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  • 🚨  Rance, M., Walsh, C., Sukhodolsky, D. G., Pittman, B., Qiu, M., Kichuk, S. A., … others. (2018). Time course of clinical change following neurofeedback. NeuroImage.
  • 🚨  Zhang, S., Yoshida, W., Mano, H., Yanagisawa, T., Shibata, K., Kawato, M., and Seymour, B. (2018). Endogenous controllability of closed-loop brain-machine interfaces for pain. BioRxiv, 369736.
  • 🚨  Hellrung, L., Borchardt, V., Gotting, F. N., Stadler, J., Tempelmann, C., Tobler, P., … Meer, J. van der. (2018). Motion and physiological noise effects on amygdala real-time fMRI neurofeedback learning. BioRxiv, 366138.
  • 🚨  Torner, J., Skouras, S., Gispert, J. D., Molinuevo, J. L., and Alpiste, F. (2018). Multipurpose virtual reality environment for biomedical and health applications. BioRxiv, 366302.
  • 🚨  deBettencourt, M. T., Turk-Browne, N. B., and Norman, K. A. (2018). Neurofeedback helps to reveal a relationship between context reinstatement and memory retrieval. BioRxiv, 355727.
  • 🚨  Ramot, M., and Gonzalez-Castillo, J. (2018). A framework for offline evaluation and optimization of real-time algorithms for use in neurofeedback, demonstrated on an instantaneous proxy for correlations. BioRxiv, 351072.
  • 🚨  Zich, C., Haller, S. P. W., Luehrs, M., Lisk, S., Lau, J. Y. F., and Kadosh, K. C. (2018). Modulatory effects of dynamic fMRI-based neurofeedback on emotion regulation networks during adolescence. BioRxiv, 347971.
  • 🚨  Skouras, S., and Scharnowski, F. (2018). The effects of psychiatric history and age on self-regulation of the default mode network. BioRxiv, 342220.
  • 🚨  Kirschner, M., Sladky, R., Haugg, A., Staempfli, P., Jehli, E., Hodel, M., … Herdener, M. (2018). Self-regulation of the Dopaminergic Reward Circuit in Cocaine Users with Mental Imagery and Neurofeedback. BioRxiv, 321166.
  • 🚨  Zhao, Z., Yao, S., Li, K., Sindermann, C., Zhou, F., Zhao, W., … Becker, B. (2018). Real-time functional connectivity-based neurofeedback of amygdala-frontal pathways reduces anxiety. BioRxiv, 308924.
  • 🚨  Kaas, A. L., Valente, G., Goebel, R., and Sorger, B. (2018). Somatosensory imagery induces topographically specific activation patterns instrumental to fMRI-based Brain Computer Interfacing. BioRxiv, 296640.
  • Thibault, R. T., MacPherson, A., Lifshitz, M., Roth, R. R., and Raz, A. (2018). Neurofeedback with fMRI: A critical systematic review. NeuroImage, 172, 786–807.
  • Papoutisi, M., Weiskopf, N., Langbehn, D., Reilmann, R., Rees, G., and Tabrizi, S. J. (2018). Stimulating neural plasticity with real‐time fMRI neurofeedback in Huntington’s disease: A proof of concept study. Human Brain Mapping.
  • MacDuffie, K. E., MacInnes, J., Dickerson, K. C., Eddington, K. M., Strauman, T. J., and Adcock, R. A. (2018). Single session real-time fMRI neurofeedback has a lasting impact on cognitive behavioral therapy strategies. NeuroImage: Clinical.
  • Christian, P., Jenny, Z., Matthias, R., Fungisai, G. M., Stephanie, M., Talma, H., … Gabriele, E. (2018). Monitoring and control of amygdala neurofeedback involves distributed information processing in the human brain. Human Brain Mapping.
  • 🚨  Li, Z., Zhang, C.-Y., Huang, J., Wang, Y., Yan, C., Li, K., … Chan, R. C. K. (2018). Improving motivation through real-time fMRI-based self-regulation of the nucleus accumbens. Neuropsychology.
  • 🚨  Zotev, V., Phillips, R., Misaki, M., Wong, C. K., Wurfel, B. E., Krueger, F., … Bodurka, J. (2018). Real-time fMRI neurofeedback training of the amygdala activity with simultaneous EEG in veterans with combat-related PTSD. NeuroImage: Clinical, 19, 106–121.
