
  year: 2014
  end-page: 341
  article-title: Methods to detect, characterize, and remove motion artifact in resting state fMRI
  publication-title: NeuroImage
– volume: 34
  start-page: 200
  year: 2013
  end-page: 212
  article-title: Acquired self‐control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia
  publication-title: Human Brain Mapping
– volume: 81
  start-page: 110
  year: 2013
  end-page: 118
  article-title: Real‐time fMRI links subjective experience with brain activity during focused attention
  publication-title: NeuroImage
– volume: 82
  start-page: 336
  year: 2013
  end-page: 343
  article-title: Comparing neural response to painful electrical stimulation with functional MRI at 3 and 7 T
  publication-title: NeuroImage
– volume: 156
  start-page: 489
  year: 2017a
  end-page: 503
  article-title: OpenNFT: An open‐source Python/Matlab framework for real‐time fMRI neurofeedback training based on activity, connectivity and multivariate pattern analysis
  publication-title: NeuroImage
– volume: 44
  start-page: 925
  year: 2000
  end-page: 932
  article-title: Impact of signal‐to‐noise on functional MRI
  publication-title: Magnetic Resonance in Medicine
– volume: 51
  start-page: 966
  year: 2004
  end-page: 970
  article-title: Principles of a brain‐computer interface (BCI) based on real‐time functional magnetic resonance imaging (fMRI)
  publication-title: IEEE Transactions on Biomedical Engineering
– volume: 191
  start-page: 421
  year: 2019
  end-page: 429
  article-title: No time for drifting: Comparing performance and applicability of signal detrending algorithms for real‐time fMRI
  publication-title: NeuroImage
– volume: 61
  start-page: 115
  year: 2012
  end-page: 130
  article-title: Enhancement of temporal resolution and BOLD sensitivity in real‐time fMRI using multi‐slab echo‐volumar imaging
  publication-title: NeuroImage
– volume: 42
  start-page: 87
  year: 1999
  end-page: 97
  article-title: Enhancement of BOLD‐contrast sensitivity by single‐shot multi‐echo functional MR imaging
  publication-title: Magnetic Resonance in Medicine
– volume: 378
  start-page: 71
  year: 2018
  end-page: 88
  article-title: When the brain takes ‘BOLD’ steps: Real‐time fMRI neurofeedback can further enhance the ability to gradually self‐regulate regional brain activation
  publication-title: Neuroscience
– volume: 44
  start-page: 162
  year: 2000
  end-page: 167
  article-title: Image‐based method for retrospective correction of physiological motion effects in fMRI: RETROICOR
  publication-title: Magnetic Resonance in Medicine
– volume: 154
  start-page: 169
  year: 2017
  end-page: 173
  article-title: Towards a consensus regarding global signal regression for resting state functional connectivity MRI
  publication-title: NeuroImage
– year: 1998
  article-title: Single shot *‐sensitive spectroscopic imaging increases fMRI sensitivity: Preliminary evidence from visual and olfactory activation
  publication-title: International Society for Magnetic Resonance in Medicine
– volume: 35
  start-page: 1981
  year: 2014
  end-page: 1996
  article-title: Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high‐motion data points
  publication-title: Human Brain Mapping
– volume: 82
  start-page: 728
  year: 2013
  end-page: 733
  article-title: High‐resolution functional MRI of the human amygdala at 7 T
  publication-title: European Journal of Radiology
– volume: 35
  start-page: 346
  year: 1996
  end-page: 355
  article-title: Movement‐related effects in fMRI time‐series
  publication-title: Magnetic Resonance in Medicine
– volume: 334
  start-page: 1413
  year: 2011
  end-page: 1415
  article-title: Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation
  publication-title: Science
– volume: 9
  year: 2014
  article-title: Real‐time fMRI neurofeedback training of amygdala activity in patients with major depressive disorder
  publication-title: PLoS One
– volume: 27
  start-page: 624
  year: 2005
  end-page: 634
  article-title: Detecting and adjusting for artifacts in fMRI time series data
  publication-title: NeuroImage
– volume: 10
  year: 2015
  article-title: Flexible adaptive paradigms for fMRI using a novel software package ‘brain analysis in real‐time’ (BART)
  publication-title: PLoS One
– volume: 46
  start-page: 631
  year: 2001
  end-page: 637
  article-title: Physiological noise in oxygenation‐sensitive magnetic resonance imaging
  publication-title: Magnetic Resonance in Medicine
– volume: 43
  start-page: 259
  year: 2000
  end-page: 268
  article-title: Functional magnetic resonance imaging in real time (FIRE): Sliding‐window correlation analysis and reference‐vector optimization
  publication-title: Magnetic Resonance in Medicine
– volume: 27
  start-page: 4960
  year: 2017
  end-page: 4970
