Neurofeedback with fMRI: A critical systematic review (Live Document)
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ArticleControl groupAccount for
ROI to regulateCTBCTFLinearCTCBehavioral measureCTB or
CTC Transfer
# of subjectsTested
Full ReferenceLEGEND
Alegria et al., (2017)other brain regionDNRPFC (right inferior gyrus)YDNRYYADHD scalesYNY-S
Y-S (behavior)
Alegria, A. A., Wulff, M., Brinson, H., Barker, G. J., Norman, L. J., Brandeis, D., … Rubia, K. (2017). Real-time fMRI neurofeedback in adolescents with attention deficit hyperactivity disorder. Human Brain Mapping, 38(6), 3190–3209. doi:10.1002/hbm.23584
Compared to baseline
Amano et al., (2016)within subjectsDNRV1, V2 (classifier decoded sub-region)DNRDNRDNRDNRcolor perceptionYYN
Y-S (behavior)
Amano, K., Shibata, K., Kawato, M., Sasaki, Y., & Watanabe, T. (2016). Learning to Associate Orientation with Color in Early Visual Areas by Associative Decoded fMRI Report. Current Biology, 26, 1–6.
Compared to first trial
Auer et al., (2015)no treatmentDNRsomatomotor corticesYDNRDNRYN--Y-SNhealthyY33N
Auer, T., Schweizer, R., & Frahm, J. (2015). Training Efficiency and Transfer Success in an Extended Real-Time Functional MRI Neurofeedback Training of the Somatomotor Cortex of Healthy Subjects. Frontiers in Human Neuroscience, 9(October), 1–14. doi:10.3389/fnhum.2015.00547
Compared to control
Banca et al., (2015)noneDNRvisual (hMT+/V5)YDNRDNRNAN--NNhealthyY20Y
Banca, P., Sousa, T., Catarina Duarte, I., & Castelo-Branco, M. (2015). Visual motion imagery neurofeedback based on the hMT+/V5 complex: evidence for a feedback-specific neural circuit involving neocortical and cerebellar regions. Journal of Neural Engineering, 12(6), 66003. doi:10.1088/1741-2560/12/6/066003
LinearA linear trend
Berman et al., (2013)noneglobalinsula (right anterior)YDNRDNRNAN--Y-USNhealthyY16Y
Berman, B. D., Horovitz, S. G., & Hallett, M. (2013). Modulation of functionally localized right insular cortex activity using real-time fMRI-based neurofeedback. Frontiers in Human Neuroscience, 7, 1–11. doi:10.3389/fnhum.2013.00638
Berman et al., (2012)noneglobalM1 (left)NDNRDNRNAN--Y-USNhealthyY15N
Berman, B. D., Horovitz, S. G., Venkataraman, G., & Hallett, M. (2011). Self-modulation of primary motor cortex activity with motor and motor imagery tasks using real-time fMRI-based neurofeedback. NeuroImage, 59(2), 917–925. doi:10.1016/j.neuroimage.2011.07.035.Self-modulation
Blefari et al., (2015)noneDNRM1 (contralateral)NNDNRNAmotor performanceNNANNhealthyY13N
Blefari, M. L., Sulzer, J., Hepp-Reymond, M.-C., Kollias, S., & Gassert, R. (2015). Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery. Frontiers in Behavioral Neuroscience, 9(February), 18. doi:10.3389/fnbeh.2015.00018
Bray et al., (2007)mental rehearsal scannerothersomatomotor cortex (left)DNRY/NYYreaction timeYDNRNNhealthyY22N
Bray, S., Shimojo, S., & O’Doherty, J. P. (2007). Direct instrumental conditioning of neural activity using functional magnetic resonance imaging-derived reward feedback. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 27(28), 7498–507. doi:10.1523/JNEUROSCI.2118-07.2007
Bruehl et al., (2014)noneDNRamygdala (right)DNRYYNAN--NNhealthyY6N
Bruehl, A. B., Scherpiet, S., Sulzer, J., Staempfli, P., Seifritz, E., Herwig, U., … Herwig, U. (2014). Real-time neurofeedback using functional MRI could improve down-regulation of amygdala activity during emotional stimulation: A proof-of-concept study. Brain Topography, 27(1), 138–148. doi:10.1007/s10548-013-0331-9
Table data
Canterberry et al., (2013)noneDNRACC NNDNRNAcigarette cravingYNANNnicotine addictionY9N
Canterberry, M., Hanlon, C. a., Hartwell, K. J., Li, X., Owens, M., LeMatty, T., et al. (2013). Sustained reduction of nicotine craving with real-time neurofeedback: Exploring the role of severity of dependence. Nicotine and Tobacco Research, 15(12), 2120–2124. doi:10.1093/ntr/ntt122
Caria et al., (2010)other brain region
mental rehearsal scanner
globalinsula (left anterior)YYYYvalence ratings,
arousal ratings
Caria, A., Sitaram, R., Veit, R., Begliomini, C., & Birbaumer, N. (2010). Volitional control of anterior insula activity modulates the response to aversive stimuli. A real-time functional magnetic resonance imaging study. Biological psychiatry, 68, 425–432. doi:10.1016/j.biopsych.2010.04.020
Caria et al., (2007); Lee et al., (2011)other brain region
mental rehearsal scanner
globalinsula (right anterior)DNRYYDNRN--Y-USNhealthyY15Y
Caria, A., Veit, R., Sitaram, R., Lotze, M., Weiskopf, N., Grodd, W., & Birbaumer, N. (2007). Regulation of anterior insular cortex activity using real-time fMRI. NeuroImage, 35(3), 1238–1246. doi:10.1016/j.neuroimage.2007.01.018 ; Lee, S., Ruiz, S., Caria, A., Veit, R., Birbaumer, N., & Sitaram, R. (2011). Detection of Cerebral Reorganization Induced by Real-Time fMRI Feedback Training of Insula Activation. Neurorehabilitation and Neural Repair, 25(3), 259–267.