  • 🚨  Nicholson, A. A., Rabellino, D., Densmore, M., Frewen, P. A., Paret, C., Kluetsch, R., … Lanius, R. A. (2018). Intrinsic connectivity network dynamics in PTSD during amygdala downregulation. Human Brain Mapping, 0(0).
  • 🚨  Mehler, D. M. A., Sokunbi, M. O., Habes, I., Barawi, K., Subramanian, L., Range, M., … Linden, D. E. J. (2018). Targeting the affective brain—a randomized controlled trial of real-time fMRI neurofeedback in patients with depression. Neuropsychopharmacology, 1.
  • 🚨  Zweerings, J., Pflieger, E. M., Mathiak, K. A., Zvyagintsev, M., Kacela, A., Flatten, G., and Mathiak, K. (2018). Impaired Voluntary Control in PTSD: Probing Self-Regulation of the ACC With Real-Time fMRI. Frontiers in Psychiatry, 9.
  • 🚨  Liu, N., Yu, X., Yao, L., and Zhao, X. (2018). Mapping the Cortical Network Arising From Up-Regulated Amygdaloidal Activation Using λ-Louvain Algorithm. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(6), 1169–1177.
  • 🚨  Sokunbi, M. O. (2018). Using real-time fMRI brain-computer interfacing to treat eating disorders. Journal of the Neurological Sciences, 388, 109–114.
  • 🚨  Young, K. D., Zotev, V., Phillips, R., Misaki, M., Drevets, W. C., and Bodurka, J. (2018). Amygdala real-time functional magnetic resonance imaging neurofeedback for major depressive disorder: A review. Psychiatry and Clinical Neurosciences, 72(7), 466–481.
  • 🚨  Taschereau-Dumouchel, V., Cortese, A., Chiba, T., Knotts, J. D., Kawato, M., and Lau, H. (2018). Towards an unconscious neural reinforcement intervention for common fears. Proceedings of the National Academy of Sciences, 115(13), 3470–3475.
  • 🚨  Orlov, N. D., Giampietro, V., O’Daly, O., Lam, S.-L., Barker, G. J., Rubia, K., … Allen, P. (2018). Real-time fMRI neurofeedback to down-regulate superior temporal gyrus activity in patients with schizophrenia and auditory hallucinations: a proof-of-concept study. Translational Psychiatry, 8(1), 46.
  • 🚨  Gerchen, M. F., Kirsch, M., Bahs, N., Halli, P., Gerhardt, S., Schäfer, A., … Kirsch, P. (2018). The SyBil-AA real-time fMRI neurofeedback study: protocol of a single-blind randomized controlled trial in alcohol use disorder. BMC Psychiatry, 18(1), 12.
  • 🚨  Pierrefeu, A. de, Fovet, T., Hadj‐Selem, F., Löfstedt, T., Ciuciu, P., Lefebvre, S., … Duchesnay, E. (2018). Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity. Human Brain Mapping, 39(4), 1777–1788.
  • 🚨  Kleinjung, T., Thüring, C., Güntensperger, D., Neff, P., and Meyer, M. (2018). Neurofeedback in der Behandlung des chronischen Tinnitus. HNO, 66(3), 198–204.
  • 🚨  Hellrung, L., Dietrich, A., Hollmann, M., Pleger, B., Kalberlah, C., Roggenhofer, E., … Horstmann, A. (2018). Intermittent compared to continuous real-time fMRI neurofeedback boosts control over amygdala activation. NeuroImage, 166, 198–208.
  • 🚨  Heunis, S., Lamerichs, R., Zinger, S., Aldenkamp, B., and Breeuwer, M. (2018). Quality and denoising in real-time fMRI neurofeedback: a methods review. OSF Preprints.
  • Krause, F., Benjamins, C., Lührs, M., Eck, J., Noirhomme, Q., Rosenke, M., … Goebel, R. (2017). Real-time fMRI-based self-regulation of brain activation across different visual feedback presentations. Brain-Computer Interfaces, 4(1-2), 87–101.
  • Lorenz, R., Hampshire, A., and Leech, R. (2017). Neuroadaptive Bayesian optimization and hypothesis testing. Trends in Cognitive Sciences.