  article-title: Connectivity neurofeedback training can differentially change functional connectivity and cognitive performance
  publication-title: Cerebral Cortex
– volume: 11
  start-page: 473
  year: 2007
  end-page: 481
  article-title: Reading and controlling human brain activation using real‐time functional magnetic resonance imaging
  publication-title: Trends in Cognitive Sciences
– volume: 32
  start-page: 22
  year: 2010
  end-page: 31
  article-title: Modulation of subgenual anterior cingulate cortex activity with real‐time neurofeedback
  publication-title: Human Brain Mapping
– volume: 17
  start-page: 825
  year: 2002
  end-page: 841
  article-title: Improved optimization for the robust and accurate linear registration and motion correction of brain images
  publication-title: NeuroImage
– volume: 38
  start-page: 3190
  year: 2017
  end-page: 3209
  article-title: Real‐time fMRI neurofeedback in adolescents with attention deficit hyperactivity disorder
  publication-title: Human Brain Mapping
– volume: 168
  start-page: 383
  year: 2018
  end-page: 391
  article-title: Unsmoothed functional MRI of the human amygdala and bed nucleus of the stria terminalis during processing of emotional faces
  publication-title: NeuroImage
– volume: 27
  start-page: 447
  year: 1998
  end-page: 474
  article-title: On the characteristics of functional magnetic resonance imaging of the brain
  publication-title: Annual Review of Biophysics and Biomolecular Structure
– volume: 15
  start-page: 2120
  year: 2013
  end-page: 2124
  article-title: Sustained reduction of nicotine craving with real‐time neurofeedback: Exploring the role of severity of dependence
  publication-title: Nicotine & Tobacco Research
– volume: 33
  start-page: 9488
  year: 2013
  end-page: 9497
  article-title: The day‐after effect: Long term, Hebbian‐like restructuring of resting‐state fMRI patterns induced by a single epoch of cortical activation
  publication-title: The Journal of Neuroscience
– volume: 166
  start-page: 198
  year: 2018
  end-page: 208
  article-title: Intermittent compared to continuous real‐time fMRI neurofeedback boosts control over amygdala activation
  publication-title: NeuroImage
– volume: 45
  start-page: 167
  year: 2001
  end-page: 171
  article-title: Evaluation of motion and realignment for functional magnetic resonance imaging in real time
  publication-title: Magnetic Resonance in Medicine
– volume: 18
  start-page: 86
  year: 2017
  end-page: 100
  article-title: Closed‐loop brain training: The science of neurofeedback
  publication-title: Nature Reviews Neuroscience
– volume: 12
  start-page: 25
  year: 2000
  end-page: 41
  article-title: A new approach to measure single‐event related brain activity using real‐time fMRI: Feasibility of sensory, motor, and higher cognitive tasks
  publication-title: Human Brain Mapping
– volume: 11
  start-page: 291
  year: 2013
  end-page: 300
  article-title: A graphics processing unit accelerated motion correction algorithm and modular system for real‐time fMRI
  publication-title: Neuroinformatics
– volume: 22
  start-page: 58
  year: 2012
  end-page: 66
  article-title: Intermittent “real‐time” fMRI feedback is superior to continuous presentation for a motor imagery task: A pilot study
  publication-title: Journal of Neuroimaging
– volume: 24
  start-page: 1068
  year: 2005
  end-page: 1079
  article-title: Single‐shot compensation of image distortions and BOLD contrast optimization using multi‐echo EPI for real‐time fMRI
  publication-title: NeuroImage
– volume: 46
  start-page: 515
  year: 2001
  end-page: 522
  article-title: Spiral‐in/out BOLD fMRI for increased SNR and reduced susceptibility artifacts
  publication-title: Magnetic Resonance in Medicine
– year: 1994
– year: 2011
  article-title: Handbook of Functional MRI Data Analysis [WWW Document]
  publication-title: Cambridge Core
– volume: 154
  start-page: 150
  year: 2017
  end-page: 158
  article-title: A simple but useful way to assess fMRI scan qualities
  publication-title: NeuroImage
– volume: 31
  start-page: 283
  year: 1994
  end-page: 291
  article-title: Artifacts due to stimulus correlated motion in functional imaging of the brain
  publication-title: Magnetic Resonance in Medicine
– volume: 59
  start-page: 431
  year: 2012
  end-page: 438
  article-title: The influence of head motion on intrinsic functional connectivity MRI
  publication-title: NeuroImage
– year: 2011
  article-title: Automated real‐time behavioral and physiological data acquisition and display integrated with stimulus presentation for fMRI
  publication-title: Frontiers in Neuroinformatics,
– volume: 124
  start-page: 806
  year: 2016
  end-page: 812
  article-title: Meta‐analysis of real‐time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?
