An Artistic Approach to Neurofeedback for Emotion Regulation

  • Damien Gabriel centre d investigation clinique inserm CIC 1431
  • Thibault Chabin
  • Coralie Joucla
  • Thomas Bussière
  • Aleksandra Tarka
  • Nathan Galmes
  • Alexandre Comte
  • Guillaume Bertrand
  • Julie Giustiniani
  • Emmanuel Haffen
Keywords: neurofeedback, emotion, art


While literature has suggested that neurofeedback performance improves when sensory feedback is related to the pathology under consideration, it is still difficult to represent a proper feedback representative of our emotional state.  In this study, we have initiated a collaboration between neuroscientists and artists to develop a visual representation of emotions.  Emotions were represented as particles moving in a white sphere according to valence and arousal levels.  Several possibilities for particle control were explored: direction of particles, their concentration in a specific place, or their gravity.  Participants were asked to evaluate these possibilities on scales ranging from 0 to 5 on how artistic the different representations were and could be used as a clinical activity, whether they thought they had successfully controlled the particles during the neurofeedback exercise, and whether they had appreciated the experience.  We found that controlling the direction and concentration of particles was considered the most artistic, with an average score around 3 out of 5, and that 47% of the 107 participants considered the concentration of particles as artistic.  In addition, we found that participants could significantly control the direction of particles during this session.  Our approach constitutes a first step before evaluating the effectiveness of our emotional neurofeedback over several sessions.


Aftanas, L. I., & Golocheikine, S. A. (2001). Human anterior and frontal midline theta and lower alpha reflect emotionally positive state and internalized attention: High-resolution EEG investigation of meditation. Neuroscience Letters, 310(1), 57–60.

Arjmand, H.-A., Hohagen, J., Paton, B., & Rickard, N. S. (2017). Emotional responses to music: Shifts in frontal brain asymmetry mark periods of musical change. Frontiers in Psychology, 8, 2044.

Arns, M., Batail, J.-M., Bioulac, S., Congedo, M., Daudet, C., Drapier, D., … The NExT group. (2017). Neurofeedback: One of today’s techniques in psychiatry? L’Encéphale, 43(2), 135–145.

Arns, M., Heinrich, H., & Strehl, U. (2014). Evaluation of neurofeedback in ADHD: The long and winding road. Biological Psychology, 95, 108–115.

Baehr, E., & Baehr, R. (1997). The use of brainwave biofeedback as an adjunctive therapeutic treatment for depression: Three case studies. Biofeedback, 25(1), 10–11.

Baehr, E., Rosenfeld, J. P., & Baehr, R. (1997). The clinical use of an alpha asymmetry protocol in the neurofeedback treatment of depression: Two case studies. Journal of Neurotherapy, 2, 10–23.

Bagdasaryan, J., & Quyen, M. L. V. (2013). Experiencing your brain: Neurofeedback as a new bridge between neuroscience and phenomenology. Frontiers in Human Neuroscience, 7, 680.

Bandura, A. (1999). Moral disengagement in the perpetration of inhumanities. Personality and Social Psychology Review, 3(3), 193–209.

Bayliss, J. D., Inverso, S. A., & Tentler, A. (2004). Changing the P300 brain computer interface. CyberPsychology & Behavior, 7(6), 694–704.

Caria, A., Sitaram, R., Veit, R., Begliomini, C., & Birbaumer, N. (2010). Volitional control of anterior insula activity modulates the response to aversive stimuli. A real-time functional magnetic resonance imaging study. Biological Psychiatry, 68(5), 425–432.

Caria, A., Veit, R., Sitaram, R., Lotze, M., Weiskopf, N., Grodd, W., & Birbaumer, N. (2007). Regulation of anterior insular cortex activity using real-time fMRI. NeuroImage, 35(3), 1238–1246.

Cavazza, M., Aranyi, G., Charles, F., Porteous, J., Gilroy, S., Klovatch, I., … Hendler, T. (2014). Towards empathic neurofeedback for interactive storytelling. Open Access Series in Informatics, 42–60.

Choi, S. W., Chi, S. E., Chung, S. Y., Kim, J. W., Ahn, C. Y., & Kim, H. T. (2011). Is alpha wave neurofeedback effective with randomized clinical trials in depression? A pilot study. Neuropsychobiology, 63(1), 43–51.