Yes' for at least one measure AND 'No' for at least one measure; Or, 'Yes' for "learners" and 'No' for "non-learners"
Chiew et al., (2012)sham - other participantDNRM1 (laterality)DNRY/NYYreaction timeNNNNhealthyY18N
Chiew, M., LaConte, S. M., & Graham, S. J. (2012). NeuroImage Investigation of fMRI neurofeedback of differential primary motor cortex activity using kinesthetic motor imagery. NeuroImage, 61(1), 21–31. doi:10.1016/j.neuroimage.2012.02.053
DNRDo not report
Cordes et al., (2015)noneDNRACCYDNRDNRNAaffect, mood--NNschizophreniaY22N
Cordes, J. S., Mathiak, K. A. K., Dyck, M., Alawi, E. M., Gaber, T. J., Zepf, F. D., et al. (2015). Cognitive and neural strategies during control of the anterior cingulate cortex by fMRI neurofeedback in patients with schizophrenia. Frontiers in behavioral neuroscience, 9(June), 169. doi:10.3389/fnbeh.2015.00169
Yes, successful
Cortese et al., (2016, 2017)inverseDNRindividualized (confidence)DNRNNDNRconfidenceYYN
Y-S (behavior)
Cortese, A., Amano, K., Koizumi, A., Kawato, M., & Lau, H. (2016). Multivoxel neurofeedback selectively modulates confidence without changing perceptual performance. Nature Communications, 7, 13669. doi:10.1038/ncomms13669; Cortese, A., Amano, K., Koizumi, A., Lau, H., & Kawato, M. (2017). Decoded fMRI neurofeedback can induce bidirectional confidence changes within single participants. NeuroImage, 149, 323–337. doi:10.1016/j.neuroimage.2017.01.069
Yes, unsuccessful
Debettencourt et al., (2015)sham - other participant
mental rehearsal no scanner
DNRindividualized (face/scene attention)DNRDNRDNRYattentionYYNNhealthyN80N
DeBettencourt, M. T., Cohen, J. D., Lee, R. F., Norman, K. a, Turk-browne, N. B., DeBettencourt, T., et al. (2015). Closed-loop training of attention with real-time brain imaging. Nature Neuroscience, 18(3), 1–9. doi:10.1038/nn.3940
NANot applicable
deCharms et al., (2004)sham - otherglobalsomatomotor cortex (left)YDNRYYN--Y-SNhealthyY9N
DeCharms, R. C., Christoff, K., Glover, G. H., Pauly, J. M., Whitfield, S., & Gabrieli, J. D. . E. (2004). Learned regulation of spatially localized brain activation using real-time fMRI. NeuroImage, 21(1), 436–443. doi:10.1016/j.neuroimage.2003.08.041
Region of interest
deCharms et al., (2005)sham - other participant
other brain region
mental rehearsal no scanner
globalACC (rostral)YYYDNRpain ratingsYYNNchronic painY36N
deCharms, R. C., Maeda, F., Glover, G. H., Ludlow, D., Pauly, J. M., Soneji, D., et al. (2005). Control over brain activation and pain learned by using real-time functional MRI. Proceedings of the National Academy of Sciences of the United States of America, 102(51), 18626–31. doi:10.1073/pnas.0505210102
Functional connectivity
Emmert et al., (2014, 2017a)noneDNRinsula (left anterior), ACCDNRYDNRNApain ratingsYNANNhealthyN28N
Emmert, K., Breimhorst, M., Bauermann, T., Birklein, F., Van De Ville, D., & Haller, S. (2014). Comparison of anterior cingulate vs. insular cortex as targets for real-time fMRI regulation during pain stimulation. Frontiers in behavioral neuroscience, 8(October), 350. doi:10.3389/fnbeh.2014.00350 ; Emmert, K., Breimhorst, M., Bauermann, T., Birklein, F., Rebhorn, C., Van De Ville, D., & Haller, S. (2017). Active pain coping is associated with the response in real-time fMRI neurofeedback during pain. Brain Imaging and Behavior, 11(3), 712–721. doi:10.1007/s11682-016-9547-0
Respiration rate and/or heart rate are statistically tested between conditions
Emmert et al. (2017b)none
regressed out
auditory cortexYNNNAtinnitus scaleYNAN
Y-US (behavior)
Emmert, K., Kopel, R., Koush, Y., Maire, R., Senn, P., Van De Ville, D., & Haller, S. (2017). Continuous vs. intermittent neurofeedback to regulate auditory cortex activity of tinnitus patients using real-time fMRI - A pilot study. NeuroImage: Clinical, 14, 97–104. doi:10.1016/j.nicl.2016.12.023
The percent BOLD change from a large background brain region is subtracted from the percent BOLD change in the ROI
Frank et al., 2012noneDNRinsula (anterior)YDNRDNRNAmoodNNANNobeseY21N
Frank, S., Lee, S., Preissl, H., Schultes, B., Birbaumer, N., & Veit, R. (2012). The obese brain athlete: self-regulation of the anterior insula in adiposity. PloS one, 7(8), e42570. doi:10.1371/journal.pone.0042570
Additional intruments and calclations are used to regress out respiration artifacts
Garrison et al., (2013)noneDNRposterior cingulate cortexYDNRDNRNAN--NNhealthyY44N
Garrison, K. a., Scheinost, D., Worhunsky, P. D., Elwafi, H. M., Thornhill, T. a., Thompson, E., et al. (2013). Real-time fMRI links subjective experience with brain activity during focused attention. NeuroImage, 81, 110–8. doi:10.1016/j.neuroimage.2013.05.030
Greer et al., (2014)mental rehearsal scannerDNRnucleus accumbensYDNRDNRYaffect--Y-USNhealthyY25Y
Greer, S. M., Trujillo, A. J., Glover, G. H., & Knutson, B. (2014). Control of nucleus accumbens activity with neurofeedback. NeuroImage, 96, 237–244. doi:10.1016/j.neuroimage.2014.03.073