  publication-title: NeuroImage
– volume: 10
  year: 2016
  article-title: Amygdala regulation following fMRI‐neurofeedback without instructed strategies
  publication-title: Frontiers in Human Neuroscience
– volume: 154
  start-page: 128
  year: 2017
  end-page: 149
  article-title: Methods for cleaning the BOLD fMRI signal
  publication-title: NeuroImage
– volume: 18
  start-page: 390
  year: 2003
  end-page: 400
  article-title: Single‐shot * mapping with 3D compensation of local susceptibility gradients in multiple regions
  publication-title: NeuroImage
– volume: 25
  start-page: 1263
  year: 2007
  end-page: 1270
  article-title: Contrast‐to‐noise ratio (CNR) as a quality parameter in fMRI
  publication-title: Journal of Magnetic Resonance Imaging
– volume: 172
  start-page: 786
  year: 2018
  end-page: 807
  article-title: Neurofeedback with fMRI: A critical systematic review
  publication-title: NeuroImage
– volume: 28
  start-page: 197
  year: 2015
  end-page: 207
  article-title: Upregulation of the rostral anterior cingulate cortex can Alter the perception of emotions: fMRI‐based neurofeedback at 3 and 7 T
  publication-title: Brain Topography
– volume: 14
  start-page: 97
  year: 2017
  end-page: 104
  article-title: Continuous vs. intermittent neurofeedback to regulate auditory cortex activity of tinnitus patients using real‐time fMRI—A pilot study
  publication-title: NeuroImage
– volume: 14
  start-page: 967
  year: 2001
  end-page: 976
  article-title: Regional differences in the refractory period of the hemodynamic response: An event‐related fMRI study
  publication-title: NeuroImage
– volume: 7
  year: 2012
  article-title: Real‐time self‐regulation of emotion networks in patients with depression
  publication-title: PLoS One
– volume: 54
  start-page: 361
  year: 2011
  end-page: 368
  article-title: Computing moment‐to‐moment BOLD activation for real‐time neurofeedback
  publication-title: NeuroImage
– volume: 102
  start-page: 18626
  year: 2005
  end-page: 18631
  article-title: Control over brain activation and pain learned by using real‐time functional MRI
  publication-title: PNAS
– volume: 96
  start-page: 237
  year: 2014
  end-page: 244
  article-title: Control of nucleus accumbens activity with neurofeedback
  publication-title: NeuroImage
– volume: 44
  start-page: 857
  year: 2009
  end-page: 869
  article-title: Influence of heart rate on the BOLD signal: The cardiac response function
  publication-title: NeuroImage
– volume: 378
  start-page: 155
  year: 2018
  end-page: 164
  article-title: Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning
  publication-title: Neuroscience
– volume: 143
  start-page: 141
  year: 2016
  end-page: 151
  article-title: Noise contributions to the fMRI signal: An overview
  publication-title: NeuroImage
– volume: 10
  start-page: 91
  year: 1999
  end-page: 106
  article-title: Real‐time fMRI paradigm control, physiology, and behavior combined with near real‐time statistical analysis
  publication-title: NeuroImage
– volume: 56
  start-page: 440
  year: 2011
  end-page: 454
  article-title: Decoding fMRI brain states in real‐time
  publication-title: NeuroImage
– volume: 55
  start-page: 1227
  year: 2006
  end-page: 1235
  article-title: BOLD contrast sensitivity enhancement and artifact reduction with multiecho EPI: Parallel‐acquired inhomogeneity‐desensitized fMRI
