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2018

  • 🚨  Rance, M., Walsh, C., Sukhodolsky, D. G., Pittman, B., Qiu, M., Kichuk, S. A., … others. (2018). Time course of clinical change following neurofeedback. NeuroImage.
    Link
  • 🚨  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.
    Link
  • 🚨  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.
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  • 🚨  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.
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  • 🚨  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.
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  • 🚨  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.
    Link
  • 🚨  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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 🚨  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.
  • 🚨  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.
  • 🚨  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.
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  • 🚨  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.
    Link
  • 🚨  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.
    Link
  • 🚨  Skouras, S., and Scharnowski, F. (2018). The effects of psychiatric history and age on self-regulation of the default mode network. BioRxiv, 342220.
    Link
  • 🚨  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.
    Link
  • 🚨  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.
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  • 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.
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  • 🚨  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.
    Link
  • 🚨  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).
    Link
  • 🚨  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.
    Link
  • 🚨  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.
    Link
  • 🚨  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.
    Link
  • 🚨  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.
    Link
  • 🚨  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.
    Link
  • 🚨  Kleinjung, T., Thüring, C., Güntensperger, D., Neff, P., and Meyer, M. (2018). Neurofeedback in der Behandlung des chronischen Tinnitus. HNO, 66(3), 198–204.
    Link
  • 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.
    Link
  • 🚨  Sokunbi, M. O. (2018). Using real-time fMRI brain-computer interfacing to treat eating disorders. Journal of the Neurological Sciences, 388, 109–114.
    Link
  • 🚨  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.
    Link
  • 🚨  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.
    Link
  • 🚨  Oblak, E. F., Sulzer, J. S., and Lewis-Peacock, J. A. (2018). A simulation-based approach to improve decoded neurofeedback performance. BioRxiv.
    Link

    • 2017

  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • Blume, F., Hudak, J., Dresler, T., Ehlis, A.-C., Kühnhausen, J., Renner, T. J., and Gawrilow, C. (2017). NIRS-based neurofeedback training in a virtual reality classroom for children with attention-deficit/hyperactivity disorder: study protocol for a randomized controlled trial. Trials, 18(1), 41.
    Link
  • Liu, N., Cliffer, S., Pradhan, A. H., Lightbody, A., Hall, S. S., and Reiss, A. L. (2017). Optical-imaging-based neurofeedback to enhance therapeutic intervention in adolescents with autism: methodology and initial data. Neurophotonics, 4(1), 011003–011003.
    Link
  • Kober, S. E., Schweiger, D., Reichert, J. L., Neuper, C., and Wood, G. (2017). Upper Alpha Based Neurofeedback Training in Chronic Stroke: Brain Plasticity Processes and Cognitive Effects. Applied Psychophysiology and Biofeedback, 1–15.
    Link
  • Moreno-Garcı́a Inmaculada, Meneres-Sancho, S., Camacho-Vara de Rey, C., and Servera, M. (2017). A Randomized Controlled Trial to Examine the Posttreatment Efficacy of Neurofeedback, Behavior Therapy, and Pharmacology on ADHD Measures. Journal of Attention Disorders, 1087054717693371.
    Link
  • Friesen, C. L., Bardouille, T., Neyedli, H. F., and Boe, S. G. (2017). Combined Action Observation and Motor Imagery Neurofeedback for Modulation of Brain Activity. Frontiers in Human Neuroscience, 10, 692.
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  • 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.
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  • Mennella, R., Patron, E., and Palomba, D. (2017). Frontal alpha asymmetry neurofeedback for the reduction of negative affect and anxiety. Behaviour Research and Therapy.
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  • Mohagheghi, A., Amiri, S., Moghaddasi Bonab, N., Chalabianloo, G., Noorazar, S. G., Tabatabaei, S. M., and Farhang, S. (2017). A Randomized Trial of Comparing the Efficacy of Two Neurofeedback Protocols for Treatment of Clinical and Cognitive Symptoms of ADHD: Theta Suppression/Beta Enhancement and Theta Suppression/Alpha Enhancement. BioMed Research International, 2017.
    Link
  • Fielenbach, S., Donkers, F. C. L., Spreen, M., and Bogaerts, S. (2017). Neurofeedback as a Treatment for Impulsivity in a Forensic Psychiatric Population With Substance Use Disorder: Study Protocol of a Randomized Controlled Trial Combined With an N-of-1 Clinical Trial. JMIR Research Protocols, 6(1), e13.
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  • Alves-Pinto, A., Turova, V., Blumenstein, T., Hantuschke, C., and Lampe, R. (2017). Implicit Learning of a Finger Motor Sequence by Patients with Cerebral Palsy After Neurofeedback. Applied Psychophysiology and Biofeedback, 1–11.
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  • Lee, E.-J., and Jung, C.-H. (2017). Additive effects of neurofeedback on the treatment of ADHD: A randomized controlled study. Asian Journal of Psychiatry, 25, 16–21.
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  • Kalaivani, M., Jeyalakshmi, M. S., and Aarthy, M. T. (2017). Neurofeedback training for elderly with increased stress level. In Intelligent Systems and Control (ISCO), 2017 11th International Conference on, pages 129–133. IEEE.
    Link
  • Heidari, Z., Taremian, F., and Khalatbari, J. (2017). The Effect of Modified Alpha-Theta Neurofeedback Protocol on Instant Craving in Opioid Users. ZUMS Journal, 25(109), 130–139.
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  • Enriquez-Geppert, S., Huster, R. J., and Herrmann, C. S. (2017). EEG-neurofeedback as a tool to modulate cognition and behaviour: a review tutorial. Frontiers in Human Neuroscience, 11, 51.
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  • Mirifar, A., Beckmann, J., and Ehrlenspiel, F. (2017). Neurofeedback as Supplementary Training for Optimizing Athletes’ Performance: A Systematic Review with Implications for Future Research. Neuroscience & Biobehavioral Reviews.
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  • Alkoby, O., Abu-Rmileh, A., Shriki, O., and Todder, D. (2017). Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning. Neuroscience.
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  • Thibault, R. T., Lifshitz, M., and Raz, A. (2017). Neurofeedback or Neuroplacebo?
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  • 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.
    Link
  • Lorenz, R., Hampshire, A., and Leech, R. (2017). Neuroadaptive Bayesian optimization and hypothesis testing. Trends in Cognitive Sciences.
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  • 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.
    Link
  • Zotev, V., Misaki, M., Phillips, R., Wong, C. K., and Bodurka, J. (2017). Real-time fMRI neurofeedback of the mediodorsal and anterior thalamus enhances correlation between thalamic BOLD activity and alpha EEG rhythm. ArXiv Preprint ArXiv:1702.04195.
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  • Kaur, C., and Singh, P. (2017). Toward EEG Spectral Analysis of Tomographic Neurofeedback for Depression. In Proceeding of International Conference on Intelligent Communication, Control and Devices, pages 97–103. Springer.
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  • 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.