  • Lorenz, R., Violante, I. R., Monti, R. P., Montana, G., Hampshire, A., and Leech, R. (2017). Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization. BioRxiv, 128678.
  • McDonald, A. R., Muraskin, J., Van Dam, N. T., Froehlich, C., Puccio, B., Pellman, J., … others. (2017). The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository. NeuroImage, 146, 157–170.
  • Nicholson, A. A., Rabellino, D., Densmore, M., Frewen, P. A., Paret, C., Kluetsch, R., … others. (2017). The neurobiology of emotion regulation in posttraumatic stress disorder: Amygdala downregulation via real-time fMRI neurofeedback. Human Brain Mapping, 38(1), 541–560.
  • Cortese, A., Amano, K., Koizumi, A., Lau, H., and Kawato, M. (2017). Decoded fMRI neurofeedback can induce bidirectional confidence changes within single participants. NeuroImage, 149, 323–337.
  • Zilverstand, A., Sorger, B., Slaats-Willemse, D., Kan, C. C., Goebel, R., and 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), e0170795.
  • Emmert, K., Kopel, R., Koush, Y., Maire, R., Senn, P., Van De Ville, D., and Haller, S. (2017). Continuous vs. intermittent neurofeedback to regulate auditory cortex activity of tinnitus patients using real-time fMRI-A pilot study. NeuroImage: Clinical.
  • Oblak, E. F., Lewis-Peacock, J. A., and Sulzer, J. S. (2017). Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment. PLoS Computational Biology, 13(7), e1005681.
  • Paret, C., Ruf, M., Gerchen, M. F., Kluetsch, R., Demirakca, T., Jungkunz, M., … Ende, G. (2016). fMRI neurofeedback of amygdala response to aversive stimuli enhances prefrontal–limbic brain connectivity. NeuroImage, 125, 182–188.
  • Nakazawa, E., Yamamoto, K., Tachibana, K., Toda, S., Takimoto, Y., and Akabayashi, A. (2016). Ethics of decoded neurofeedback in clinical research, treatment, and moral enhancement. AJOB Neuroscience, 7(2), 110–117.
  • Koizumi, A., Amano, K., Cortese, A., Shibata, K., Yoshida, W., Seymour, B., … Lau, H. (2016). Fear reduction without fear through reinforcement of neural activity that bypasses conscious exposure. Nature Human Behaviour, 1, 0006.
  • Cortese, A., Amano, K., Koizumi, A., Kawato, M., and Lau, H. (2016). Multivoxel neurofeedback selectively modulates confidence without changing perceptual performance. Nature Communications, 7.
  • Amano, K., Shibata, K., Kawato, M., Sasaki, Y., and Watanabe, T. (2016). Learning to associate orientation with color in early visual areas by associative decoded fMRI neurofeedback. Current Biology, 26(14), 1861–1866.
  • Hamilton, J. P., Glover, G. H., Bagarinao, E., Chang, C., Mackey, S., Sacchet, M. D., and Gotlib, I. H. (2016). Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder. Psychiatry Research: Neuroimaging, 249, 91–96.
  • Liew, S.-L., Rana, M., Cornelsen, S., Fortunato de Barros Filho, M., Birbaumer, N., Sitaram, R., … Soekadar, S. R. (2016). Improving motor corticothalamic communication after stroke using real-time fMRI connectivity-based neurofeedback. Neurorehabilitation and Neural Repair, 30(7), 671–675.
  • Gerin, M. I., Fichtenholtz, H., Roy, A., Walsh, C. J., Krystal, J. H., Southwick, S., and Hampson, M. (2016). Real-time fMRI neurofeedback with war veterans with chronic PTSD: a feasibility study. Frontiers in Psychiatry, 7.
  • Fovet, T., Orlov, N., Dyck, M., Allen, P., Mathiak, K., and Jardri, R. (2016). Translating neurocognitive models of auditory-verbal hallucinations into therapy: using real-time fMRI-neurofeedback to treat voices. Frontiers in Psychiatry, 7.
  • Emmert, K., Breimhorst, M., Bauermann, T., Birklein, F., Rebhorn, C., Van De Ville, D., and Haller, S. (2016). Active pain coping is associated with the response in real-time fMRI neurofeedback during pain. Brain Imaging and Behavior, 1–10.