  publication-title: Magnetic Resonance in Medicine
– volume: 112
  start-page: 188
  year: 2017
  end-page: 195
  article-title: Volitional regulation of brain responses to food stimuli in overweight and obese subjects: A real‐time fMRI feedback study
  publication-title: Appetite
– year: 2018
  article-title: Motion and physiological noise effects on amygdala real‐time fMRI neurofeedback learning
  publication-title: bioRxiv
– volume: 19
  start-page: 200
  year: 2003
  end-page: 207
  article-title: Modeling regional and psychophysiologic interactions in fMRI: The importance of hemodynamic deconvolution
  publication-title: NeuroImage
– volume: 20
  start-page: 2209
  year: 2003
  end-page: 2224
  article-title: Real‐time independent component analysis of fMRI time‐series
  publication-title: NeuroImage
– volume: 14
  start-page: 344
  year: 2017c
  end-page: 347
  article-title: Real‐time fMRI data for testing OpenNFT functionality
  publication-title: Data in Brief
– volume: 9
  year: 2015
  article-title: FRIEND engine framework: A real time neurofeedback client‐server system for neuroimaging studies
  publication-title: Frontiers in Behavioral Neuroscience
– year: 2000
– volume: 171
  start-page: 234
  year: 2018
  end-page: 245
  article-title: Behavioral interventions for reducing head motion during MRI scans in children
  publication-title: NeuroImage
– volume: 76
  start-page: 386
  year: 2013
  end-page: 399
  article-title: Real‐time fMRI neurofeedback: Progress and challenges
  publication-title: NeuroImage
– volume: 8
  start-page: 341ps12
  year: 2016
  end-page: 341ps12
  article-title: What does research reproducibility mean?
  publication-title: Science Translational Medicine
– volume: 31
  start-page: 1536
  year: 2006
  end-page: 1548
  article-title: Separating respiratory‐variation‐related fluctuations from neuronal‐activity‐related fluctuations in fMRI
  publication-title: NeuroImage
– volume: 146
  start-page: 157
  year: 2017
  end-page: 170
  article-title: The real‐time fMRI neurofeedback based stratification of default network regulation neuroimaging data repository
  publication-title: NeuroImage
– volume: 22
  start-page: 1333
  year: 2012
  end-page: 1338
  article-title: A real‐time fMRI‐based spelling device immediately enabling robust motor‐independent communication
  publication-title: Current Biology
– volume: 115
  year: 2018
  article-title: Ridding fMRI data of motion‐related influences: Removal of signals with distinct spatial and physical bases in multiecho data
  publication-title: PNAS
– volume: 12
  year: 2017
  article-title: fMRI neurofeedback training for increasing anterior cingulate cortex activation in adult attention deficit hyperactivity disorder. An exploratory randomized, single‐blinded study
  publication-title: PLoS One
– volume: 23
  start-page: 194
  year: 2010
  end-page: 198
  article-title: Towards a cure for BCI illiteracy
  publication-title: Brain Topography
– volume: 47
  start-page: 711
  year: 2000
  end-page: 722
  article-title: An integrated functional magnetic resonance imaging procedure for preoperative mapping of cortical areas associated with tactile, motor, language, and visual functions
  publication-title: Neurosurgery
– volume: 185
  start-page: 545
  year: 2019
  end-page: 555
  article-title: A systematic review of the psychological factors that influence neurofeedback learning outcomes