    • 2016

  • 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.
    Link
  • Cortese, A., Amano, K., Koizumi, A., Kawato, M., and Lau, H. (2016). Multivoxel neurofeedback selectively modulates confidence without changing perceptual performance. Nature Communications, 7.
    Link
  • 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.
    Link
  • Janssen, T. W. P., Bink, M., Geladé, K., van Mourik, R., Maras, A., and Oosterlaan, J. (2016). A randomized controlled trial investigating the effects of neurofeedback, methylphenidate, and physical activity on event-related potentials in children with attention-deficit/hyperactivity disorder. Journal of Child and Adolescent Psychopharmacology, 26(4), 344–353.
    Link
  • Engelbregt, H. J., Keeser, D., van Eijk, L., Suiker, E. M., Eichhorn, D., Karch, S., … Pogarell, O. (2016). Short and long-term effects of sham-controlled prefrontal EEG-neurofeedback training in healthy subjects. Clinical Neurophysiology, 127(4), 1931–1937.
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  • Hernandez, L. D., Rieger, K., Baenninger, A., Brandeis, D., and Koenig, T. (2016). Towards using microstate-neurofeedback for the treatment of psychotic symptoms in schizophrenia. A feasibility study in healthy participants. Brain Topography, 29(2), 308–321.
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  • Keynan, J. N., Meir-Hasson, Y., Gilam, G., Cohen, A., Jackont, G., Kinreich, S., … others. (2016). Limbic activity modulation guided by fMRI-inspired EEG improves implicit emotion regulation. Biological Psychiatry.
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  • 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.
    Link
  • Zotev, V., Yuan, H., Misaki, M., Phillips, R., Young, K. D., Feldner, M. T., and 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, 224–238.
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  • 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.
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  • 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.
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  • Mayer, K., Blume, F., Wyckoff, S. N., Brokmeier, L. L., and Strehl, U. (2016). Neurofeedback of slow cortical potentials as a treatment for adults with Attention Deficit-/Hyperactivity Disorder. Clinical Neurophysiology, 127(2), 1374–1386.
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  • González-Castro, P., Cueli, M., Rodrı́guez Celestino, Garcı́a Trinidad, and Álvarez, L. (2016). Efficacy of neurofeedback versus pharmacological support in subjects with ADHD. Applied Psychophysiology and Biofeedback, 41(1), 17–25.
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  • Surmeli, T., Eralp, E., Mustafazade, I., Kos, H., Özer, G. E., and Surmeli, O. H. (2016). Quantitative EEG Neurometric Analysis–Guided Neurofeedback Treatment in Dementia 20 Cases. How Neurometric Analysis Is Important for the Treatment of Dementia and as a Biomarker? Clinical EEG and Neuroscience, 47(2), 118–133.
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  • Zhigalov, A., Kaplan, A., and Palva, J. M. (2016). Modulation of critical brain dynamics using closed-loop neurofeedback stimulation. Clinical Neurophysiology, 127(8), 2882–2889.
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  • Lackner, N., Unterrainer, H. F., Skliris, D., Wood, G., Wallner-Liebmann, S. J., Neuper, C., and Gruzelier, J. H. (2016). The effectiveness of visual short-time neurofeedback on brain activity and clinical characteristics in alcohol use disorders: Practical issues and results. Clinical EEG and Neuroscience, 47(3), 188–195.
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  • Gapen, M., van der Kolk, B. A., Hamlin, E., Hirshberg, L., Suvak, M., and Spinazzola, J. (2016). A pilot study of neurofeedback for chronic PTSD. Applied Psychophysiology and Biofeedback, 41(3), 251–261.
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  • 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.
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  • Hsueh, J.-J., Chen, T.-S., Chen, J.-J., and Shaw, F.-Z. (2016). Neurofeedback training of EEG alpha rhythm enhances episodic and working memory. Human Brain Mapping, 37(7), 2662–2675.
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  • 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.
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  • Micoulaud-Franchi, J.-A., and Fovet, T. (2016). Neurofeedback: time needed for a promising non-pharmacological therapeutic method. The Lancet Psychiatry, 3(9), e16.
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  • Pacheco, N. C. (2016). Neurofeedback for peak performance training. Journal of Mental Health Counseling, 38(2), 116–123.
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  • Cheon, E.-J., Koo, B.-H., and Choi, J.-H. (2016). The Efficacy of Neurofeedback in Patients with Major Depressive Disorder: An Open Labeled Prospective Study. Applied Psychophysiology and Biofeedback, 41(1), 103–110.
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  • Benioudakis, E. S., Kountzaki, S., Batzou, K., Markogiannaki, K., Seliniotaki, T., Darakis, E., … Nestoros, J. N. (2016). Can Neurofeedback Decrease Anxiety and Fear in Cancer Patients? A Case Study. Postępy Psychiatrii i Neurologii, 25(1), 59–65.
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  • Bluschke, A., Broschwitz, F., Kohl, S., Roessner, V., and Beste, C. (2016). The neuronal mechanisms underlying improvement of impulsivity in ADHD by theta/beta neurofeedback. Scientific Reports, 6.
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  • 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.
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  • 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.
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  • Gomez-Pilar, J., Corralejo, R., Nicolas-Alonso, L. F., Álvarez, D., and Hornero, R. (2016). Neurofeedback training with a motor imagery-based BCI: neurocognitive improvements and EEG changes in the elderly. Medical & Biological Engineering & Computing, 54(11), 1655–1666.
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  • Lackner, N., Unterrainer, H.-F., Skliris, D., Shaheen, S., Dunitz-Scheer, M., Wood, G., … Neuper, C. (2016). EEG neurofeedback effects in the treatment of adolescent anorexia nervosa. Eating Disorders, 24(4), 354–374.
    Link
  • 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.
    Link
  • Jensen, M. P., Gianas, A., George, H. R., Sherlin, L. H., Kraft, G. H., and Ehde, D. M. (2016). Use of neurofeedback to enhance response to hypnotic analgesia in individuals with multiple sclerosis. International Journal of Clinical and Experimental Hypnosis, 64(1), 1–23.
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  • 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.
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  • van Lutterveld, R., Houlihan, S. D., Pal, P., Sacchet, M. D., McFarlane-Blake, C., Patel, P. R., … others. (2016). Source-space EEG neurofeedback links subjective experience with brain activity during effortless awareness meditation. NeuroImage.
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  • Rozengurt, R., Barnea, A., Uchida, S., and Levy, D. A. (2016). Theta EEG neurofeedback benefits early consolidation of motor sequence learning. Psychophysiology, 53(7), 965–973.
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  • 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.
    Link
  • Geladé, K., Janssen, T. W. P., Bink, M., van Mourik, R., Maras, A., and Oosterlaan, J. (2016). Behavioral effects of neurofeedback compared to stimulants and physical activity in attention-deficit/hyperactivity disorder: a randomized controlled trial. Journal of Clinical Psychiatry, 77(10), e1270–e1277.
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  • Kim, J.-H., Park, E.-J., and Oh, N.-rae. (2016). Effects of neurofeedback training on life stress and depression in female college students. Journal of Digital Convergence, 14(3), 299–307.
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  • Deilami, M., Jahandideh, A., Kazemnejad, Y., Fakour, Y., Alipoor, S., Rabiee, F., … Mosavi, S. A. (2016). The effect of neurofeedback therapy on reducing symptoms associated with attention deficit hyperactivity disorder: A case series study. Basic and Clinical Neuroscience, 7(2), 167.
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  • Geladé, K., Bink, M., Janssen, T. W. P., van Mourik, R., Maras, A., and Oosterlaan, J. (2016). An RCT into the effects of neurofeedback on neurocognitive functioning compared to stimulant medication and physical activity in children with ADHD. European Child & Adolescent Psychiatry, 1–12.
    Link
  • Bink, M., Bongers, I. L., Popma, A., Janssen, T. W. P., and van Nieuwenhuizen, C. (2016). 1-year follow-up of neurofeedback treatment in adolescents with attention-deficit hyperactivity disorder: randomised controlled trial. British Journal of Psychiatry Open, 2(2), 107–115.