  • Ihssen, N., Sokunbi, M. O., Lawrence, A. D., Lawrence, N. S., and Linden, D. E. J. (2016). Neurofeedback of visual food cue reactivity: a potential avenue to alter incentive sensitization and craving. Brain Imaging and Behavior, 1–10.
  • Marxen, M., Jacob, M. J., Müller, D. K., Posse, S., Ackley, E., Hellrung, L., … Smolka, M. N. (2016). Amygdala regulation following fmri-neurofeedback without instructed strategies. Frontiers in Human Neuroscience, 10.
  • Ramot, M., Grossman, S., Friedman, D., and Malach, R. (2016). Covert neurofeedback without awareness shapes cortical network spontaneous connectivity. Proceedings of the National Academy of Sciences, 201516857.
  • Dyck, M. S., Mathiak, K. A., Bergert, S., Sarkheil, P., Koush, Y., Alawi, E. M., … Mathiak, K. (2016). Targeting treatment-resistant auditory verbal hallucinations in schizophrenia with fMRI-based neurofeedback–exploring different cases of schizophrenia. Frontiers in Psychiatry, 7.
  • Radua, J., Stoica, T., Scheinost, D., Pittenger, C., and Hampson, M. (2016). Neural correlates of success and failure signals during neurofeedback learning. Neuroscience.
  • Habes, I., Rushton, S., Johnston, S. J., Sokunbi, M. O., Barawi, K., Brosnan, M., … Linden, D. E. J. (2016). fMRI neurofeedback of higher visual areas and perceptual biases. Neuropsychologia, 85, 208–215.
  • Paret, C., Kluetsch, R., Zaehringer, J., Ruf, M., Demirakca, T., Bohus, M., … Schmahl, C. (2016). Alterations of amygdala-prefrontal connectivity with real-time fMRI neurofeedback in BPD patients. Social Cognitive and Affective Neuroscience, 11(6), 952–960.
  • Kopel, R., Emmert, K., Scharnowski, F., Haller, S., and Van De Ville, D. (2016). Distributed patterns of brain activity underlying real-time fMRI neurofeedback training. IEEE Transactions on Biomedical Engineering.
  • Lorenz, R., Monti, R. P., Violante, I. R., Anagnostopoulos, C., Faisal, A. A., Montana, G., and Leech, R. (2016). The Automatic Neuroscientist: A framework for optimizing experimental design with closed-loop real-time fMRI. NeuroImage, 129, 320–334.
  • MacInnes, J. J., Dickerson, K. C., Chen, N.-kuei, and Adcock, R. A. (2016). Cognitive Neurostimulation: Learning to Volitionally Sustain Ventral Tegmental Area Activation. Neuron, 89(6), 1331–1342.
  • Paret, C., Ruf, M., Gerchen, M. F., Kluetsch, R., Demirakca, T., Jungkunz, M., … Ende, G. (2016). fMRI neurofeedback of amygdala response to aversive stimuli enhances prefrontal–limbic brain connectivity. NeuroImage, 125, 182–188.
  • Emmert, K., Kopel, R., Sulzer, J., Brühl, A. B., Berman, B. D., Linden, D. E. J., … others. (2016). Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated? NeuroImage, 124, 806–812.
  • Kadosh, K. C., Luo, Q., de Burca, C., Sokunbi, M. O., Feng, J., Linden, D. E. J., and Lau, J. Y. F. (2016). Using real-time fMRI to influence effective connectivity in the developing emotion regulation network. NeuroImage, 125, 616–626.
  • Sherwood, M. S., Kane, J. H., Weisend, M. P., and 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.
  • Li, Z., Tong, L., Guan, M., He, W., Wang, L., Bu, H., … Yan, B. (2016). Altered Resting-State Amygdala Functional Connectivity after Real-Time fMRI Emotion Self-Regulation Training. BioMed Research International, 2016.
  • Hartwell, K. J., Hanlon, C. A., Li, X., Borckardt, J. J., Canterberry, M., Prisciandaro, J. J., … Brady, K. T. (2016). Individualized real-time fMRI neurofeedback to attenuate craving in nicotine-dependent smokers. Journal of Psychiatry & Neuroscience: JPN, 41(1), 48.