Coan, J. A., & Allen, J. J. B. (2004). Frontal EEG asymmetry as a moderator and mediator of emotion. Biological Psychology, 67(1–2), 7–50.

Cook, I. A., O’Hara, R., Uijtdehaage, S. H. J., Mandelkern, M., & Leuchter, A. F. (1998). Assessing the accuracy of topographic EEG mapping for determining local brain function. Electroencephalography and Clinical Neurophysiology, 107(6), 408–414.

Cunningham, W. A., Arbuckle, N. L., Jahn, A., Mowrer, S. M., & Abduljalil, A. M. (2010). Aspects of neuroticism and the amygdala: Chronic tuning from motivational styles. Neuropsychologia, 48(12), 3399–3404.

Cunningham, W. A., Raye, C. L., & Johnson, M. K. (2005). Neural

correlates of evaluation associated with promotion and prevention regulatory focus. Cognitive, Affective, & Behavioral Neuroscience, 5(2), 202–211.

Davidson, R. J. (1988). EEG measures of cerebral asymmetry: Conceptual and methodological issues. International Journal of Neuroscience, 39(1–2), 71–89.

Davidson, R. J. (1992). Anterior cerebral asymmetry and the nature of emotion. Brain and Cognition, 20(1), 125–151.

Davidson, R. J. (1998). Anterior electrophysiological asymmetries, emotion, and depression: Conceptual and methodological conundrums. Psychophysiology, 35(5), 607–614.

Davidson, R. J., Ekman, P., Saron, C. D., Senulis, J. A., & Friesen, W. V. (1990). Approach-withdrawal and cerebral asymmetry: Emotional expression and brain physiology: I. Journal of Personality and Social Psychology, 58(2), 330–341.

deCharms, R. C. (2008). Applications of real-time fMRI. Nature Reviews Neuroscience, 9(9), 720–729.

Dikker, S., Wan, L., Davidesco, I., Kaggen, L., Oostrik, M., McClintock, J., … Poeppel, D. (2017). Brain-to-brain synchrony tracks real-world dynamic group interactions in the classroom. Current Biology, 27(9), 1375–1380.

Ertl, M., Hildebrandt, M., Ourina, K., Leicht, G., & Mulert, C. (2013). Emotion regulation by cognitive reappraisal—The role of frontal theta oscillations. NeuroImage, 81, 412–421.

Gaume, A., Vialatte, A., Mora-Sánchez, A., Ramdani, C., & Vialatte, F. B. (2016). A psychoengineering paradigm for the neurocognitive mechanisms of biofeedback and neurofeedback. Neuroscience & Biobehavioral Reviews, 68, 891–910.

Grandchamp, R., & Delorme, A. (2016). The brainarium: An interactive immersive tool for brain education, art, and neurotherapy. Computational Intelligence and Neuroscience, 4204385.

Gruzelier, J. H. (2014). EEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants. Neuroscience & Biobehavioral Reviews, 44, 124–141.

Gruzelier, J. H. (2018). Enhancing creativity with neurofeedback in the performing arts: Actors, musicians, dancers. In S. Burgoyne (Eds.), Creativity in theatre. Creativity theory and action in education (Vol. 2). New York, NY: Springer.

Harmon-Jones, E., & Gable, P. A. (2018). On the role of asymmetric frontal cortical activity in approach and withdrawal motivation: An updated review of the evidence. Psychophysiology, 55(1), e12879.

Kinreich, S., Podlipsky, I., Jamshy, S., Intrator, N., & Hendler, T. (2014). Neural dynamics necessary and sufficient for transition into pre-sleep induced by EEG neurofeedback. NeuroImage, 97, 19–28.

Koush, Y., Meskaldji, D.-E., Pichon, S., Rey, G., Rieger, S. W., Linden, D. E. J., … Scharnowski, F. (2017). Learning control over emotion networks through connectivity-based neurofeedback. Cerebral Cortex, 27(2), 1193–1202.

Kovacevic, N., Ritter, P., Tays, W., Moreno, S., & McIntosh, A. R. (2015). "My Virtual Dream": Collective neurofeedback in an immersive art environment. PLoS ONE, 10(7), e0130129.