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  • Liu, Y., Hou, X., Sourina, O., and Bazanova, O. (2016). Individual Theta/Beta Based Algorithm for Neurofeedback Games to Improve Cognitive Abilities. In Transactions on Computational Science XXVI, pages 57–73. Springer.
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  • Gadea, M., Aliño, M., Garijo, E., Espert, R., and Salvador, A. (2016). Testing the Benefits of Neurofeedback on Selective Attention Measured Through Dichotic Listening. Applied Psychophysiology and Biofeedback, 41(2), 157–164.
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  • Ford, N. L., Wyckoff, S. N., and Sherlin, L. H. (2016). Neurofeedback and mindfulness in peak performance training among athletes. Biofeedback, 44(3), 152–159.
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  • 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.
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  • Reis, J., Portugal, A. M., Fernandes Luı́s, Afonso, N., Pereira, M., Sousa, N., and Dias, N. S. (2016). An alpha and theta intensive and short neurofeedback protocol for healthy aging working-memory training. Frontiers in Aging Neuroscience, 8.
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  • Dupee, M., Forneris, T., and Werthner, P. (2016). Perceived Outcomes of a Biofeedback and Neurofeedback Training Intervention for Optimal Performance: Learning to Enhance Self-Awareness and Self-Regulation With Olympic Athletes. The Sport Psychologist, 30(4), 339–349.
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  • de Ruiter, M. A., Oosterlaan, J., Schouten-van Meeteren, A. Y. N., Maurice-Stam, H., van Vuurden, D. G., Gidding, C., … Grootenhuis, M. A. (2016). Neurofeedback ineffective in paediatric brain tumour survivors: Results of a double-blind randomised placebo-controlled trial. European Journal of Cancer, 64, 62–73.
    Link
  • Reichert, J. L., Kober, S. E., Schweiger, D., Grieshofer, P., Neuper, C., and Wood, G. (2016). Shutting down sensorimotor interferences after stroke: A proof-of-principle SMR neurofeedback study. Frontiers in Human Neuroscience, 10.
    Link
  • Fernández Thalı́a, Bosch-Bayard, J., Harmony Thalı́a, Caballero Marı́a I, Dı́az-Comas Lourdes, Galán Lı́dice, … Otero-Ojeda, G. (2016). Neurofeedback in Learning Disabled Children: Visual versus Auditory Reinforcement. Applied Psychophysiology and Biofeedback, 41(1), 27–37.
    Link
  • Schmidt, J., and Martin, A. (2016). Neurofeedback Against Binge Eating: A Randomized Controlled Trial in a Female Subclinical Threshold Sample. European Eating Disorders Review, 24(5), 406–416.
    Link
  • 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.
    Link
  • 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.
    Link
  • Cowley, B., Holmström, É., Juurmaa, K., Kovarskis, L., and Krause, C. M. (2016). Computer enabled neuroplasticity treatment: a clinical trial of a novel design for neurofeedback therapy in adult ADHD. Frontiers in Human Neuroscience, 10.
    Link
  • 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.
    Link
  • La Marca, J. P., and O’Connor, R. E. (2016). Neurofeedback as an Intervention to Improve Reading Achievement in Students with Attention Deficit Hyperactivity Disorder, Inattentive Subtype. NeuroRegulation, 3(2), 55.
    Link
  • Lackner, N., Unterrainer, H. F., Skliris, D., Wood, G., Dunitz-Scheer, M., Wallner-Liebmann, S. J., … Neuper, C. (2016). Neurofeedback in the Treatment of Anorexia Nervosa: a Case Report. Fortschritte Der Neurologie-Psychiatrie, 84(2), 88–95.
    Link
  • Altan, S., Berberoglu, B., Canan, S., and Dane, Ş. (2016). Effects of neurofeedback therapy in healthy young subjects. Clinical and Investigative Medicine. Medecine Clinique Et Experimentale, 39(6), 27496.
    Link
  • Ashoori, J. (2016). The Effect of Neurofeedback Training on Anxiety and Depression in Students with Attention Deficit/Hyperactivity Disorders. Journal of Education And Community Health, 2(4), 41–47.
    Link
  • Habibollahi, S., Souri, A., Haji Arbabi, F., and Ashoori, J. (2016). Effects of neurofeedback training on sustain attention and planning in students with attention deficit disorder. Koomesh, 17(2), 447–454.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • Micoulaud Franchi, J., Geoffroy, P., Fond, G., Lopez, R., Bioulac10, S., and Philip11, P. (2016). EEG Neurofeedback treatments in 44 children with ADHD: An updated meta–analysis of Randomized Controlled Trials. Neurofeedback in ADHD.
    Link
  • Cortese, S., Ferrin, M., Brandeis, D., Holtmann, M., Aggensteiner, P., Daley, D., … others. (2016). Neurofeedback for attention-deficit/hyperactivity disorder: meta-analysis of clinical and neuropsychological outcomes from randomized controlled trials. Journal of the American Academy of Child & Adolescent Psychiatry, 55(6), 444–455.
    Link
  • 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.
    Link
  • Thibault, R. T., and Raz, A. (2016). When can neurofeedback join the clinical armamentarium? Lancet, 3(6).
    Link
  • Marzbani, H., Marateb, H. R., and Mansourian, M. (2016). Neurofeedback: a comprehensive review on system design, methodology and clinical applications. Basic and Clinical Neuroscience, 7(2), 143.
    Link
  • Reiter, K., Andersen, S. B., and Carlsson, J. (2016). Neurofeedback treatment and posttraumatic stress disorder: Effectiveness of neurofeedback on posttraumatic stress disorder and the optimal choice of protocol. The Journal of Nervous and Mental Disease, 204(2), 69–77.
    Link
  • Thibault, R. T., and Raz, A. (2016). Neurofeedback: the power of psychosocial therapeutics. The Lancet Psychiatry, 3(11), e18.
    Link
  • Perronnet, L., Lécuyer, A., Lotte, F., Clerc, M., and Barillot, C. (2016). Brain training with neurofeedback. Brain–Computer Interfaces 1: Foundations and Methods, 271–292.
    Link
  • Sacchet, M. D., and Gotlib, I. H. (2016). Neurofeedback training for major depressive disorder: recent developments and future directions. Taylor & Francis.
    Link
  • Chapin, T. J. (2016). Developing a specialty in neurofeedback: Decision points. Journal of Mental Health Counseling, 38(2), 155–169.
    Link
  • Sitaram, R., Ros, T., Stoeckel, L., Haller, S., Scharnowski, F., Lewis-Peacock, J., … Sulzer, J. (2016). Closed-loop brain training: the science of neurofeedback. Nature Reviews Neuroscience.
    Link
  • 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.
    Link
  • Thibault, R. T., Lifshitz, M., and Raz, A. (2016). The self-regulating brain and neurofeedback: Experimental science and clinical promise. Cortex, 74, 247–261.
    Link
  • Meir-Hasson, Y., Keynan, J. N., Kinreich, S., Jackont, G., Cohen, A., Podlipsky-Klovatch, I., … Intrator, N. (2016). One-class fMRI-inspired EEG model for self-regulation training. PloS One, 11(5), e0154968.
    Link
  • Bauer, R., Fels, M., Royter, V., Raco, V., and Gharabaghi, A. (2016). Closed-loop adaptation of neurofeedback based on mental effort facilitates reinforcement learning of brain self-regulation. Clinical Neurophysiology, 127(9), 3156–3164.
    Link
  • Gaume, A., Vialatte, A., Mora-Sánchez, A., Ramdani, C., and Vialatte, F. B. (2016). A psychoengineering paradigm for the neurocognitive mechanisms of biofeedback and neurofeedback. Neuroscience & Biobehavioral Reviews, 68, 891–910.
    Link
  • Bluschke, A., Roessner, V., and Beste, C. (2016). Editorial perspective: how to optimise frequency band neurofeedback for ADHD. Journal of Child Psychology and Psychiatry, 57(4), 457–461.
    Link
  • Ros, T., Frewen, P., Théberge, J., Michela, A., Kluetsch, R., Mueller, A., … Lanius, R. A. (2016). Neurofeedback tunes scale-free dynamics in spontaneous brain activity. Cerebral Cortex.
    Link
  • Hosseini, S. M. H., Pritchard-Berman, M., Sosa, N., Ceja, A., and Kesler, S. R. (2016). Task-based neurofeedback training: A novel approach toward training executive functions. NeuroImage, 134, 153–159.
    Link
  • Serra-Sala, M., Timoneda-Gallart, C., and Pérez-Álvarez, F. (2016). Clinical usefulness of hemoencephalography beyond the neurofeedback. Neuropsychiatric Disease and Treatment, 12, 1173.
    Link
  • Radua, J., Stoica, T., Scheinost, D., Pittenger, C., and Hampson, M. (2016). Neural correlates of success and failure signals during neurofeedback learning. Neuroscience.
    Link
  • Lin, W.-L., and Shih, Y.-L. (2016). Designing EEG Neurofeedback Procedures to Enhance Open-ended versus Closed-ended Creative Potentials. Creativity Research Journal, 28(4), 458–466.
    Link
  • 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.
    Link
  • van der Meer, J. N., Pampel, A., Van Someren, E. J. W., Ramautar, J. R., van der Werf, Y. D., Gomez-Herrero, G., … others. (2016). Carbon-wire loop based artifact correction outperforms post-processing EEG/fMRI corrections—A validation of a real-time simultaneous EEG/fMRI correction method. NeuroImage, 125, 880–894.
    Link