  • Moeller, S. J., Konova, A. B., and Goldstein, R. Z. (2015). Multiple ambiguities in the measurement of drug craving. Addiction, 110(2), 205–206.
  • Farkas, A., Bluschke, A., Roessner, V., and Beste, C. (2015). Neurofeedback and its possible relevance for the treatment of Tourette syndrome. Neuroscience & Biobehavioral Reviews, 51, 87–99.
  • Scharnowski, F., and Weiskopf, N. (2015). Cognitive enhancement through real-time fMRI neurofeedback. Current Opinion in Behavioral Sciences, 4, 122–127.
  • Mishra, J., and Gazzaley, A. (2015). Closed-loop cognition: the next frontier arrives. Trends in Cognitive Sciences, 19(5), 242–243.
  • Cisler, J. M., Bush, K., James, G. A., Smitherman, S., and Kilts, C. D. (2015). Decoding the traumatic memory among women with PTSD: implications for neurocircuitry models of PTSD and real-time fMRI neurofeedback. PloS One, 10(8), e0134717.
  • Feng, I. J., Jack, A. I., and Tatsuoka, C. (2015). Dynamic adjustment of stimuli in real time functional magnetic resonance imaging. PloS One, 10(3), e0117942.
  • Lee, D., Jang, C., and Park, H.-J. (2015). Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification. NeuroImage, 108, 203–213.
  • Misaki, M., Barzigar, N., Zotev, V., Phillips, R., Cheng, S., and Bodurka, J. (2015). Real-time fMRI processing with physiological noise correction–Comparison with off-line analysis. Journal of Neuroscience Methods, 256, 117–121.
  • Reichert, C., Fendrich, R., Bernarding, J., Tempelmann, C., Hinrichs, H., and Rieger, J. W. (2015). Online tracking of the contents of conscious perception using real-time fMRI. Probing Auditory Scene Analysis, 69.
  • Zilverstand, A., Sorger, B., Sarkheil, P., and Goebel, R. (2015). fMRI neurofeedback facilitates anxiety regulation in females with spider phobia. Frontiers in Behavioral Neuroscience, 9.
  • Kirsch, M., Gruber, I., Ruf, M., Kiefer, F., and Kirsch, P. (2015). Real-time functional magnetic resonance imaging neurofeedback can reduce striatal cue-reactivity to alcohol stimuli. Addiction Biology.
  • Scharnowski, F., Veit, R., Zopf, R., Studer, P., Bock, S., Diedrichsen, J., … Weiskopf, N. (2015). Manipulating motor performance and memory through real-time fMRI neurofeedback. Biological Psychology, 108, 85–97.
  • Megumi, F., Yamashita, A., Kawato, M., and Imamizu, H. (2015). Functional MRI neurofeedback training on connectivity between two regions induces long-lasting changes in intrinsic functional network. Frontiers in Human Neuroscience, 9, 160.
  • Cordes, J. S., Mathiak, K. A., Dyck, M., Alawi, E. M., Gaber, T. J., Zepf, F. D., … Mathiak, K. (2015). Cognitive and neural strategies during control of the anterior cingulate cortex by fMRI neurofeedback in patients with schizophrenia. Frontiers in Behavioral Neuroscience, 9.
  • Kim, D.-Y., Yoo, S.-S., Tegethoff, M., Meinlschmidt, G., and Lee, J.-H. (2015). The inclusion of functional connectivity information into fMRI-based neurofeedback improves its efficacy in the reduction of cigarette cravings. Journal of Cognitive Neuroscience.
  • Koush, Y., Meskaldji, D.-E., Pichon, S., Rey, G., Rieger, S. W., Linden, D. E. J., … Scharnowski, F. (2015). Learning control over emotion networks through connectivity-based neurofeedback. Cerebral Cortex, bhv311.
  • Gröne, M., Dyck, M., Koush, Y., Bergert, S., Mathiak, K. A., Alawi, E. M., … Mathiak, K. (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.
  • Karch, S., Keeser, D., Hümmer, S., Paolini, M., Kirsch, V., Karali, T., … others. (2015). Modulation of craving related brain responses using real-time fMRI in patients with alcohol use disorder. PloS One, 10(7), e0133034.