posterior cingulate cortex
Groene et al., (2015)noneDNRACC (rostral)YDNRDNRNAaffectYNANNhealthyY24N
Gröne, M., Dyck, M., Koush, Y., Bergert, S., Mathiak, K. A., Alawi, E. M., et al. (2015). Upregulation of the Rostral Anterior Cingulate Cortex can Alter the Perception of Emotions: fMRI-Based Neurofeedback at 3 and 7 T. Brain Topography, 28(2), 197–207. doi:10.1007/s10548-014-0384-4
perfrontal cortex
Guan et al., (2015)other brain regionDNRACC (rostral)YYDNRYpain ratingsYYNNchronic painY14N
Guan, M., Li, L., Tong, L., Zhang, Y., Zheng, D., Yan, B., et al. (2015). Self-regulation of rACC activation in patients with postherpetic neuralgia: A preliminary study using real-time fMRI neurofeedback. PloS one, 10(4), e0123675. doi:10.7910/DVN/27368
primary auditory cortex
Habes et al., (2016)mental rehearsal scanner
regressed out
PPA/FFAYDNRDNRDNRvisual performanceNNNNhealthyY17N
Habes, I., Rushton, S., Johnston, S. J., Sokunbi, M. O., Barawi, K., Brosnan, M., et al. (2016). fMRI neurofeedback of higher visual areas and perceptual biases. Neuropsychologia, 85, 208–215. doi:10.1016/j.neuropsychologia.2016.03.031
secondary auditory cortex
Haller et al., (2010)noneglobalA1DNRYYNAtinnitus--NNtinnitusN6N
Haller, S., Birbaumer, N., & Veit, R. (2010). Real-time fMRI feedback training may improve chronic tinnitus. European Radiology, 20(3), 696–703. doi:10.1007/s00330-009-1595-z
primary visual cortex
Hamilton et al., (2016)sham - other participant
regressed out
individualized (salience network)YDNRDNRNemotionDNRYNNdepressionY20Y
Hamilton, J. P., Glover, G. H., Bagarinao, E., Chang, C., Mackey, S., Sacchet, M. D., & Gotlib, I. H. (2016). Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder. Psychiatry Research: Neuroimaging, 249, 91–96. doi:
primary visual cortex
Hamilton et al., (2011)sham - other participantglobalACC (subgenual)YDNRDNRYN--Y-USNhealthyY17Y
Hamilton, J. P., Glover, G. H., Hsu, J., Johnson, R. F., & Gotlib, I. H. (2011). Modulation of Subgenual Anterior Cingulate Cortex Activity With Real-Time Neurofeedback. Human Brain Mapping, 32(1), 22–31. doi:10.1002/hbm.20997.Modulation
primary motor cortex
Hampson et al., 2011noneDNRSMAYNDNRNA0--NNhealthyY8Y
Hampson, M., Scheinost, D., Qiu, M., Bhawnani, J., Lacadie, C. M., Leckman, J. F., et al. (2011). Biofeedback of real-time functional magnetic resonance imaging data from the supplementary motor area reduces functional connectivity to subcortical regions. Brain connectivity, 1(1), 91–8. doi:10.1089/brain.2011.0002
supplementary motor area
Hanlon et al., (2013)noneDNRACC (ventral), PFC (dorsomedial)YDNRDNRNAcigarette cravingYNANNnicotine addictionY21N
Hanlon, C. a., Hartwell, K. J., Canterberry, M., Li, X., Owens, M., LeMatty, T., et al. (2013). Reduction of cue-induced craving through realtime neurofeedback in nicotine users: The role of region of interest selection and multiple visits. Psychiatry Research - Neuroimaging, 213(1), 79–81. doi:10.1016/j.pscychresns.2013.03.003
premotor cortex
Harmelech et al., (2015)other brain region
Mental rehearsal scanner
DNR5 visual areas, inferior parietal lobuleYDNRDNRYN--NNhealthyY8N
Harmelech, T., Friedman, D., & Malach, R. (2015). Differential Magnetic Resonance Neurofeedback Modulations across Extrinsic (Visual) and Intrinsic (Default-Mode) Nodes of the Human Cortex. Journal of Neuroscience, 35(6), 2588–2595. doi:10.1523/JNEUROSCI.3098-14.2015
ventral tegmental area
Harmelech et al., (2013)noneDNRACC (dorsal)YDNRDNRNAN--NY-S (FC)healthyY20Y
Harmelech, T., Preminger, S., Wertman, E., & Malach, R. (2013). The Day-After Effect: Long Term, Hebbian-Like Restructuring of Resting-State fMRI Patterns Induced by a Single Epoch of Cortical Activation. The Journal of Neuroscience, 33(22), 9488–9497. doi:10.1523/JNEUROSCI.5911-12.2013
parahippocampal place area
Hartwell et al., (2016)mental rehearsal scannerDNRACC, PFC (individualized: craving)DNRDNRDNRYcigarette cravingDNRYNNnicotine addictionY44N
Hartwell, K. J., Hanlon, C. a., Li, X., Borckardt, J. J., Canterberry, M., Prisciandaro, J. J., et al. (2016). Individualized real-time fMRI neurofeedback to attenuate craving in nicotine-dependent smokers. Journal of Psychiatry and Neuroscience, 41(1), 48–55. doi:10.1503/jpn.140200
fusiform face area
Hohenfeld et al., (2017)other brain regionDNRPHCNNDNRNmemoryYDNRNNAlzeimer'sY30Y
Hohenfeld, C., Nellessen, N., Dogan, I., Kuhn, H., Müller, C., Papa, F., et al. (2017). Cognitive improvement and brain changes after real-time functional MRI neurofeedback training in healthy elderly and prodromal Alzheimer’s disease. Frontiers in Neurology, 8(AUG), 1–15. doi:10.3389/fneur.2017.00384
parahippocampal cortex
Hui et al., (2014); Xie et al., (2015)sham - other participantglobalPMC (right)DNRNDNRYmotor performanceYYNNhealthyY28Y