    • 2015

  • Foldes, S. T., Weber, D. J., and Collinger, J. L. (2015). MEG-based neurofeedback for hand rehabilitation. Journal of Neuroengineering and Rehabilitation, 12(1), 1.
    Link
  • Okazaki, Y. O., Horschig, J. M., Luther, L., Oostenveld, R., Murakami, I., and Jensen, O. (2015). Real-time MEG neurofeedback training of posterior alpha activity modulates subsequent visual detection performance. NeuroImage, 107, 323–332.
    Link
  • Merkel, N., Bland, G., Wibral, M., and Singer, W. (2015). Changing High Frequency Oscillatory Patterns in Early Visual Cortex with MEG Neurofeedback. In 6th European Conference of the International Federation for Medical and Biological Engineering, pages 930–933. Springer.
    Link
  • Kober, S. E., Schweiger, D., Witte, M., Reichert, J. L., Grieshofer, P., Neuper, C., and Wood, G. (2015). Specific effects of EEG based neurofeedback training on memory functions in post-stroke victims. Journal of Neuroengineering and Rehabilitation, 12(1), 1.
    Link
  • Rogel, A., Guez, J., Getter, N., Keha, E., Cohen, T., Amor, T., and Todder, D. (2015). Transient Adverse Side Effects During Neurofeedback Training: A Randomized, Sham-Controlled, Double Blind Study. Applied Psychophysiology and Biofeedback, 40(3), 209–218.
    Link
  • Quaedflieg, C. W. E. M., Smulders, F. T. Y., Meyer, T., Peeters, F. P. M. L., Merckelbach, H. L. G. J., and Smeets, T. (2015). The validity of individual frontal alpha asymmetry EEG neurofeedback. Social Cognitive and Affective Neuroscience, nsv090.
    Link
  • Von Carlowitz-Ghori, K., Bayraktaroglu, Z., Waterstraat, G., Curio, G., and Nikulin, V. V. (2015). Voluntary control of corticomuscular coherence through neurofeedback: a proof-of-principle study in healthy subjects. Neuroscience, 290, 243–254.
    Link
  • Vukelić, M., and Gharabaghi, A. (2015). Oscillatory entrainment of the motor cortical network during motor imagery is modulated by the feedback modality. Neuroimage, 111, 1–11.
    Link
  • Wang, Y., Sokhadze, E. M., El-Baz, A. S., Li, X., Sears, L., Casanova, M. F., and Tasman, A. (2015). Relative Power of Specific EEG Bands and Their Ratios during Neurofeedback Training in Children with Autism Spectrum Disorder. Frontiers in Human Neuroscience, 9.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • Moeller, S. J., Konova, A. B., and Goldstein, R. Z. (2015). Multiple ambiguities in the measurement of drug craving. Addiction, 110(2), 205–206.
    Link
  • Zuberer, A., Brandeis, D., and Drechsler, R. (2015). Are treatment effects of neurofeedback training in children with ADHD related to the successful regulation of brain activity? A review on the learning of regulation of brain activity and a contribution to the discussion on specificity. Frontiers in Human Neuroscience, 9, 135.
    Link
  • 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.
    Link
  • Zich, C., Debener, S., De Vos, M., Frerichs, S., Maurer, S., and Kranczioch, C. (2015). Lateralization patterns of covert but not overt movements change with age: An EEG neurofeedback study. Neuroimage, 116, 80–91.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • Caria, A., and de Falco, S. (2015). Anterior insular cortex regulation in autism spectrum disorders. Frontiers in Behavioral Neuroscience, 9, 38.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • Pichiorri, F., Morone, G., Petti, M., Toppi, J., Pisotta, I., Molinari, M., … others. (2015). Brain–computer interface boosts motor imagery practice during stroke recovery. Annals of Neurology, 77(5), 851–865.
    Link
  • Scharnowski, F., and Weiskopf, N. (2015). Cognitive enhancement through real-time fMRI neurofeedback. Current Opinion in Behavioral Sciences, 4, 122–127.
    Link
  • Mishra, J., and Gazzaley, A. (2015). Closed-loop cognition: the next frontier arrives. Trends in Cognitive Sciences, 19(5), 242–243.
    Link
  • Basilio, R., Garrido, G. J., Sato, J. R., Hoefle, S., Melo, B. R. P., Pamplona, F. A., … Moll, J. (2015). FRIEND Engine Framework: a real time neurofeedback client-server system for neuroimaging studies. Frontiers in Behavioral Neuroscience, 9, 3.
    Link
  • Hellrung, L., Hollmann, M., Zscheyge, O., Schlumm, T., Kalberlah, C., Roggenhofer, E., … Horstmann, A. (2015). Flexible adaptive paradigms for fMRI using a novel software package ‘Brain Analysis in Real-Time’(BART). PloS One, 10(4), e0118890.
    Link
  • 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.
    Link
  • Mayeli, A., Zotev, V., Refai, H., and Bodurka, J. (2015). An automatic ICA-based method for removing artifacts from EEG data acquired during fMRI in real time. In 2015 41st Annual Northeast Biomedical Engineering Conference (NEBEC), pages 1–2. IEEE.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link