  publication-title: NeuroImage
– volume: 59
  start-page: 478
  year: 2012
  end-page: 489
  article-title: Signal quality and Bayesian signal processing in neurofeedback based on real‐time fMRI
  publication-title: NeuroImage
– volume: 8
  year: 2013
  article-title: On the definition of signal‐to‐noise ratio and contrast‐to‐noise ratio for fMRI data
  publication-title: PLoS One
– year: 2012
– volume: 21
  start-page: 436
  year: 2004
  end-page: 443
  article-title: Learned regulation of spatially localized brain activation using real‐time fMRI
  publication-title: NeuroImage
– volume: 25
  start-page: 35
  year: 2007
  end-page: 46
  article-title: CORSICA: Correction of structured noise in fMRI by automatic identification of ICA components
  publication-title: Magnetic Resonance Imaging
– volume: 48
  start-page: 771
  year: 2002
  end-page: 780
  article-title: Real‐time autoshimming for echo planar timecourse imaging
  publication-title: Magnetic Resonance in Medicine
– volume: 19
  start-page: 422
  year: 2003
  end-page: 429
  article-title: Estimation of general linear model coefficients for real‐time application
  publication-title: NeuroImage
– volume: 9
  year: 2014
  article-title: Windowed correlation: A suitable tool for providing dynamic fMRI‐based functional connectivity neurofeedback on task difficulty
  publication-title: PLoS One
– volume: 27
  start-page: 1552
  year: 2015
  end-page: 1572
  article-title: The inclusion of functional connectivity information into fMRI‐based neurofeedback improves its efficacy in the reduction of cigarette cravings
  publication-title: Journal of Cognitive Neuroscience
– volume: 35
  start-page: 2588
  year: 2015
  end-page: 2595
  article-title: Differential magnetic resonance neurofeedback modulations across extrinsic (visual) and intrinsic (default‐mode) nodes of the human cortex
  publication-title: The Journal of Neuroscience
– year: 2017
– volume: 256
  start-page: 117
  year: 2015
  end-page: 121
  article-title: Real‐time fMRI processing with physiological noise correction—Comparison with off‐line analysis
  publication-title: Journal of Neuroscience Methods
– volume: 12
  year: 2017
  article-title: MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites
  publication-title: PLoS One
– ident: e_1_2_13_63_1
  doi: 10.1016/j.neuroimage.2018.10.021
– ident: e_1_2_13_48_1
  doi: 10.1523/JNEUROSCI.3098-14.2015
– ident: e_1_2_13_92_1
  doi: 10.1371/journal.pcbi.1005681
– ident: e_1_2_13_105_1
  doi: 10.1016/j.neuroimage.2013.08.048
– ident: e_1_2_13_101_1
  doi: 10.1002/(SICI)1522-2594(199907)42:1<87::AID-MRM13>3.0.CO;2-O
– ident: e_1_2_13_22_1
  doi: 10.1073/pnas.0505210102
– ident: e_1_2_13_147_1
  doi: 10.1016/j.neuroimage.2005.02.050
– ident: e_1_2_13_10_1
  doi: 10.1016/S1053-8119(09)72192-5
– ident: e_1_2_13_74_1
  doi: 10.1016/j.neuroimage.2010.06.052
– ident: e_1_2_13_109_1
  doi: 10.1016/j.neuroimage.2018.12.006
– ident: e_1_2_13_2_1
  doi: 10.1002/hbm.23584
– ident: e_1_2_13_111_1
  doi: 10.1002/mrm.27146
– ident: e_1_2_13_57_1
  doi: 10.1016/j.neuroimage.2010.07.060
– ident: e_1_2_13_133_1
  doi: 10.1002/mrm.21136
– start-page: 366138
  year: 2018
  ident: e_1_2_13_51_1
  article-title: Motion and physiological noise effects on amygdala real‐time fMRI neurofeedback learning
  publication-title: bioRxiv
– ident: e_1_2_13_131_1