Hui, M., Zhang, H., Ge, R., Yao, L., & Long, Z. (2014). Modulation of functional network with real-time fMRI feedback training of right premotor cortex activity. Neuropsychologia, 62(1), 111–123. doi:10.1016/j.neuropsychologia.2014.07.012; Xie, F., Xu, L., Long, Z., Yao, L., & Wu, X. (2015). Functional connectivity alteration after real-time fMRI motor imagery training through self-regulation of activities of the right premotor cortex. BMC Neuroscience, 16, 1–11. doi:10.1186/s12868-015-0167-1
Johnson et al., (2012)sham - randomizedDNRpremotor cortex (left)DNRDNRDNRY/NN--NNhealthyY13N
Johnson, K. a, Hartwell, K., Lematty, T., Borckardt, J., Morgan, P. S., Govindarajan, K., et al. (2012). Intermittent “Real‐time” fMRI Feedback Is Superior to Continuous Presentation for a Motor Imagery Task: A Pilot Study. Journal of Neuroimaging, 22(1), 58–66. doi:10.1111/j.1552-6569.2010.00529.x.Intermittent
Johnston et al., (2009)noneDNRindividualized (emotion)YYDNRNAaffect, mood--NNhealthyY13N
Johnston, S. J., Boehm, S. G., Healy, D., Goebel, R., & Linden, D. E. J. (2009). Neurofeedback: A promising tool for the self-regulation of emotion networks. NeuroImage, 49(1), 1066–72. doi:10.1016/j.neuroimage.2009.07.056
Johnston et al., (2011)mental rehearsal scannerDNRindividualized (emotion)DNRYDNRYaffect, moodNNNNhealthyN27N
Johnston, S. J., Linden, D. E. J., Healy, D., Goebel, R., Habes, I., & Boehm, S. G. (2011). Upregulation of emotion areas through neurofeedback with a focus on positive mood. Cognitive, affective & behavioral neuroscience, 11(1), 44–51. doi:10.3758/s13415-010-0010-1
Kadosh et al., (2015)noneDNRinsula (right anterior)YNNNAN--NNhealthyY17Y
Kadosh, K. C., Luo, Q., de Burca, C., Sokunbi, M. O., Feng, J., Linden, D. E. J., & Lau, J. Y. F. (2015). Using real-time fMRI to influence differential effective connectivity in the developing emotion regulation network. NeuroImage, 125, 616–626. doi:10.1016/j.neuroimage.2015.09.070
Karch et al., (2015)other brain regionDNRindividualized (craving)YDNRDNRDNRalcohol cravingYDNRNNalcohol addictionN27Y
Karch, S., Keeser, D., Hümmer, S., Paolini, M., Kirsch, V., Karali, T., et al. (2015). Modulation of craving related brain responses using real-time fMRI in patients with alcohol use disorder. PLoS ONE, 10(7), e0133034. doi:10.1371/journal.pone.0133034
Kim et al., (2015)noneotherACC, PFC (medial, orbito),
and FC to PCC and precuneus
DNRYDNRNAcigarette cravingNNANNnicotine addictionN14Y
Kim, D.-Y., Yoo, S.-S., Tegethoff, M., Meinlschmidt, G., Lee, J.-H. H., Meinlshmidt, G., & Lee, J.-H. H. (2015). The Inclusion of Functional Connectivity Information into fMRI-based Neurofeedback Improves Its Efficacy in the. Journal of cognitive neuroscience, 27(8), 1552–72. doi:10.1162/jocn
Kirsch et al., (2016)sham - other participantDNRventral striatumDNRYDNRYalcohol cravingNYY-SNheavy drinkersN33N
Kirsch, M., Gruber, I., Ruf, M., Kiefer, F., & Kirsch, P. (2016). Real-time functional magnetic resonance imaging neurofeedback can reduce striatal cue-reactivity to alcohol stimuli. Addiction Biology, 21(4), 982–992. doi:10.1111/adb.12278
Koizumi et al., (2016)within subjectsDNRindividualized (fear response)YYDNRDNRfear responseYYNNhealthyN7N
Koizumi, A., Amano, K., Cortese, A., Yoshida, W., Seymor, B., Kawato, M., & Lau, H. (2016). Fear extinction without fear : Direct reinforcement of neural activity bypasses the need for conscious exposure. Nature human behaviour, 1(November), 1–7. doi:10.1038/s41562-016-0006
Koush et al., (2017)sham - other participantratePFC (dorsomedial), amygdala (FC)YDNRYYvalence ratingsYYY-SNhealthyY15Y
Koush, Y., Rosa, M. J., Robineau, F., Heinen, K., W Rieger, S., Weiskopf, N., et al. (2013). Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI. NeuroImage, 81(1), 422–30. doi:10.1016/j.neuroimage.2013.05.010
Koush et al., (2013)noneratevisual, parietal (FC)YDNRNNAN--NNhealthyY17Y
Koush, Y., Meskaldji, D.-E., Pichon, S., Rey, G., Rieger, S. W., Linden, D. E. J., et al. (2017). Learning Control Over Emotion Networks Through Connectivity-Based Neurofeedback. Cerebral Cortex, 27(2), 1193–1202. doi:10.1093/cercor/bhv311
Lawrence et al., (2014)other brain regionglobalinsula (right anterior)DNRDNRYYvalence ratings,
arousal ratings
Lawrence, E. J., Su, L., Barker, G. J., Medford, N., Dalton, J. J., Williams, S. C. R., et al. (2014). Self-regulation of the anterior insula: Reinforcement learning using real-time fMRI neurofeedback. NeuroImage, 88(1), 113–124. doi:10.1016/j.neuroimage.2013.10.069
Li et al., (2012)noneDNRACC, PFC (medial) YDNRDNRNAcigarette cravingYNANNnicotine addictionY10N
Li, X., Hartwell, K. J., Borckardt, J., Prisciandaro, J. J., Saladin, M. E., Morgan, P. S., et al. (2012). Volitional reduction of anterior cingulate cortex activity produces decreased cue craving in smoking cessation: a preliminary real-time fMRI study. Addiction biology, 1–10.