    • 2014

  • 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.
    Link
  • Moll, J., Weingartner, J. H., Bado, P., Basilio, R., Sato, J. R., Melo, B. R., … Zahn, R. (2014). Voluntary enhancement of neural signatures of affiliative emotion using FMRI neurofeedback. PloS One, 9(5), e97343.
    Link
  • Greer, S. M., Trujillo, A. J., Glover, G. H., and Knutson, B. (2014). Control of nucleus accumbens activity with neurofeedback. NeuroImage, 96, 237–244.
    Link
  • Sokunbi, M. O., Linden, D. E. J., Habes, I., Johnston, S., and 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, 392.
    Link
  • Emmert, K., Breimhorst, M., Bauermann, T., Birklein, F., Van De Ville, D., and 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, 350.
    Link
  • Scheinost, D., Stoica, T., Wasylink, S., Gruner, P., Saksa, J., Pittenger, C., and Hampson, M. (2014). Resting state functional connectivity predicts neurofeedback response. Frontiers in Behavioral Neuroscience, 8, 338.
    Link
  • Leeds, D. D., Pyles, J. A., and Tarr, M. J. (2014). Exploration of complex visual feature spaces for object perception. Frontiers in Computational Neuroscience, 8, 106.
    Link
  • Li, X., Yao, L., Ye, Q., and Zhao, X. (2014). Online Spatial Normalization for Real-Time fMRI. PloS One, 9(7), e103302.
    Link
  • Hui, M., Zhang, H., Ge, R., Yao, L., and Long, Z. (2014). Modulation of functional network with real-time fMRI feedback training of right premotor cortex activity. Neuropsychologia, 62, 111–123.
    Link
  • Rance, M., Ruttorf, M., Nees, F., Schad, L. R., and 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.
    Link
  • 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.
    Link
  • Kober, S. E., Wood, G., Kurzmann, J., Friedrich, E. V. C., Stangl, M., Wippel, T., … Neuper, C. (2014). Near-infrared spectroscopy based neurofeedback training increases specific motor imagery related cortical activation compared to sham feedback. Biological Psychology, 95, 21–30.
    Link
  • Clark, V. P., and Parasuraman, R. (2014). Neuroenhancement: enhancing brain and mind in health and in disease. Elsevier.
    Link
  • Raspopovic, S., Capogrosso, M., Petrini, F. M., Bonizzato, M., Rigosa, J., Di Pino, G., … others. (2014). Restoring natural sensory feedback in real-time bidirectional hand prostheses. Science Translational Medicine, 6(222), 222ra19–222ra19.
    Link
  • Ros, T., Munneke, M. A. M., Parkinson, L. A., and Gruzelier, J. H. (2014). Neurofeedback facilitation of implicit motor learning. Biological Psychology, 95, 54–58.
    Link
  • Grefkes, C., and Ward, N. S. (2014). Cortical reorganization after stroke: how much and how functional? The Neuroscientist, 20(1), 56–70.
    Link
  • Kaiser, V., Bauernfeind, G., Kreilinger, A., Kaufmann, T., Kübler, A., Neuper, C., and Müller-Putz, G. R. (2014). Cortical effects of user training in a motor imagery based brain–computer interface measured by fNIRS and EEG. Neuroimage, 85, 432–444.
    Link
  • Lefebvre, S., Thonnard, J.-L., Laloux, P., Peeters, A., Jamart, J., and Vandermeeren, Y. (2014). Single session of dual-tDCS transiently improves precision grip and dexterity of the paretic hand after stroke. Neurorehabilitation and Neural Repair, 28(2), 100–110.
    Link
  • Nozari, N., Woodard, K., and Thompson-Schill, S. L. (2014). Consequences of cathodal stimulation for behavior: when does it help and when does it hurt performance? PLoS One, 9(1), e84338.
    Link
  • Narayana, S., Zhang, W., Rogers, W., Strickland, C., Franklin, C., Lancaster, J. L., and Fox, P. T. (2014). Concurrent TMS to the primary motor cortex augments slow motor learning. Neuroimage, 85, 971–984.
    Link
  • Linden, D. E. J. (2014). Neurofeedback and networks of depression. Dialogues in Clinical Neuroscience, 16(1), 103.
    Link
  • 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.
    Link
  • 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.
    Link
  • Yuan, H., Young, K. D., Phillips, R., Zotev, V., Misaki, M., and 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.
    Link
  • 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.
    Link
  • Ruiz, S., Birbaumer, N., and Sitaram, R. (2014). Volitional control of neural connectivity. In Brain-Computer Interface Research, pages 63–74. Springer.
    Link
  • Goebel, R., and Linden, D. (2014). Neurofeedback with real-time functional MRI. In MRI in Psychiatry, pages 35–46. Springer.
    Link
  • 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.
    Link
  • 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.
    Link
  • Fan, J. M., Nuyujukian, P., Kao, J. C., Chestek, C. A., Ryu, S. I., and Shenoy, K. V. (2014). Intention estimation in brain–machine interfaces. Journal of Neural Engineering, 11(1), 016004.
    Link
  • So, K., Dangi, S., Orsborn, A. L., Gastpar, M. C., and Carmena, J. M. (2014). Subject-specific modulation of local field potential spectral power during brain–machine interface control in primates. Journal of Neural Engineering, 11(2), 026002.
    Link
  • Gruzelier, J. H. (2014). Differential effects on mood of 12–15 (SMR) and 15–18 (beta1) Hz neurofeedback. International Journal of Psychophysiology, 93(1), 112–115.
    Link
  • Petrov, Y., Nador, J., Hughes, C., Tran, S., Yavuzcetin, O., and Sridhar, S. (2014). Ultra-dense EEG sampling results in two-fold increase of functional brain information. NeuroImage, 90, 140–145.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • 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.
    Link
  • Brem, A.-K., Fried, P. J., Horvath, J. C., Robertson, E. M., and Pascual-Leone, A. (2014). Is neuroenhancement by noninvasive brain stimulation a net zero-sum proposition? Neuroimage, 85, 1058–1068.
    Link
  • Kaufman, M. T., Churchland, M. M., Ryu, S. I., and Shenoy, K. V. (2014). Cortical activity in the null space: permitting preparation without movement. Nature Neuroscience, 17(3), 440–448.
    Link
  • 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.
    Link
  • 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.
    Link
  • Zotev, V., Phillips, R., Yuan, H., Misaki, M., and Bodurka, J. (2014). Self-regulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback. NeuroImage, 85, 985–995.
    Link
  • 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.
    Link
  • 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.
    Link
  • Leuze, C. W. U., Anwander, A., Bazin, P.-L., Dhital, B., Stüber, C., Reimann, K., … Turner, R. (2014). Layer-specific intracortical connectivity revealed with diffusion MRI. Cerebral Cortex, 24(2), 328–339.
    Link
  • 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.
    Link