  doi: 10.1016/j.neuroimage.2005.01.007
– ident: e_1_2_13_142_1
  doi: 10.1016/j.mri.2007.02.007
– ident: e_1_2_13_125_1
  doi: 10.1016/j.appet.2017.01.032
– ident: e_1_2_13_11_1
  doi: 10.1016/j.neuroimage.2012.09.043
– ident: e_1_2_13_150_1
  doi: 10.1002/mrm.20261
– ident: e_1_2_13_13_1
  doi: 10.1093/ntr/ntt122
– volume-title: Prospective acquisition correction for head motion with image‐based trackingfor real‐time fMRI
  year: 2000
  ident: e_1_2_13_129_1
– ident: e_1_2_13_124_1
  doi: 10.1016/j.cub.2012.05.022
– ident: e_1_2_13_81_1
  doi: 10.3389/fnhum.2016.00183
– ident: e_1_2_13_37_1
  doi: 10.1002/1522-2594(200007)44:1<162::AID-MRM23>3.0.CO;2-E
– ident: e_1_2_13_104_1
  doi: 10.1016/j.neuroimage.2011.10.018
– ident: e_1_2_13_122_1
  doi: 10.1002/1522-2594(200102)45:2<289::AID-MRM1038>3.0.CO;2-U
– ident: e_1_2_13_84_1
  doi: 10.1016/j.neuroimage.2016.10.048
– ident: e_1_2_13_121_1
  doi: 10.1016/j.neuroimage.2016.12.024
– ident: e_1_2_13_127_1
  doi: 10.1016/j.neuroimage.2013.03.033
– start-page: 1242
  year: 2016
  ident: e_1_2_13_137_1
  article-title: Real‐time full correlation matrix analysis of fMRI data
  publication-title: IEEE International Conference on Big Data (Big Data), IEEE
– ident: e_1_2_13_31_1
  doi: 10.1002/mrm.1910350312
– ident: e_1_2_13_95_1
  doi: 10.1016/j.mri.2006.09.042
– ident: e_1_2_13_7_1
  doi: 10.3389/fnbeh.2015.00003
– ident: e_1_2_13_38_1
  doi: 10.1126/scitranslmed.aaf5027
– ident: e_1_2_13_152_1
  doi: 10.1371/journal.pone.0085929
– ident: e_1_2_13_33_1
  doi: 10.1002/jmri.20935
– ident: e_1_2_13_12_1
  doi: 10.1016/j.neuroimage.2016.12.018
– ident: e_1_2_13_29_1
  doi: 10.1016/j.neuroimage.2003.08.012
– ident: e_1_2_13_67_1
  doi: 10.1016/j.neuroimage.2017.06.039
– ident: e_1_2_13_59_1
  doi: 10.1016/j.jneumeth.2008.08.013
– volume: 98
  start-page: 357
  year: 2004
  ident: e_1_2_13_143_1
  article-title: Self‐regulation of local brain activity using real‐time functional magnetic resonance imaging (fMRI)
  publication-title: Journal of Physiology
– volume: 27
  start-page: 1193
  year: 2017
  ident: e_1_2_13_69_1
  article-title: Learning control over emotion networks through connectivity‐based neurofeedback
  publication-title: Cerebral Cortex
– ident: e_1_2_13_76_1
  doi: 10.1371/journal.pone.0038115
– ident: e_1_2_13_41_1
  doi: 10.1016/j.neuroimage.2014.03.034
– ident: e_1_2_13_36_1
  doi: 10.1002/mrm.1222
– ident: e_1_2_13_144_1
  doi: 10.1371/journal.pone.0077089
– ident: e_1_2_13_47_1
  doi: 10.1016/j.neuroimage.2012.02.015
– ident: e_1_2_13_115_1
  doi: 10.1371/journal.pbio.1002546
– ident: e_1_2_13_64_1
  doi: 10.1016/j.neuroimage.2006.10.026
– ident: e_1_2_13_116_1
  doi: 10.1126/science.1212003
– ident: e_1_2_13_65_1
  doi: 10.1162/jocn_a_00802
– ident: e_1_2_13_139_1
  doi: 10.1016/j.tics.2017.09.010
– ident: e_1_2_13_49_1
  doi: 10.1523/JNEUROSCI.5911-12.2013
– ident: e_1_2_13_40_1
  doi: 10.1016/j.neuroimage.2014.03.073
– ident: e_1_2_13_77_1
  doi: 10.1016/j.neuroimage.2016.09.008
– ident: e_1_2_13_66_1
  doi: 10.1016/j.neuroimage.2019.02.058
– ident: e_1_2_13_108_1
– ident: e_1_2_13_46_1
  doi: 10.1002/hbm.20997
– ident: e_1_2_13_28_1
  doi: 10.1016/j.neuroimage.2015.09.042
– ident: e_1_2_13_60_1
  doi: 10.1006/nimg.2001.0900
– ident: e_1_2_13_99_1
  doi: 10.1002/1097-0193(200101)12:1<25::AID-HBM30>3.0.CO;2-H
– ident: e_1_2_13_90_1
  doi: 10.1038/nn.4500