Linden, D. (2013). Biological psychiatry: Time for new paradigms. The British Journal of Psychiatry, 202(3), 166–167.

Linden, D. E. J. (2014). Neurofeedback and networks of depression. Dialogues in Clinical Neuroscience, 16(1), 103–112.

Linhartová, P., Látalová, A., Kóša, B., Kašpárek, T., Schmahl, C., & Paret, C. (2019). fMRI neurofeedback in emotion regulation: A literature review. NeuroImage, 193, 75–92.

Lorenzetti, V., Melo, B., Basílio, R., Suo, C., Yücel, M., Tierra-Criollo, C. J., & Moll, J. (2018). Emotion regulation using virtual environments and real-time fMRI neurofeedback. Frontiers in Neurology, 9, 390.

Lubianiker, N., Goldway, N., Fruchtman-Steinbok, T., Paret, C., Keynan, J. N., Singer, N., … Hendler, T. (2019). Process-based framework for precise neuromodulation. Nature Human Behaviour, 3(5), 436–445.

Marzbani, H., Marateb, H. R., & Mansourian, M. (2016). Neurofeedback: A comprehensive review on system design, methodology and clinical applications. Basic and Clinical Neuroscience, 7(2), 143–158.

Meir-Hasson, Y., Kinreich, S., Podlipsky, I., Hendler, T., & Intrator, N. (2014). An EEG finger-print of fMRI deep regional activation. NeuroImage, 102(1), 128–141.

Micoulaud-Franchi, J.-A., & Fovet, T. (2016). Neurofeedback: Time needed for a promising non-pharmacological therapeutic method. The Lancet Psychiatry, 3(9), e16.

Micoulaud-Franchi, J.-A., & Fovet, T. (2018). A framework for disentangling the hyperbolic truth of neurofeedback: Comment on Thibault and Raz (2017). The American Psychologist, 73(7), 933–935.

Micoulaud-Franchi, J.-A., McGonigal, A., Lopez, R., Daudet, C., Kotwas, I., & Bartolomei, F. (2015). Electroencephalographic neurofeedback: Level of evidence in mental and brain disorders and suggestions for good clinical practice. Neurophysiologie Clinique/Clinical Neurophysiology, 45(6), 423–433.

Oude Bos, D., & Reuderink, B. (2008). BrainBasher: A BCI game. In Extended Abstracts of the International Conference on Fun and Games 2008, Eindhoven, Netherlands (pp. 36–39). Einhoven, Netherlands: Eindhoven University of Technology.

Papousek, I., Weiss, E. M., Schulter, G., Fink, A., Reiser, E. M., & Lackner, H. K. (2014). Prefrontal EEG alpha asymmetry changes while observing disaster happening to other people: Cardiac correlates and prediction of emotional impact. Biological Psychology, 103, 184–194.

Paquette, V., Beauregard, M., & Beaulieu-Prévost, D. (2009). Effect of a psychoneurotherapy on brain electromagnetic tomography in individuals with major depressive disorder. Psychiatry Research: Neuroimaging, 174(3), 231–239.

Paret, C., Goldway, N., Zich, C., Keynan, J. N., Hendler, T., Linden, D., & Cohen Kadosh, K. (2019). Current progress in real-time functional magnetic resonance-based neurofeedback: Methodological challenges and achievements. NeuroImage, 202, 116107.

Peeters, F., Oehlen, M., Ronner, J., van Os, J., & Lousberg, R. (2014). Neurofeedback as a treatment for major depressive disorder—A pilot study. PLoS ONE, 9(3), e91837.

Pizzagalli, D. A., Nitschke, J. B., Oakes, T. R., Hendrick, A. M., Horras, K. A., Larson, C. L., … Davidson, R. J. (2002). Brain electrical tomography in depression: The importance of symptom severity, anxiety, and melancholic features. Biological Psychiatry, 52(2), 73–85.

Ramirez, R., Palencia-Lefler, M., Giraldo, S., & Vamvakousis, Z. (2015). Musical neurofeedback for treating depression in elderly people. Frontiers in Neuroscience, 9, 354.