    • 2013

  • Feis, D.-L., Brodersen, K. H., von Cramon, D. Y., Luders, E., and Tittgemeyer, M. (2013). Decoding gender dimorphism of the human brain using multimodal anatomical and diffusion MRI data. Neuroimage, 70, 250–257.
    Link
  • Ruiz, S., Lee, S., Soekadar, S. R., Caria, A., Veit, R., Kircher, T., … Sitaram, R. (2013). Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia. Human Brain Mapping, 34(1), 200–212.
    Link
  • Sulzer, J., Sitaram, R., Blefari, M. L., Kollias, S., Birbaumer, N., Stephan, K. E., … Gassert, R. (2013). Neurofeedback-mediated self-regulation of the dopaminergic midbrain. Neuroimage, 83, 817–825.
    Link
  • Kober, S. E., Witte, M., Ninaus, M., Neuper, C., and Wood, G. (2013). Learning to modulate one’s own brain activity: the effect of spontaneous mental strategies.
    Link
  • Mihara, M., Hattori, N., Hatakenaka, M., Yagura, H., Kawano, T., Hino, T., and Miyai, I. (2013). Near-infrared Spectroscopy–mediated Neurofeedback Enhances Efficacy of Motor Imagery–based Training in Poststroke Victims. Stroke, 44(4), 1091–1098.
    Link
  • Niv, S. (2013). Clinical efficacy and potential mechanisms of neurofeedback. Personality and Individual Differences, 54(6), 676–686.
    Link
  • Gruet, M., Temesi, J., Rupp, T., Levy, P., Millet, G. Y., and Verges, S. (2013). Stimulation of the motor cortex and corticospinal tract to assess human muscle fatigue. Neuroscience, 231, 384–399.
    Link
  • Chapin, H., and Mackey, S. (2013). A Transparent, Trainable Brain. Scientific American Mind, 24(1), 50–57.
    Link
  • Craddock, R. C., Jbabdi, S., Yan, C.-G., Vogelstein, J. T., Castellanos, F. X., Di Martino, A., … Milham, M. P. (2013). Imaging human connectomes at the macroscale. Nature Methods, 10(6), 524–539.
    Link
  • Grosse-Wentrup, M., and Schölkopf, B. (2013). A review of performance variations in SMR-based brain- computer interfaces (BCIs). In Brain-Computer Interface Research, pages 39–51. Springer.
    Link
  • Sulzer, J., Haller, S., Scharnowski, F., Weiskopf, N., Birbaumer, N., Blefari, M. L., … others. (2013). Real-time fMRI neurofeedback: progress and challenges. Neuroimage, 76, 386–399.
    Link
  • Andersson, P., Pluim, J. P. W., Viergever, M. A., and Ramsey, N. F. (2013). Navigation of a telepresence robot via covert visuospatial attention and real-time fMRI. Brain Topography, 26(1), 177–185.
    Link
  • Hinds, O., Thompson, T. W., Ghosh, S., Yoo, J. J., Whitfield-Gabrieli, S., Triantafyllou, C., and Gabrieli, J. D. E. (2013). Roles of default-mode network and supplementary motor area in human vigilance performance: evidence from real-time fMRI. Journal of Neurophysiology, 109(5), 1250–1258.
    Link
  • Andersson, P., Pluim, J. P. W., Viergever, M. A., and Ramsey, N. F. (2013). Navigation of a telepresence robot via covert visuospatial attention and real-time fMRI. Brain Topography, 26(1), 177–185.
    Link
  • Halder, S., Varkuti, B., Bogdan, M., Kübler, A., Rosenstiel, W., Sitaram, R., and Birbaumer, N. (2013). Prediction of brain-computer interface aptitude from individual brain structure.
    Link
  • Papageorgiou, T. D., Lisinski, J. M., McHenry, M. A., White, J. P., and LaConte, S. M. (2013). Brain–computer interfaces increase whole-brain signal to noise. Proceedings of the National Academy of Sciences, 110(33), 13630–13635.
    Link
  • Richiardi, J., Achard, S., Bunke, H., and Van De Ville, D. (2013). Machine learning with brain graphs: predictive modeling approaches for functional imaging in systems neuroscience. IEEE Signal Processing Magazine, 30(3), 58–70.
    Link
  • Soldati, N., Calhoun, V. D., Bruzzone, L., and Jovicich, J. (2013). ICA analysis of fMRI with real-time constraints: an evaluation of fast detection performance as function of algorithms, parameters and a priori conditions. Frontiers in Human Neuroscience, 7, 19.
    Link
  • Zheng, W., Ackley, E. S., Martı́nez-Ramón Manel, and Posse, S. (2013). Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas. Magnetic Resonance Imaging, 31(2), 247–261.
    Link
  • Buckner, R. L., Krienen, F. M., and Yeo, B. T. T. (2013). Opportunities and limitations of intrinsic functional connectivity MRI. Nature Neuroscience, 16(7), 832–837.
    Link
  • Koush, Y., Rosa, M. J., Robineau, F., Heinen, K., Rieger, S. W., Weiskopf, N., … Scharnowski, F. (2013). Connectivity-based neurofeedback: dynamic causal modeling for real-time fMRI. Neuroimage, 81, 422–430.
    Link
  • Ros, T., Théberge, J., Frewen, P. A., Kluetsch, R., Densmore, M., Calhoun, V. D., and Lanius, R. A. (2013). Mind over chatter: plastic up-regulation of the fMRI salience network directly after EEG neurofeedback. Neuroimage, 65, 324–335.
    Link
  • Müller, K., Bacht, K., Prochnow, D., Schramm, S., and Seitz, R. J. (2013). Activation of thalamus in motor imagery results from gating by hypnosis. Neuroimage, 66, 361–367.
    Link
  • Nierhaus, T., Gundlach, C., Goltz, D., Thiel, S. D., Pleger, B., and Villringer, A. (2013). Internal ventilation system of MR scanners induces specific EEG artifact during simultaneous EEG-fMRI. Neuroimage, 74, 70–76.
    Link
  • Plichta, M. M., Wolf, I., Hohmann, S., Baumeister, S., Boecker, R., Schwarz, A. J., … others. (2013). Simultaneous EEG and fMRI reveals a causally connected subcortical-cortical network during reward anticipation. Journal of Neuroscience, 33(36), 14526–14533.
    Link
  • Berman, B. D., Horovitz, S. G., and Hallett, M. (2013). Modulation of functionally localized right insular cortex activity using real-time fMRI-based neurofeedback. Frontiers in Human Neuroscience, 7, 638.
    Link
  • Brewer, J. A., Garrison, K. A., and Whitfield-Gabrieli, S. (2013). What about the “self” is processed in the posterior cingulate cortex?
    Link
  • Garrison, K. A., Scheinost, D., Worhunsky, P. D., Elwafi, H. M., Thornhill, T. A., Thompson, E., … others. (2013). Real-time fMRI links subjective experience with brain activity during focused attention. Neuroimage, 81, 110–118.
    Link
  • Rana, M., Gupta, N., Lee, S., and others. (2013). A toolbox for real-time subject-independent and subject-dependent classification of brain states from fMRI signals. Frontiers in Neuroscience, 7, 170.
    Link
  • Chen, A., Yao, J., Kuiken, T., and Dewald, J. P. A. (2013). Cortical motor activity and reorganization following upper-limb amputation and subsequent targeted reinnervation. NeuroImage: Clinical, 3, 498–506.
    Link
  • Seitz, A. R. (2013). Cognitive neuroscience: targeting neuroplasticity with neural decoding and biofeedback. Current Biology, 23(5), R210–R212.
    Link
  • Lohmann, G., Stelzer, J., Neumann, J., Ay, N., and Turner, R. (2013). “More is different” in functional magnetic resonance imaging: a review of recent data analysis techniques. Brain Connectivity, 3(3), 223–239.
    Link
  • Scheinost, D., Hampson, M., Qiu, M., Bhawnani, J., Constable, R. T., and Papademetris, X. (2013). A graphics processing unit accelerated motion correction algorithm and modular system for real-time fMRI. Neuroinformatics, 11(3), 291–300.
    Link
  • Koush, Y., Elliott, M. A., Scharnowski, F., and Mathiak, K. (2013). Real-time automated spectral assessment of the BOLD response for neurofeedback at 3 and 7T. Journal of Neuroscience Methods, 218(2), 148–160.
    Link
  • Scheinost, D., Hampson, M., Qiu, M., Bhawnani, J., Constable, R. T., and Papademetris, X. (2013). A graphics processing unit accelerated motion correction algorithm and modular system for real-time fMRI. Neuroinformatics, 11(3), 291–300.
    Link
  • Can, D. D., Richards, T., and Kuhl, P. K. (2013). Early gray-matter and white-matter concentration in infancy predict later language skills: a whole brain voxel-based morphometry study. Brain and Language, 124(1), 34–44.
    Link