Li et al., (2016a, 2016b)mental rehearsal scannerglobalindividualized (emotion)DNRYDNRDNRaffectNNNNhealthyY23Y
Li, Z., Tong, L., Wang, L., Li, Y., He, W., Guan, M., & Yan, B. (2016). Self-regulating positive emotion networks by feedback of multiple emotional brain states using real-time fMRI. Experimental Brain Research, 234(12), 3575–3586. doi:10.1007/s00221-016-4744-z ; Li, Z., Tong, L., Guan, M., He, W., Wang, L., Bu, H., et al. (2016). Altered Resting-State Amygdala Functional Connectivity after Real-Time fMRI Emotion Self-Regulation Training. BioMed Research International, 2016. doi:10.1155/2016/2719895
Linden et al., (2012)mental rehearsal no scannerDNRindividualized (emotion)DNRYYDNRmoodYYNNdepressionY16N
Linden, D. E. J., Habes, I., Johnston, S. J., Linden, S., Tatineni, R., Subramanian, L., et al. (2012). Real-time self-regulation of emotion networks in patients with depression. PLoS ONE, 7(6), e38115. doi:10.1371/journal.pone.0038115
MacInnes et al., (2016)sham - randomized
other brain region
mental rehearsal scanner
regressed out
MacInnes, J. J., Dickerson, K. C., Chen, N. kuei, & Adcock, R. A. (2016). Cognitive Neurostimulation: Learning to Volitionally Sustain Ventral Tegmental Area Activation. Neuron, 89(6), 1331–1342. doi:10.1016/j.neuron.2016.02.002
Marins et al., (2015)mental rehearsal scannerDNRpremotor cortex (left)DNRYDNRYN--NNhealthyY28N
Marins, T., Rodrigues, E., Engel, A., Hoefle, S., Basílio, R., Lent, R., et al. (2015). Enhancing Motor Network Activity Using Real-Time Functional MRI Neurofeedback of Left Premotor Cortex. Frontiers in Behavioral Neuroscience, 9(December), 1–12. doi:doi: 10.3389/fnbeh.2015.00341
Marxen et al., (2016)nonerateamygdala (bilateral)NDNRDNRNAN--Y-SNhealthyN32N
Marxen, M., Jacob, M. J., Müller, D. K., Posse, S., Ackley, E., Hellrung, L., et al. (2016). Amygdala Regulation Following fMRI-Neurofeedback without Instructed Strategies. Frontiers in Human Neuroscience, 10(April), 1–14. doi:10.3389/fnhum.2016.00183
Mathiak et al., (2015)noneDNRACC (dorsal)YDNRYNAaffect, reaction timeYNAY-SNhealthyY24N
Mathiak, K. A., Alawi, E. M., Koush, Y., Dyck, M., Cordes, J. S., Gaber, T. J., et al. (2015). Social reward improves the voluntary control over localized brain activity in fMRI-based neurofeedback training. Frontiers in behavioral neuroscience, 9(June), 136. doi:10.3389/fnbeh.2015.00136
McCaig et al., 2011sham - other participant
mental rehearsal scanner
DNRPFC (rostrolateral)DNRYDNRY0--NNhealthyY30N
McCaig, R. G., Dixon, M., Keramatian, K., Liu, I., & Christoff, K. (2011). Improved modulation of rostrolateral prefrontal cortex using real-time fMRI training and meta-cognitive awareness. NeuroImage, 55(3), 1298–305. doi:10.1016/j.neuroimage.2010.12.016
Megumi et al., (2015)sham - other participant
mental rehearsal scanner
DNRM1 (left), lateral parietal cortex (left) (FC)DNRDNRDNRYN--NY-S (FC)healthyY33Y
Megumi, F., Yamashita, a, Kawato, M., Imamizu, H., Fukuda, M., Mitsuo, K., & Hiroshi, I. (2015). Functional MRI neurofeedback training on connectivity induces long-lasting changes in intrinsic functional network. Frontiers in Human Neuroscience, 9(March), Article 160. doi:10.3389/fnhum.2015.00160
Moll et al., (2014)mental rehearsal scannerDNRindividualized (tenderness/pride)DNRYDNRYemotionNNNNhealthyY25N
Moll, J., Weingartner, J. H., Bado, P., Basilio, R., Sato, J. R., Melo, B. R., et al. (2014). Voluntary enhancement of neural signatures of affiliative emotion using fMRI neurofeedback. PLoS ONE, 9(5), 1–11. doi:10.1371/journal.pone.0097343
Nicholson et al., (2017)noneDNRamygdalaYNNNAN--Y-SNPTSDN10Y
Nicholson, A. A., Rabellino, D., Densmore, M., Frewen, P. A., Paret, C., Kluetsch, R., et al. (2017). The neurobiology of emotion regulation in posttraumatic stress disorder: Amygdala downregulation via real-time fMRI neurofeedback. Human Brain Mapping, 38(1), 541–560. doi:10.1002/hbm.23402
Paret et al., (2014, 2016a)other brain regionDNRamygdalaNDNRNNvalence ratings,
arousal ratings
Paret, C., Kluetsch, R., Ruf, M., Demirakca, T., Hoesterey, S., Ende, G., & Schmahl, C. (2014). Down-regulation of amygdala activation with real-time fMRI neurofeedback in a healthy female sample. Frontiers in behavioral neuroscience, 8(September), 299. doi:10.3389/fnbeh.2014.00299 ; Paret, C., Ruf, M., Gerchen, M. F., Kluetsch, R., Demirakca, T., Jungkunz, M., et al. (2016). FMRI neurofeedback of amygdala response to aversive stimuli enhances prefrontal-limbic brain connectivity. NeuroImage, 125, 182–188. doi:10.1016/j.neuroimage.2015.10.027
Paret et al., (2016b)noneDNRamygdalaYNNNAemotional awareness,
valence ratings
YNAY-USNborderline personality disorderN8Y
Paret, C., Kluetsch, R., Zaehringer, J., Ruf, M., Demirakca, T., Bohus, M., et al. (2016). Alterations of amygdala-prefrontal connectivity with real-time fMRI neurofeedback in BPD patients. Social Cognitive and Affective Neuroscience, 11(6), 952–960. doi:10.1093/scan/nsw016
Perronnet et al., (2017)noneDNRM1 (left)YNDNRNAN--Y-USNhealthyY10N
Perronnet, L., Lécuyer, A., Mano, M., Bannier, E., Lotte, F., Clerc, M., & Barillot, C. (2017). Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task. Frontiers in Human Neuroscience, 11(April), 193. doi:10.3389/FNHUM.2017.00193
Ramot et al., (2016)inverseDNRPPA/FFAY/NNDNRDNRN--NNhealthyN16Y
Ramot, M., Grossman, S., Friedman, D., & Malach, R. (2016). Covert neurofeedback without awareness shapes cortical network spontaneous connectivity. Proceedings of the National Academy of Sciences of the United States of America, 113(17), E2413–2420. doi:10.1073/pnas.1516857113