  • Schnyer, D. M., Beevers, C. G., Sherman, S. M., Cohen, J. D., Norman, K. A., Turk-Browne, N. B., and others. (2015). Neurocognitive therapeutics: from concept to application in the treatment of negative attention bias. Biology of Mood & Anxiety Disorders, 5(1), 1.
  • deBettencourt, M. T., Cohen, J. D., Lee, R. F., Norman, K. A., Turk-Browne, N. B., and others. (2015). Closed-loop training of attention with real-time brain imaging. Nature Neuroscience, 18(3), 470–475.
  • Harmelech, T., Friedman, D., and Malach, R. (2015). Differential magnetic resonance neurofeedback modulations across extrinsic (visual) and intrinsic (default-mode) nodes of the human cortex. The Journal of Neuroscience, 35(6), 2588–2595.
  • Baecke, S., Lützkendorf, R., Mallow, J., Luchtmann, M., Tempelmann, C., Stadler, J., and Bernarding, J. (2015). A proof-of-principle study of multi-site real-time functional imaging at 3T and 7T: Implementation and validation. Scientific Reports, 5, 8413.
  • Blefari, M. L., Sulzer, J., Hepp-Reymond, M.-C., Kollias, S., and Gassert, R. (2015). Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery. Frontiers in Behavioral Neuroscience, 9, 18.
  • Caria, A., and de Falco, S. (2015). Anterior insular cortex regulation in autism spectrum disorders. Frontiers in Behavioral Neuroscience, 9, 38.
  • Shen, J., Zhang, G., Yao, L., and Zhao, X. (2015). Real-time fMRI training-induced changes in regional connectivity mediating verbal working memory behavioral performance. Neuroscience, 289, 144–152.
  • Sarkheil, P., Zilverstand, A., Kilian-Hütten, N., Schneider, F., Goebel, R., and Mathiak, K. (2015). fMRI feedback enhances emotion regulation as evidenced by a reduced amygdala response. Behavioural Brain Research, 281, 326–332.
  • Guan, M., Ma, L., Li, L., Yan, B., Zhao, L., Tong, L., … Shi, D. (2015). Self-regulation of brain activity in patients with postherpetic neuralgia: a double-blind randomized study using real-time FMRI neurofeedback. PloS One, 10(4), e0123675.
  • Zhang, Q., Zhang, G., Yao, L., and Zhao, X. (2015). Impact of real-time fMRI working memory feedback training on the interactions between three core brain networks. Frontiers in Behavioral Neuroscience, 9.
  • Marins, T. F., Rodrigues, E. C., Engel, A., Hoefle, S., Basilio, R., Lent, R., … Tovar-Moll, F. (2015). Enhancing motor network activity using real-time functional MRI neurofeedback of left premotor cortex. Frontiers in Behavioral Neuroscience, 9.
  • Liew, S.-L., Rana, M., Cornelsen, S., de Barros Filho, M. F., Birbaumer, N., Sitaram, R., … Soekadar, S. R. (2015). Improving Motor Corticothalamic Communication After Stroke Using Real-Time fMRI Connectivity-Based Neurofeedback. Neurorehabilitation and Neural Repair, 1545968315619699.
  • Buyukturkoglu, K., Roettgers, H., Sommer, J., Rana, M., Dietzsch, L., Arikan, E. B., … others. (2015). Self-regulation of anterior insula with real-time fMRI and its behavioral effects in obsessive-compulsive disorder: a feasibility study. PloS One, 10(8), e0135872.
  • Auer, T., Schweizer, R., and 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.
  • Ruiz, S., Buyukturkoglu, K., Rana, M., Birbaumer, N., and Sitaram, R. (2014). Real-time fMRI brain computer interfaces: self-regulation of single brain regions to networks. Biological Psychology, 95, 4–20.
  • Koush, Y., Elliott, M. A., Scharnowski, F., and Mathiak, K. (2014). Comparison of Real-Time Water Proton Spectroscopy and Echo-Planar Imaging Sensitivity to the BOLD Effect at 3 T and at 7 T. PloS One, 9(3), e91620.
  • Antal, A., Bikson, M., Datta, A., Lafon, B., Dechent, P., Parra, L. C., and Paulus, W. (2014). Imaging artifacts induced by electrical stimulation during conventional fMRI of the brain. Neuroimage, 85, 1040–1047.