– ident: e_1_2_13_146_1
  doi: 10.1093/cercor/bhx177
– ident: e_1_2_13_42_1
  doi: 10.1007/s10548-014-0384-4
– ident: e_1_2_13_93_1
  doi: 10.1146/annurev.biophys.27.1.447
– ident: e_1_2_13_26_1
  doi: 10.1016/j.cmpb.2011.07.007
– ident: e_1_2_13_78_1
  doi: 10.1523/JNEUROSCI.23-10-03963.2003
– ident: e_1_2_13_106_1
  doi: 10.1073/pnas.1720985115
– ident: e_1_2_13_56_1
– ident: e_1_2_13_25_1
  doi: 10.1016/j.neuroimage.2017.08.025
– ident: e_1_2_13_130_1
  doi: 10.1016/j.neuroimage.2017.12.071
– ident: e_1_2_13_135_1
  doi: 10.3389/fninf.2011.00027
– ident: e_1_2_13_89_1
  doi: 10.1016/j.neuroimage.2016.11.052
– ident: e_1_2_13_138_1
  doi: 10.1002/mrm.10259
– ident: e_1_2_13_19_1
  doi: 10.1016/j.tics.2007.08.014
– ident: e_1_2_13_123_1
  doi: 10.1016/j.neuroscience.2016.09.026
– ident: e_1_2_13_110_1
  doi: 10.1016/j.eurpsy.2017.10.011
– ident: e_1_2_13_114_1
  doi: 10.1007/s12021-013-9176-3
– ident: e_1_2_13_8_1
  doi: 10.1016/j.yebeh.2010.08.004
– ident: e_1_2_13_141_1
  doi: 10.1109/TBME.2004.827063
– ident: e_1_2_13_148_1
  doi: 10.1097/00001756-200208070-00005
– ident: e_1_2_13_75_1
  doi: 10.1002/hbm.20326
– ident: e_1_2_13_120_1
  doi: 10.1016/j.neuroimage.2011.06.078
– ident: e_1_2_13_151_1
  doi: 10.1371/journal.pone.0170795
– ident: e_1_2_13_85_1
  doi: 10.1016/j.jneumeth.2015.08.033
– ident: e_1_2_13_5_1
  doi: 10.1016/S1053-8119(03)00081-8
– ident: e_1_2_13_53_1
  doi: 10.1371/journal.pone.0118890
– ident: e_1_2_13_62_1
  doi: 10.1111/j.1552-6569.2010.00529.x
– ident: e_1_2_13_54_1
– ident: e_1_2_13_128_1
  doi: 10.1016/j.neuroimage.2013.05.115
– ident: e_1_2_13_68_1
  doi: 10.1016/j.dib.2017.07.049
– ident: e_1_2_13_79_1
  doi: 10.1002/mrm.24314
– ident: e_1_2_13_132_1
  doi: 10.1016/j.neuroimage.2011.07.044
– ident: e_1_2_13_3_1
  doi: 10.1016/j.neuroscience.2016.12.050
– ident: e_1_2_13_82_1
  doi: 10.1002/1522-2594(200101)45:1<167::AID-MRM1023>3.0.CO;2-M
– ident: e_1_2_13_24_1
  doi: 10.1002/mrm.25770
– ident: e_1_2_13_103_1
  doi: 10.1016/j.neuroimage.2016.08.009
– ident: e_1_2_13_61_1
  doi: 10.1006/nimg.2002.1132
– ident: e_1_2_13_134_1
  doi: 10.1007/s10548-009-0121-6
– ident: e_1_2_13_50_1
  doi: 10.1007/s12529-011-9165-6
– ident: e_1_2_13_136_1
  doi: 10.1006/nimg.1999.0457
– ident: e_1_2_13_80_1
  doi: 10.3389/fnbeh.2015.00341
– ident: e_1_2_13_149_1
  doi: 10.1371/journal.pone.0088785
– ident: e_1_2_13_16_1
  doi: 10.1038/nn.4499
– ident: e_1_2_13_15_1
  doi: 10.1016/j.neuroimage.2008.09.029
– ident: e_1_2_13_18_1
  doi: 10.1002/mrm.1910330213
– ident: e_1_2_13_73_1
  doi: 10.1016/j.neuroimage.2017.03.033
– ident: e_1_2_13_97_1
  doi: 10.1002/mrm.20900
– ident: e_1_2_13_72_1
  doi: 10.1002/mrm.1240
– ident: e_1_2_13_118_1
  doi: 10.1038/nrn.2016.164
– ident: e_1_2_13_55_1
– ident: e_1_2_13_52_1
  doi: 10.1016/j.neuroimage.2017.10.031
– ident: e_1_2_13_27_1
  doi: 10.1016/j.nicl.2016.12.023
– ident: e_1_2_13_23_1
  doi: 10.1016/j.neuroimage.2005.04.039
– ident: e_1_2_13_94_1
  doi: 10.1002/1522-2594(200012)44:6<925::AID-MRM14>3.0.CO;2-M
– ident: e_1_2_13_17_1
  doi: 10.1002/(SICI)1522-2594(199912)42:6<1014::AID-MRM4>3.0.CO;2-F
– ident: e_1_2_13_21_1
  doi: 10.1016/j.neuroimage.2003.08.041
– ident: e_1_2_13_88_1
  doi: 10.1016/j.neuroimage.2006.09.032
– ident: e_1_2_13_39_1
  doi: 10.1016/j.neuroimage.2018.01.023
– ident: e_1_2_13_35_1
  doi: 10.1016/S1053-8119(03)00058-2
– ident: e_1_2_13_43_1