Rance et al., (2014a)noneDNRACC (rostral) / insula (left posterior)YYDNRNApain ratingsNNANNhealthyN10N
Rance, M., Ruttorf, M., Nees, F., Schad, L. R., & Flor, H. (2014). Neurofeedback of the difference in activation of the anterior cingulate cortex and posterior insular cortex. Frontiers in behavioral neuroscience, 35(12), 5784–5798. doi:10.1002/hbm.22585
Rance et al., (2014b)noneDNRACC (rostral), insula (left posterior)YYDNRNApain ratingsNNANNhealthyN10N
Rance, M., Ruttorf, M., Nees, F., Schad, L. R., Flor, H., Rudi Schad, L., & Flor, H. (2014). Real time fMRI feedback of the anterior cingulate and posterior insular cortex in the processing of pain. Human Brain Mapping, 35(12), 5784–5798. doi:10.1002/hbm.22585
Robineau et al., (2014, 2017a)noneratevisual (left/right)Y/NY/NY/NNAvisual extinctionNNAY-SNhealthyY14N
Robineau, F., Rieger, S. W., Mermoud, C., Pichon, S., Koush, Y., Van De Ville, D., et al. (2014). Self-regulation of inter-hemispheric visual cortex balance through real-time fMRI neurofeedback training. NeuroImage, 100, 1–14. doi:10.1016/j.neuroimage.2014.05.072 ; Robineau, F., Meskaldji, D. E. D. E., Koush, Y., Rieger, S. W. S. W. S. W., Mermoud, C., Morgenthaler, S., et al. (2017). Maintenance of Voluntary Self-regulation Learned through Real-Time fMRI Neurofeedback. Frontiers in Human Neuroscience, 11(March), 1–8. doi:10.3389/fnhum.2017.00131
Robineau et al., (2017b)noneDNRV1YYDNRNAvisual neglect testsYNANNhemineglectY9N
Robineau, F., Saj, A., Neveu, R., Van De Ville, D., Scharnowski, F., & Vuilleumier, P. (2017). Using real-time fMRI neurofeedback to restore right occipital cortex activity in patients with left visuo-spatial neglect: proof-of-principle and preliminary results. Neuropsychological Rehabilitation, 0(0), 1–22. doi:10.1080/09602011.2017.1301262
Rota et al., (2009, 2011)other brain regionglobalinferior frontal gyrus (right)DNRYYDNRprosody identificationYDNRNNhealthyY12Y
Rota, G., Sitaram, R., Veit, R., Erb, M., Weiskopf, N., Dogil, G., & Birbaumer, N. (2009). Self-regulation of regional cortical activity using real-time fMRI: the right inferior frontal gyrus and linguistic processing. Human brain mapping, 30(5), 1605–14. doi:10.1002/hbm.20621 ; Rota, G., Handjaras, G., Sitaram, R., Birbaumer, N., & Dogil, G. (2011). Reorganization of functional and effective connectivity during real-time fMRI-BCI modulation of prosody processing. Brain and language, 117(3), 123–32. doi:10.1016/j.bandl.2010.07.008
Ruiz et al., (2013)noneglobalinsula (bilateral anterior)YYYNAfacial recognitionYNAY-USNschizophreniaY9Y
Ruiz, S., Buyukturkoglu, K., Rana, M., Birbaumer, N., & Sitaram, R. (2013). Real-time fMRI brain computer interfaces: Self-regulation of single brain regions to networks. Biological psychology. doi:10.1016/j.biopsycho.2013.04.010
Sarkheil et al., (2015)mental rehearsal scannerDNRPFC (left lateral)DNRDNRDNRNaffect DNRNNNhealthyY14Y
Sarkheil, P., Zilverstand, A., Kilian-Hütten, N., Schneider, F., Goebel, R., & Mathiak, K. (2015). fMRI feedback enhances emotion regulation as evidenced by a reduced amygdala response. Behavioural Brain Research, 281(0), 326–332. doi:10.1016/j.bbr.2014.11.027
Scharnowski et al., (2012, 2014)other brain regionrateretinotopic visual cortexY/NDNRDNRY/Nvisual detectionYDNRY-SNhealthyY16Y
Scharnowski, F., Hutton, C., Josephs, O., Weiskopf, N., & Rees, G. (2012). Improving Visual Perception through Neurofeedback. The Journal of neuroscience, 32(49), 17830–41. doi:10.1523/JNEUROSCI.6334-11.2012 ; Scharnowski, F., Rosa, M. J., Golestani, N., Hutton, C., Josephs, O., Weiskopf, N., & Rees, G. (2014). Connectivity changes underlying neurofeedback training of visual cortex activity. PLoS ONE, 9(3). doi:10.1371/journal.pone.0091090
Scharnowski et al., (2015)inverseDNRSMA/PHCYDNRYYN--Y-SY-S (ROI)healthyY7Y
Scharnowski, F., Veit, R., Zopf, R., Studer, P., Bock, S., Diedrichsen, J., et al. (2015). Manipulating motor performance and memory through real-time fMRI neurofeedback. Biological Psychology, 108, 85–97. doi:10.1016/j.biopsycho.2015.03.009
Scheinost et al., (2013); Radua et al., (2016)sham - other participantDNRPFC (orbito)YDNRDNRNanxietyYYY-S
Y-S (behavior)
Scheinost, D., Stoica, T., Saksa, J., Papademetris, X., Constable, R. T., Pittenger, C., & Hampson, M. (2013). Orbitofrontal cortex neurofeedback produces lasting changes in contamination anxiety and resting-state connectivity. Translational psychiatry, 3(4), e250. doi:10.1038/tp.2013.24 ; Radua, J., Stoica, T., Scheinost, D., Pittenger, C., & Hampson, M. (2016). Neural correlates of success and failure signals during neurofeedback learning. Neuroscience. doi:10.1016/j.neuroscience.2016.04.003
Sepulveda et al., (2016)noneglobalSMAYY/NDNRNAN--Y-SNhealthyY/N20Y
Sepulveda, P., Sitaram, R., Rana, M., Montalba, C., Tejos, C., & Ruiz, S. (2016). How feedback, motor imagery, and reward influence brain self-regulation using real-time fMRI. Human Brain Mapping, 37(9), 3153–3171. doi:10.1002/hbm.23228
Sherwood et al., (2016a, 2016b)mental rehearsal no scannerDNRPFC (left dorsolateral)YDNRYDNRworking memoryYYNNhealthyY18N