  • Brühl, A. B., Scherpiet, S., Sulzer, J., Stämpfli, P., Seifritz, E., and 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.
  • Mendelsohn, A., Pine, A., and Schiller, D. (2014). Between thoughts and actions: motivationally salient cues invigorate mental action in the human brain. Neuron, 81(1), 207–217.
  • Zilverstand, A., Sorger, B., Zimmermann, J., Kaas, A., and Goebel, R. (2014). Windowed correlation: a suitable tool for providing dynamic fMRI-based functional connectivity neurofeedback on task difficulty. PLoS One, 9(1), e85929.
  • Ruiz, S., Buyukturkoglu, K., Rana, M., Birbaumer, N., and Sitaram, R. (2014). Real-time fMRI brain computer interfaces: self-regulation of single brain regions to networks. Biological Psychology, 95, 4–20.
  • Stoeckel, L. E., Garrison, K. A., Ghosh, S. S., Wighton, P., Hanlon, C. A., Gilman, J. M., … others. (2014). Optimizing real time fMRI neurofeedback for therapeutic discovery and development. NeuroImage: Clinical, 5, 245–255.
  • Budde, J., Shajan, G., Zaitsev, M., Scheffler, K., and Pohmann, R. (2014). Functional MRI in human subjects with gradient-echo and spin-echo EPI at 9.4 T. Magnetic Resonance in Medicine, 71(1), 209–218.
  • Magland, J. F., and Childress, A. R. (2014). Task-Correlated Facial and Head Movements in Classifier-Based Real-Time fMRI. Journal of Neuroimaging, 24(4), 371–378.
  • Hinds, O., Wighton, P., Dylan Tisdall, M., Hess, A., Breiter, H., and Kouwe, A. (2014). Neurofeedback using functional spectroscopy. International Journal of Imaging Systems and Technology, 24(2), 138–148.
  • Cohen, O., Druon, S., Lengagne, S., Mendelsohn, A., Malach, R., Kheddar, A., and Friedman, D. (2014). fMRI-based robotic embodiment: Controlling a humanoid robot by thought using real-time fMRI. PRESENCE: Teleoperators and Virtual Environments, 23(3), 229–241.
  • Goebel, R., and Linden, D. (2014). Neurofeedback with real-time functional MRI. In MRI in Psychiatry, pages 35–46. Springer.
  • Linden, D. E. J. (2014). Neurofeedback and networks of depression. Dialogues in Clinical Neuroscience, 16(1), 103.
  • Scharnowski, F., Rosa, M. J., Golestani, N., Hutton, C., Josephs, O., Weiskopf, N., and Rees, G. (2014). Connectivity changes underlying neurofeedback training of visual cortex activity. PloS One, 9(3), e91090.
  • Young, K. D., Zotev, V., Phillips, R., Misaki, M., Yuan, H., Drevets, W. C., and Bodurka, J. (2014). Real-time FMRI neurofeedback training of amygdala activity in patients with major depressive disorder. PloS One, 9(2), e88785.
  • Sitaram, R., Caria, A., Veit, R., Gaber, T., Ruiz, S., and Birbaumer, N. (2014). Volitional control of the anterior insula in criminal psychopaths using real-time fMRI neurofeedback: a pilot study. Frontiers in Behavioral Neuroscience, 8, 344.
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  • Nicholson, A. A., Ros, T., Frewen, P. A., Densmore, M., Théberge, J., Kluetsch, R. C., … Lanius, R. A. (2016). Alpha oscillation neurofeedback modulates amygdala complex connectivity and arousal in posttraumatic stress disorder. NeuroImage: Clinical, 12, 506–516.
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  • Jump to: fMRI EEG fNIRS MEG Mixed

    fNIRS

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  • Jump to: fMRI EEG fNIRS MEG Mixed

    MEG

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  • Charles, L., King, J.-R., and Dehaene, S. (2014). Decoding the dynamics of action, intention, and error detection for conscious and subliminal stimuli. Journal of Neuroscience, 34(4), 1158–1170.
  • Jump to: fMRI EEG fNIRS MEG Mixed

    Multiple modalities

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