  doi: 10.1016/j.neuroimage.2013.06.010
– ident: e_1_2_13_83_1
  doi: 10.1016/j.neuroimage.2010.12.016
– ident: e_1_2_13_14_1
  doi: 10.1177/1073858411407205
– ident: e_1_2_13_34_1
  doi: 10.1002/(SICI)1522-2594(200002)43:2<259::AID-MRM13>3.0.CO;2-P
– ident: e_1_2_13_20_1
– ident: e_1_2_13_140_1
  doi: 10.1016/j.neuroimage.2004.10.012
– ident: e_1_2_13_30_1
  doi: 10.1371/journal.pone.0184661
– ident: e_1_2_13_113_1
  doi: 10.1002/hbm.21427
– year: 2011
  ident: e_1_2_13_96_1
  article-title: Handbook of Functional MRI Data Analysis [WWW Document]
  publication-title: Cambridge Core
– ident: e_1_2_13_9_1
  doi: 10.1016/j.neuroimage.2006.02.048
– ident: e_1_2_13_87_1
  doi: 10.1016/j.neuroimage.2013.04.001
– ident: e_1_2_13_91_1
  doi: 10.1109/ICIP.1994.413892
– ident: e_1_2_13_145_1
  doi: 10.1093/scan/nsq024
– ident: e_1_2_13_100_1
  doi: 10.1016/S1053-8119(02)00016-2
– ident: e_1_2_13_6_1
  doi: 10.2463/mrms.5.157
– ident: e_1_2_13_44_1
  doi: 10.1002/mrm.1910310307
– ident: e_1_2_13_107_1
  doi: 10.1016/j.neuroimage.2016.09.038
– ident: e_1_2_13_117_1
  doi: 10.1002/hbm.22307
– year: 1998
  ident: e_1_2_13_102_1
  article-title: Single shot T 2*‐sensitive spectroscopic imaging increases fMRI sensitivity: Preliminary evidence from visual and olfactory activation
  publication-title: International Society for Magnetic Resonance in Medicine
– ident: e_1_2_13_58_1
  doi: 10.1097/00006123-200009000-00037
– ident: e_1_2_13_32_1
  doi: 10.1016/j.neuroimage.2013.05.030
– ident: e_1_2_13_45_1
  doi: 10.1016/j.pscychresns.2016.01.016
– ident: e_1_2_13_70_1
  doi: 10.1016/j.neuroimage.2013.05.010
– ident: e_1_2_13_86_1
  doi: 10.1038/s41562-016-0021
– ident: e_1_2_13_4_1
  doi: 10.1371/journal.pone.0027638
– year: 2020
  ident: e_1_2_13_112_1
  publication-title: Brain
– ident: e_1_2_13_119_1
  doi: 10.1016/j.ejrad.2011.09.025
– ident: e_1_2_13_98_1
  doi: 10.1016/j.neuroimage.2012.02.059
– ident: e_1_2_13_126_1
  doi: 10.1016/j.nicl.2014.07.002
– ident: e_1_2_13_71_1
  doi: 10.1016/j.neuroimage.2011.07.076
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Snippet Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF) allows subjects voluntary control of localised and distributed brain...
Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain...
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StartPage 3439
SubjectTerms Biofeedback
Biofeedback training
Brain mapping
Cognition
Control methods
Data retrieval
denoising
Electroencephalography
Feedback
fMRI
Functional magnetic resonance imaging
Functional Neuroimaging - methods
Functional Neuroimaging - standards
Humans
Image Processing, Computer-Assisted - methods
Image Processing, Computer-Assisted - standards
Learning strategies
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Magnetic Resonance Imaging - standards
Mental disorders
neurofeedback
Neurofeedback - methods
Neuroimaging
Noise reduction
quality
Quality Control
real‐time
Reproducibility
Resonance
Review
Signal quality
Software
Title Quality and denoising in real‐time functional magnetic resonance imaging neurofeedback: A methods review
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fhbm.25010
https://www.ncbi.nlm.nih.gov/pubmed/32333624
https://www.proquest.com/docview/2425836213
https://www.proquest.com/docview/2394896234
https://pubmed.ncbi.nlm.nih.gov/PMC7375116
Volume 41
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