    • 2012

  • Cohen, O., Druon, S., Lengagne, S., Mendelsohn, A., Malach, R., Kheddar, A., and Friedman, D. (2012). fMRI robotic embodiment: a pilot study. In Biomedical Robotics and Biomechatronics (BioRob), 2012 4th IEEE RAS & EMBS International Conference on, pages 314–319. IEEE.
    Link
  • Weygandt, M., Blecker, C. R., Schäfer, A., Hackmack, K., Haynes, J.-D., Vaitl, D., … Schienle, A. (2012). fMRI pattern recognition in obsessive–compulsive disorder. Neuroimage, 60(2), 1186–1193.
    Link
  • Chapin, H., Bagarinao, E., and Mackey, S. (2012). Real-time fMRI applied to pain management. Neuroscience Letters, 520(2), 174–181.
    Link
  • McCarthy-Jones, S. (2012). Taking back the brain: could neurofeedback training be effective for relieving distressing auditory verbal hallucinations in patients with schizophrenia? Schizophrenia Bulletin, sbs006.
    Link
  • Sitaram, R., Veit, R., Stevens, B., Caria, A., Gerloff, C., Birbaumer, N., and Hummel, F. (2012). Acquired control of ventral premotor cortex activity by feedback training an exploratory real-time fMRI and TMS study. Neurorehabilitation and Neural Repair, 26(3), 256–265.
    Link
  • Freyer, F., Reinacher, M., Nolte, G., Dinse, H. R., and Ritter, P. (2012). Repetitive tactile stimulation changes resting-state functional connectivity—implications for treatment of sensorimotor decline. Frontiers in Human Neuroscience, 6, 144.
    Link
  • Frank, S., Lee, S., Preissl, H., Schultes, B., Birbaumer, N., and Veit, R. (2012). The obese brain athlete: self-regulation of the anterior insula in adiposity. PLoS One, 7(8), e42570.
    Link
  • Johnson, K. A., Hartwell, K., LeMatty, T., Borckardt, J., Morgan, P. S., Govindarajan, K., … George, M. S. (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.
    Link
  • Van De Ville, D., Jhooti, P., Haas, T., Kopel, R., Lovblad, K.-O., Scheffler, K., and Haller, S. (2012). Recovery of the default mode network after demanding neurofeedback training occurs in spatio-temporally segregated subnetworks. Neuroimage, 63(4), 1775–1781.
    Link
  • Mihara, M., Miyai, I., Hattori, N., Hatakenaka, M., Yagura, H., Kawano, T., … others. (2012). Neurofeedback using real-time near-infrared spectroscopy enhances motor imagery related cortical activation. PloS One, 7(3), e32234.
    Link
  • Buch, E. R., Shanechi, A. M., Fourkas, A. D., Weber, C., Birbaumer, N., and Cohen, L. G. (2012). Parietofrontal integrity determines neural modulation associated with grasping imagery after stroke. Brain, awr331.
    Link
  • Jezzini, A., Caruana, F., Stoianov, I., Gallese, V., and Rizzolatti, G. (2012). Functional organization of the insula and inner perisylvian regions. Proceedings of the National Academy of Sciences, 109(25), 10077–10082.
    Link
  • Koralek, A. C., Jin, X., Long II, J. D., Costa, R. M., and Carmena, J. M. (2012). Corticostriatal plasticity is necessary for learning intentional neuroprosthetic skills. Nature, 483(7389), 331–335.
    Link
  • Schurger, A., Sitt, J. D., and Dehaene, S. (2012). An accumulator model for spontaneous neural activity prior to self-initiated movement. Proceedings of the National Academy of Sciences, 109(42), E2904–E2913.
    Link
  • Linden, D. E. J. (2012). The challenges and promise of neuroimaging in psychiatry. Neuron, 73(1), 8–22.
    Link
  • Zatorre, R. J., Fields, R. D., and Johansen-Berg, H. (2012). Plasticity in gray and white: neuroimaging changes in brain structure during learning. Nature Neuroscience, 15(4), 528–536.
    Link
  • Fox, P. T., and Friston, K. J. (2012). Distributed processing; distributed functions? Neuroimage, 61(2), 407–426.
    Link
  • Linden, D. E. J. (2012). The challenges and promise of neuroimaging in psychiatry. Neuron, 73(1), 8–22.
    Link
  • Behrens, T. E. J., and Sporns, O. (2012). Human connectomics. Current Opinion in Neurobiology, 22(1), 144–153.
    Link
  • Stephan, K. E., and Roebroeck, A. (2012). A short history of causal modeling of fMRI data. Neuroimage, 62(2), 856–863.
    Link
  • Caria, A., Sitaram, R., and Birbaumer, N. (2012). Real-time fMRI: a tool for local brain regulation. The Neuroscientist, 18(5), 487–501.
    Link
  • Bandettini, P. A. (2012). Twenty years of functional MRI: the science and the stories. Neuroimage, 62(2), 575–588.
    Link
  • Bullmore, E. (2012). The future of functional MRI in clinical medicine. Neuroimage, 62(2), 1267–1271.
    Link
  • Smith, S. M. (2012). The future of FMRI connectivity. Neuroimage, 62(2), 1257–1266.
    Link
  • Donahue, M. J., Hoogduin, H., Smith, S. M., Siero, J. C. W., Chappell, M., Petridou, N., … Hendrikse, J. (2012). Spontaneous blood oxygenation level-dependent fMRI signal is modulated by behavioral state and correlates with evoked response in sensorimotor cortex: A 7.0-T fMRI study. Human Brain Mapping, 33(3), 511–522.
    Link
  • Ramos-Murguialday, A., Schürholz, M., Caggiano, V., Wildgruber, M., Caria, A., Hammer, E. M., … Birbaumer, N. (2012). Proprioceptive feedback and brain computer interface (BCI) based neuroprostheses. PloS One, 7(10), e47048.
    Link
  • Friedrich, E. V. C., Scherer, R., and Neuper, C. (2012). The effect of distinct mental strategies on classification performance for brain–computer interfaces. International Journal of Psychophysiology, 84(1), 86–94.
    Link
  • Lance, B. J., Kerick, S. E., Ries, A. J., Oie, K. S., and McDowell, K. (2012). Brain–computer interface technologies in the coming decades. Proceedings of the IEEE, 100(Special Centennial Issue), 1585–1599.
    Link
  • Minati, L., Nigri, A., Rosazza, C., and Bruzzone, M. G. (2012). Thoughts turned into high-level commands: Proof-of-concept study of a vision-guided robot arm driven by functional MRI (fMRI) signals. Medical Engineering & Physics, 34(5), 650–658.
    Link
  • Sorger, B., Reithler, J., Dahmen, B., and Goebel, R. (2012). A real-time fMRI-based spelling device immediately enabling robust motor-independent communication. Current Biology, 22(14), 1333–1338.
    Link