Sherwood, M. S., Kane, J. H., Weisend, M. P., & Parker, J. G. (2016). Enhanced control of dorsolateral prefrontal cortex neurophysiology with real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback training and working memory practice. NeuroImage, 124, 214–223. doi:10.1016/j.neuroimage.2015.08.074 ; Sherwood, M. S., Weisend, M. P., Kane, J. H., & Parker, J. G. (2016). Combining Real-Time fMRI Neurofeedback Training of the DLPFC with N-Back Practice Results in Neuroplastic Effects Confined to the Neurofeedback Target Region . Frontiers in Behavioral Neuroscience , 10 (June), 1–9. doi:10.3389/fnbeh.2016.00138
Shibata et al., (2016)inverse
no treatment
DNRcingulate cortexYDNRDNRDNRfacial preferenceYYNNhealthyN33N
Shibata, K., Watanabe, T., Kawato, M., & Sasaki, Y. (2016). Differential Activation Patterns in the Same Brain Region Led to Opposite Emotional States. PLOS Biology, 14(9), e1002546. doi:10.1371/journal.pbio.1002546
Shibata et al., (2011)within subjects
no treatment
DNRV1, V2YDNRDNRDNRvisual discriminationYYNNhealthyN16N
Shibata, K., Watanabe, T., Sasaki, Y., & Kawato, M. (2011). Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation. Science (New York, N.Y.), 334(6061), 1413–5. doi:10.1126/science.1212003
Sokunbi et al., (2014); Ihssen et al., (2017)noneDNRindividualized (food craving)YDNRDNRNAhungerYNANNhealthyY10N
Sokunbi, M. O., Linden, D. E. J., Habes, I., Johnston, S. J., & Ihssen, N. (2014). Real-time fMRI brain-computer interface: development of a “motivational feedback” subsystem for the regulation of visual cue reactivity. Frontiers in behavioral neuroscience, 8(NOV), 392. doi:10.3389/fnbeh.2014.00392 ; Ihssen, N., Sokunbi, M. O., Lawrence, A. D., Lawrence, N. S., & Linden, D. E. J. (2017). Neurofeedback of visual food cue reactivity: a potential avenue to alter incentive sensitization and craving. Brain Imaging and Behavior, 11(3), 915–924. doi:10.1007/s11682-016-9558-x
Sorger et al., (2016)mental rehearsal scannerrateindividualized (mental task)YDNRDNRYN--NNY10N
Sorger, B., Kamp, T., Weiskopf, N., Peters, J. C., & Goebel, R. (2016). When the brain takes “BOLD” steps: Real-time fMRI neurofeedback can further enhance the ability to gradually self-regulate regional brain activation. Neuroscience. doi:10.1016/j.neuroscience.2016.09.026
Sousa et al., (2016)noneDNRvisual (hMT+/V5)YDNRDNRNAN--Y-SNhealthyY20N
Sousa, T., Direito, B., Lima, J., Ferreira, C., Nunes, U., & Castelo-Branco, M. (2016). Control of Brain Activity in hMT+/V5 at Three Response Levels Using fMRI-Based Neurofeedback/BCI. Plos One, 11(5), e0155961. doi:10.1371/journal.pone.0155961
Spetter et al., (2017)noneDNRPFC (dorsolateral), PFC (ventromedial) (FC)YYNNAhungerYNANNobesityY8Y
Spetter, M. S., Malekshahi, R., Birbaumer, N., Lührs, M., van der Veer, A. H., Scheffler, K., et al. (2017). Volitional regulation of brain responses to food stimuli in overweight and obese subjects: A real-time fMRI feedback study. Appetite, 112, 188–195. doi:10.1016/j.appet.2017.01.032
Subramanian et al., (2011)mental rehearsal scannerDNRSMAYDNRDNRDNRmotor performanceYDNRN
Y-S (behavior)
Parkinson's diseaseY10N
Subramanian, L., Hindle, J. V., Johnston, S. J., Roberts, M. V., Husain, M., Goebel, R., & Linden, D. (2011). Real-Time Functional Magnetic Resonance Imaging Neurofeedback for Treatment of Parkinson’s Disease. The Journal of Neuroscience, 31(45), 16309–16317. doi:10.1523/JNEUROSCI.3498-11.2011
Subramanian et al., (2016)motor therapy alone
regressed out
SMAYDNRNDNRmotor performanceYNY-SNParkinson's diseaseY30N
Subramanian, L., Morris, M. B., Brosnan, M., Turner, D. L., Morris, H. R., & Linden, D. E. J. (2016). Functional Magnetic Resonance Imaging Neurofeedback-guided Motor Imagery Training and Motor Training for Parkinson’s Disease: Randomized Trial. Frontiers in Behavioral Neuroscience, 10(June), 111. doi:10.3389/fnbeh.2016.00111
Sulzer et al., (2013)inverse
regressed out
substantia nigra, VTAYYDNRYN--Y-USNhealthyY32Y
Sulzer, J., Sitaram, R., Blefari, M. L., Kollias, S., Birbaumer, N., Stephan, K. E., et al. (2013). Neurofeedback-mediated self-regulation of the dopaminergic midbrain. NeuroImage, 83(1), 817–25. doi:10.1016/j.neuroimage.2013.05.115
Van De Ville et al, (2012)
Haller et al., (2013)
noneDNRA1 (right)DNRDNRYNAN--NY-S (FC)healthyN12Y
Van De Ville, D., Jhooti, P., Haas, T., Kopel, R., Lovblad, K.-O. O., Scheffler, K., & Haller, S. (2012). Recovery of the default mode network after demanding neurofeedback training occurs in spatio-temporally segregated subnetworks. NeuroImage, 63(4), 1775–81. doi:10.1016/j.neuroimage.2012.08.061 ; Haller, S., Kopel, R., Jhooti, P., Haas, T., Scharnowski, F., Lovblad, K. O., et al. (2013). Dynamic reconfiguration of human brain functional networks through neurofeedback. NeuroImage, 81, 243–252. doi:10.1016/j.neuroimage.2013.05.019
Veit et al., 2012noneDNRinsula (anterior)YNYNA0--NNhealthyY11Y
Veit, R., Singh, V., Sitaram, R., Caria, A., Rauss, K., & Birbaumer, N. (2012). Using real-time fMRI to learn voluntary regulation of the anterior insula in the presence of threat-related stimuli. Social cognitive and affective neuroscience, 7(6), 623–34. doi:10.1093/scan/nsr061
Yamashita et al., (2017)inverseglobalM1, lateral parietal coretx (FC)YDNRDNRYreaction timeYYNNhealthyY30Y
Yamashita, A., Hayasaka, S., Kawato, M., & Imamizu, H. (2017). Connectivity Neurofeedback Training Can Differentially Change Functional Connectivity and Cognitive Performance. Cerebral Cortex, 27(10), 4960–4970. doi:10.1093/cercor/bhx177
Yao et al., (2016)other brain regionglobalinsula (left anterior)DNRYYYpain empathyYYY-S
Y-S (ROI ), Y-US (behavior, FC)
Yao, S., Becker, B., Geng, Y., Zhao, Z., Xu, X., Zhao, W., et al. (2016). Voluntary control of anterior insula and its functional connections is feedback-independent and increases pain empathy. NeuroImage, 130, 230–240. doi:10.1016/j.neuroimage.2016.02.035