Ramirez, R., & Vamvakousis, Z. (2012). Detecting emotion from EEG signals using the emotive epoc device. Proceedings of the 2012 International Conference on Brain Informatics, LNCS 7670, 175–184.

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.

Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161–1178.

Schlund, M. W., & Cataldo, M. F. (2010). Amygdala involvement in human avoidance, escape and approach behavior. NeuroImage, 53(2), 769–776.

Shtark, M. B., Verevkin, E. G., Kozlova, L. I., Mazhirina, K. G., Pokrovskii, M. A., Petrovskii, E. D., … Yarosh, S. V. (2015). Synergetic fMRI-EEG brain mapping in alpha-rhythm voluntary control mode. Bulletin of Experimental Biology and Medicine, 158(5), 644–649.

Spielberg, J. M., Miller, G. A., Warren, S. L., Engels, A. S., Crocker, L. D., Banich, M. T., … Heller, W. (2012). A brain network instantiating approach and avoidance motivation. Psychophysiology, 49(9), 1200–1214.

Sulzer, J., Haller, S., Scharnowski, F., Weiskopf, N., Birbaumer, N., Blefari, M. L., … Sitaram, R. (2013). Real-time fMRI neurofeedback: Progress and challenges. NeuroImage, 76, 386–399.

Sutton, S. K., & Davidson, R. J. (1997). Prefrontal brain asymmetry: A biological substrate of the behavioral approach and inhibition systems. Psychological Science, 8(3), 204–210.

Thibault, R. T., & Raz, A. (2016). When can neurofeedback join the clinical armamentarium? The Lancet Psychiatry, 3(6), 497–498.

Thibault, R. T., & Raz, A. (2017). The psychology of neurofeedback: Clinical intervention even if applied placebo. The American Psychologist, 72(7), 679–688.

Thomsen, K. R. (2015). Measuring anhedonia: Impaired ability to pursue, experience, and learn about reward. Frontiers in Psychology, 6, 1409.

Weiskopf, N. (2012). Real-time fMRI and its application to neurofeedback. NeuroImage, 62(2), 682–692.

Weiskopf, N., Scharnowski, F., Veit, R., Goebel, R., Birbaumer, N., & Mathiak, K. (2004). Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI). Journal of Physiology-Paris, 98(4–6), 357–373.

Wheeler, R. E., Davidson, R. J., & Tomarken, A. J. (1993). Frontal brain asymmetry and emotional reactivity: A biological substrate of affective style. Psychophysiology, 30(1), 82–89.

Young, K. D., Zotev, V., Phillips, R., Misaki, M., Yuan, H., Drevets, W. C., & Bodurka, J. (2014). Real-time fMRI neurofeedback training of amygdala activity in patients with major depressive disorder. PLoS ONE, 9(2), e88785.

Yuan, H., Young, K. D., Phillips, R., Zotev, V., Misaki, M., & Bodurka, J. (2014). Resting-state functional connectivity modulation and sustained changes after real-time functional magnetic resonance imaging neurofeedback training in depression. Brain Connectivity, 4(9), 690–701.

Zhang, J., Jadavji, Z., Zewdie, E., & Kirton, A. (2019). Evaluating if children can use simple brain computer interfaces. Frontiers in Human Neuroscience, 13, 24.

Zich, C., Debener, S., Kranczioch, C., Bleichner, M. G., Gutberlet, I., & De Vos, M. (2015). Real-time EEG feedback during simultaneous EEG-fMRI identifies the cortical signature of motor imagery. NeuroImage, 114, 438–447.

Zotev, V., Krueger, F., Phillips, R., Alvarez, R. P., Simmons, W. K., Bellgowan, P., … Bodurka, J. (2011). Self-regulation of amygdala activation using real-time fMRI neurofeedback. PLoS ONE, 6(9), e24522.

Zotev, V., Phillips, R., Young, K. D., Drevets, W. C., & Bodurka, J. (2013). Prefrontal control of the amygdala during real-time fMRI neurofeedback training of emotion regulation. PLoS ONE, 8(11), e79184.

Zotev, V., Yuan, H., Misaki, M., Phillips, R., Young, K. D., Feldner, M. T., & Bodurka, J. (2016). Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression. NeuroImage: Clinical, 11, 224–238.

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