  • Anderson, A., Han, D., Douglas, P. K., Bramen, J., and Cohen, M. S. (2012). Real-time functional MRI classification of brain states using markov-svm hybrid models: peering inside the rt-fMRI black box. In Machine learning and interpretation in neuroimaging, pages 242–255. Springer.
    Link
  • Chiew, M., LaConte, S. M., and Graham, S. J. (2012). Investigation of fMRI neurofeedback of differential primary motor cortex activity using kinesthetic motor imagery. NeuroImage, 61(1), 21–31.
    Link
  • Coutanche, M. N., and Thompson-Schill, S. L. (2012). The advantage of brief fMRI acquisition runs for multi-voxel pattern detection across runs. Neuroimage, 61(4), 1113–1119.
    Link
  • Lee, J.-H., Kim, J., and Yoo, S.-S. (2012). Real-time fMRI-based neurofeedback reinforces causality of attention networks. Neuroscience Research, 72(4), 347–354.
    Link
  • Seth, S., and Principe, J. C. (2012). Assessing Granger non-causality using nonparametric measure of conditional independence. IEEE Transactions on Neural Networks and Learning Systems, 23(1), 47–59.
    Link
  • Magri, C., Schridde, U., Murayama, Y., Panzeri, S., and Logothetis, N. K. (2012). The amplitude and timing of the BOLD signal reflects the relationship between local field potential power at different frequencies. Journal of Neuroscience, 32(4), 1395–1407.
    Link
  • Mandeville, J. B. (2012). IRON fMRI measurements of CBV and implications for BOLD signal. Neuroimage, 62(2), 1000–1008.
    Link
  • Zotev, V., Yuan, H., Phillips, R., and Bodurka, J. (2012). EEG-assisted retrospective motion correction for fMRI: E-REMCOR. NeuroImage, 63(2), 698–712.
    Link
  • Huster, R. J., Debener, S., Eichele, T., and Herrmann, C. S. (2012). Methods for simultaneous EEG-fMRI: an introductory review. Journal of Neuroscience, 32(18), 6053–6060.
    Link
  • Cloos, M. A., Boulant, N., Luong, M., Ferrand, G., Giacomini, E., Hang, M.-F., … Amadon, A. (2012). Parallel-transmission-enabled magnetization-prepared rapid gradient-echo T1-weighted imaging of the human brain at 7T. Neuroimage, 62(3), 2140–2150.
    Link
  • Jezzard, P. (2012). Correction of geometric distortion in fMRI data. Neuroimage, 62(2), 648–651.
    Link
  • Mueller, C., Luehrs, M., Baecke, S., Adolf, D., Luetzkendorf, R., Luchtmann, M., and Bernarding, J. (2012). Building virtual reality fMRI paradigms: a framework for presenting immersive virtual environments. Journal of Neuroscience Methods, 209(2), 290–298.
    Link
  • Aqil, M., Hong, K.-S., Jeong, M.-Y., and Ge, S. S. (2012). Cortical brain imaging by adaptive filtering of NIRS signals. Neuroscience Letters, 514(1), 35–41.
    Link
  • Ferrari, M., and Quaresima, V. (2012). A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. Neuroimage, 63(2), 921–935.
    Link
  • Fox, M. D., Halko, M. A., Eldaief, M. C., and Pascual-Leone, A. (2012). Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS). Neuroimage, 62(4), 2232–2243.
    Link
  • Guillot, A., Di Rienzo, F., MacIntyre, T., Moran, A., and Collet, C. (2012). Imagining is not doing but involves specific motor commands: a review of experimental data related to motor inhibition. Frontiers in Human Neuroscience, 6, 247.
    Link
  • Plenge, E., Poot, D. H. J., Bernsen, M., Kotek, G., Houston, G., Wielopolski, P., … Meijering, E. (2012). Super-resolution methods in MRI: Can they improve the trade-off between resolution, signal-to-noise ratio, and acquisition time? Magnetic Resonance in Medicine, 68(6), 1983–1993.
    Link
  • Posse, S., Ackley, E., Mutihac, R., Rick, J., Shane, M., Murray-Krezan, C., … Speck, O. (2012). Enhancement of temporal resolution and BOLD sensitivity in real-time fMRI using multi-slab echo-volumar imaging. Neuroimage, 61(1), 115–130.
    Link
  • Posse, S. (2012). Multi-echo acquisition. Neuroimage, 62(2), 665–671.
    Link
  • van Gelderen, P., Duyn, J. H., Ramsey, N. F., Liu, G., and Moonen, C. T. W. (2012). The PRESTO technique for fMRI. Neuroimage, 62(2), 676–681.
    Link
  • Boynton, G. M., Engel, S. A., and Heeger, D. J. (2012). Linear systems analysis of the fMRI signal. NeuroImage, 62(2), 975–984.
    Link
  • Eklund, A., Andersson, M., Josephson, C., Johannesson, M., and Knutsson, H. (2012). Does parametric fMRI analysis with SPM yield valid results?—An empirical study of 1484 rest datasets. NeuroImage, 61(3), 565–578.
    Link
  • Goebel, R. (2012). BrainVoyager—past, present, future. Neuroimage, 62(2), 748–756.
    Link
  • Zang, Z.-X., Yan, C.-G., Dong, Z.-Y., Huang, J., and Zang, Y.-F. (2012). Granger causality analysis implementation on MATLAB: a graphic user interface toolkit for fMRI data processing. Journal of Neuroscience Methods, 203(2), 418–426.
    Link
  • Koush, Y., Zvyagintsev, M., Dyck, M., Mathiak, K. A., and Mathiak, K. (2012). Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI. Neuroimage, 59(1), 478–489.
    Link
  • Polanı́a Rafael, Paulus, W., and Nitsche, M. A. (2012). Reorganizing the intrinsic functional architecture of the human primary motor cortex during rest with non-invasive cortical stimulation. PloS One, 7(1), e30971.
    Link
  • Weiss, M., and Lavidor, M. (2012). When less is more: evidence for a facilitative cathodal tDCS effect in attentional abilities. Journal of Cognitive Neuroscience, 24(9), 1826–1833.
    Link
  • Silvanto, J., and Pascual-Leone, A. (2012). Why the assessment of causality in brain–behavior relations requires brain stimulation. Journal of Cognitive Neuroscience, 24(4), 775–777.
    Link

    • 2011

  • Shibata, K., Watanabe, T., Sasaki, Y., and Kawato, M. (2011). Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation. Science, 334(6061), 1413–1415.
    Link
  • Hampson, M., Scheinost, D., Qiu, M., Bhawnani, J., Lacadie, C. M., Leckman, J. F., … Papademetris, X. (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), 91–98.
    Link
  • Hampson, M., Scheinost, D., Qiu, M., Bhawnani, J., Lacadie, C. M., Leckman, J. F., … Papademetris, X. (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), 91–98.
    Link
  • Koush, Y., Elliott, M. A., and Mathiak, K. (2011). Single voxel proton spectroscopy for neurofeedback at 7 Tesla. Materials, 4(9), 1548–1563.
    Link
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