Yoo et al., (2008)sham - randomizedDNRM1 (left)YDNRDNRYN--Y-SY-S (ROI)healthyY24N
Yoo, S.-S., Lee, J.-H., O’Leary, H., Panych, L. P., & Jolesz, F. A. (2008). Neurofeedback fMRI-mediated learning and consolidation of regional brain activation during motor imagery. International journal of imaging systems and technology, 18(1), 69–78. doi:10.1002/ima.20139
Yoo et al., (2006)mental rehearsal scannerDNRA1 (left), A2 (left)YDNRDNRDNRN--NNhealthyY22N
Yoo, S.-S., O’Leary, H. M., Fairneny, T., Chen, N.-K., Panych, L. P., Park, H., & Jolesz, F. a. (2006). Increasing cortical activity in auditory areas through neurofeedback functional magnetic resonance imaging. Neuroreport, 17(12), 1273–1278. doi:10.1097/01.wnr.0000227996.53540.22
Yoo et al., (2007), Lee et al., (2012)sham - randomizedDNRA1, A2YDNRDNRYN--Y-S
Yoo, S.-S., Lee, J.-H., O’Leary, H., Lee, V., Choo, S.-E., & Jolesz, F. a. (2007). Functional magnetic resonance imaging-mediated learning of increased activity in auditory areas. Neuroreport, 18(18), 1915–1920. doi:10.1097/WNR.0b013e328350a601 ; Lee, J.-H., Kim, J., & Yoo, S.-S. (2012). Real-time fMRI-based neurofeedback reinforces causality of attention networks. Neuroscience Research, 72(4), 347–354. doi:10.1016/j.neures.2012.01.002
Young et al., (2017a, 2017b)other brain regionglobalamygdalaYDNRDNRYautobiographical memory
Y-S (behavior)
Young, K. D., Misaki, M., Harmer, C. J., Victor, T., Zotev, V., Phillips, R., et al. (2017). Real-Time Functional Magnetic Resonance Imaging Amygdala Neurofeedback Changes Positive Information Processing in Major Depressive Disorder. Biological Psychiatry, (23), 1–9. doi:10.1016/j.biopsych.2017.03.013 ; Young, K. D., Siegle, G. J., Zotev, V., Phillips, R., Misaki, M., Yuan, H., et al. (2017). Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall. American Journal of Psychiatry, (20), appi.ajp.2017.1. doi:10.1176/appi.ajp.2017.16060637
Young et al., (2014), Yuan et al., (2014), Zotev et al., (2016)other brain region
regressed out
amygdala (left)YDNRYYmoodYYY-S
Y-S (FC, behavior)
Young, K. D., Zotev, V., Phillips, R., Misaki, M., Yuan, H., Drevets, W. C., & Bodurka, J. (2014). Real-time FMRI neurofeedback training of amygdala activity in patients with major depressive disorder. PLoS ONE, 9(2), e88785. doi:10.1371/journal.pone.0088785 ; Yuan, H., Young, K. D., Phillips, R., Zotev, V., Misaki, M., & Bodurka, J. (2014). Resting-state functional connectivity modulation and sustained changes after real-time functional magnetic resonance imaging neurofeedback training in depression. Brain connectivity, 4(9), 690–701. doi:10.1089/brain.2014.0262 ; Zotev, V., Yuan, H., Misaki, M., Phillips, R., Young, K. D., Feldner, M. T., & Bodurka, J. (2016). Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression. NeuroImage: Clinical, 11(18), 224–238. doi:10.1016/j.nicl.2016.02.003
Zhang et al., (2016, 2013)sham - other participantglobalPFC (dorsolateral)DNRYYYworking memoryYYNNhealthyY30Y
Zhang, G., Yao, L. L., & Zhao, X. (2016). Neural Effect of Real Time fMRI Based Working Memory Neurofeedback Training on the Cortico-Subcortico-Cerebellar Circuit. Journal of Medical Imaging and Health Informatics, 6(5), 1324–1329. doi:10.1166/jmihi.2016.1921 ; Zhang, G., Yao, L., Zhang, H., Long, Z., & Zhao, X. (2013). Improved working memory performance through self-regulation of dorsal lateral prefrontal cortex activation using real-time fMRI. PloS one, 8(8), e73735. doi:10.1371/journal.pone.0073735
Zhang et al., (2013)mental rehearsal scannerDNRPCCDNRNDNRYN--NNhealthyY32N
Zhang, G., Zhang, H., Li, X., Zhao, X., Yao, L., & Long, Z. (2013). Functional alteration of the DMN by learned regulation of the PCC using real-time fMRI. IEEE transactions on neural systems and rehabilitation engineering, 21(4), 595–606. doi:10.1109/TNSRE.2012.2221480
Zhao et al., 2013sham - other participantglobalPMC (dorsal, ipsilateral)DNRNNYfinger tappingYYNNhealthyY24N
Zhao, X., Zhang, H., Song, S., Ye, Q., Guo, J., & Yao, L. (2013). Causal interaction following the alteration of target region activation during motor imagery training using real-time fMRI. Frontiers in Human Neuroscience, 7(December), 1–8. doi:10.3389/fnhum.2013.00866
Zilverstand et al., (2015)mental rehearsal scannerrateinsula (right)YDNRYYanxietyNYN
Y-S (behavior)
Zilverstand, A., Sorger, B., Sarkheil, P., & Goebel, R. (2015). fMRI neurofeedback facilitates anxiety regulation in females with spider phobia. Frontiers in behavioral neuroscience, 9(June), 148. doi:10.3389/fnbeh.2015.00148
Zilverstand et al., (2017)mental rehearsal scannerDNRACCDNRDNRNNattentional tasksYNY-US
Y-S (behavior)
Zilverstand, A., Sorger, B., Slaats-Willemse, D., Kan, C. C., Goebel, R., & Buitelaar, J. K. (2017). fMRI neurofeedback training for increasing anterior cingulate cortex activation in adult attention deficit hyperactivity disorder. An exploratory randomized, single-blinded study. PLoS ONE, 12(1), 1–23. doi:10.1371/journal.pone.0170795
Zotev et al., (2011)other brain region
regressed out
amygdala (left)DNRDNRYYidentifying feelings--Y-SNhealthyY28Y
Zotev, V., Krueger, F., Phillips, R., Alvarez, R. P., Simmons, W. K., Bellgowan, P., et al. (2011). Self-regulation of amygdala activation using real-time FMRI neurofeedback. PLoS ONE, 6(9), e24522. doi:10.1371/journal.pone.0024522
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