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Towards emotional regulation through neurofeedback

Authors:

Julie Porteous,

Stephen W. Gilroy,

Nimrod Jakob Keynan,

Ilana Klovatch,

Talma HendlerAuthors Info & Claims

AH '14: Proceedings of the 5th Augmented Human International Conference

Article No.: 42, Pages 1 - 8

https://doi.org/10.1145/2582051.2582093

Published: 07 March 2014 Publication History

Abstract

This paper discusses the potential of Brain-Computer Interfaces based on neurofeedback methods to support emotional control and pursue the goal of emotional control as a mechanism for human augmentation in specific contexts. We illustrate this discussion through two proof-of-concept, fully-implemented experiments: one controlling disposition towards virtual characters using pre-frontal alpha asymmetry, and the other aimed at controlling arousal through activity of the amygdala. In the first instance, these systems are intended to explore augmentation technologies that would be incorporated into various media-based systems rather than permanently affect user behaviour.

References

[1]

Atkins, P. and De Paula, J. Atkins' physical chemistry. Oxford University Press, Oxford, 2006.

[2]

Baehr, E., Rosenfeld, J. P. and Baehr, R. Clinical use of an alpha asymmetry neurofeedback protocol in the treatment of mood disorders: Follow-up study one to five years post therapy. Journal of Neurotherapy, 4, 4 (2001), 11--18.

[3]

Beauregard, M., Levesque, J. and Bourgouin, P. Neural correlates of conscious self-regulation of emotion. The Journal of Neuroscience, 21, (2001), RC165.

[4]

Benjamini, Y. and Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Statist. Soc. B, 57, 1 (1995), 289--300.

[5]

Blair, R. The amygdala and ventromedial prefrontal cortex in morality and psychopathy. Trends Cogn. Sci. (Regul. Ed.), 11, 9 (2007), 387--392.

[6]

Cacioppo, J. T., Berntson, G. G. and Nusbaum, H. C. Neuroimaging as a new tool in the toolbox of psychological science. Current Directions in Psychological Science, 17, 2 (2008), 62--67.

[7]

Damasio, A. Descartes' Error: Emotion, Reason, and the Human Brain. Putnam Publishing, 1994.

[8]

Davidson, R. J. Affective style and affective disorders: Perspectives from affective neuroscience. Cognition & Emotion, 12, 3 (1998), 307--330.

[9]

Davidson, R. J. What does the prefrontal cortex "do" in affect: perspectives on frontal EEG asymmetry research. Biol. Psychol., 67, 1 (2004), 219--234.

[10]

Decety, J. and Moriguchi, Y. The empathic brain and its dysfunction in psychiatric populations: implications for intervention across different clinical conditions. BioPsychoSocial Medicine, 1, 1 (2007), 22.

[11]

Delgado, M. R., Olsson, A. and Phelps, E. A. Extending animal models of fear conditioning to humans. Biol. Pschol., 73, 1 (2006), 39--48.

[12]

Gilroy, S. W., Porteous, J., Charles, F., Cavazza, M., Soreq, E., Raz, G., Ikar, L., Or-Borichov, A., Ben-Arie, U., Klovatch, I. and Hendler, T. A Brain-Computer Interface to a Plan-based Narrative. In Proc. IJCAI 2013, AAAI Press (2013), 1997--2005.

Digital Library

[13]

Gross, J. J. The emerging field of emotion regulation: An integrative review. Review of General Psychology, 2, 3 (1998), 271--299.

[14]

Gruzelier, J. H. EEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants. Neuroscience and Biobehavioral Reviews (2013), in press.

[15]

Hall, L. and Johansson, P. Neurofeedback and Metacognition. In Proc. AIED 2003, Supplementary Proceedings: Metacognition and Self-regulation in Learning with Metacognitive Tools, (2003), 541--556.

[16]

Hamann, S. Mapping discrete and dimensional emotions onto the brain: controversies and consensus. Trends Cogn. Sci. (Regul. Ed.), 16, 9 (2012), 458--466.

[17]

Hare, T. A., Tottenham, N., Davidson, M. C., Glover, G. H. and Casey, B. Contributions of amygdala and striatal activity in emotion regulation. Biol. Psychiatry, 57, 6 (2005), 624--632.

[18]

Harmon-Jones, E. Clarifying the emotive functions of asymmetrical frontal cortical activity. Psychophysiology, 40, 6 (2003), 838--848.

[19]

Henriques, J. B. and Davidson, R. J. Left frontal hypoactivation in depression. J. Abnorm. Psychol., 100, 4 (1991), 535--545.

[20]

Jensen, C. B. F., Petersen, M. K., Larsen, J. E., Stopczynski, A., Stahlhut, C., Ivanova, M. G., Andersen, T. and Hansen, L. K. Spatio temporal media components for neurofeedback. In Proc. IEEE ICME '13 (2013).

[21]

Johnston, S., Boehm, S., Healy, D., Goebel, R. and Linden, D. Neurofeedback: A promising tool for the self-regulation of emotion networks. Neuroimage, 49, 1 (2010), 1066--1072.

[22]

Kapeller, C., Hintermüller, C. and Guger, C. Usability of video-overlaying SSVEP based BCIs. In Proc. AH '12. ACM Press (2012a), Article 26.

Digital Library

[23]

Kapeller, C., Hintermüller, C. and Guger, C. Augmented control of an avatar using an SSVEP based BCI. In Proc. AH '12. ACM Press (2012b), Article 27.

Digital Library

[24]

Kober, S. E., Witte, M., Ninaus, M., Neuper, C. and Wood, G. Learning to modulate one's own brain activity: the effect of spontaneous mental strategies. Front. Hum. Neurosci., 7 (2013), Article 695.

[25]

Light, S. N., Coan, J. A., Zahn-Waxler, C., Frye, C., Goldsmith, H. H. and Davidson, R. J. Empathy is associated with dynamic change in prefrontal brain electrical activity during positive emotion in children. Child Dev., 80, 4 (2009), 1210--1231.

[26]

Lindquist, K. A., Wager, T. D., Kober, H., Bliss-Moreau, E. and Barrett, L. F. The brain basis of emotion: A meta-analytic review. Behav. Brain Sci., 35, 3 (2012), 121--143.

[27]

Marshall, D., Coyle, D., Wilson, S. and Callaghan, M. Games, Gameplay, and BCI: The State of the Art. IEEE T-CIAIG, 5, 2 (2013), 82--99.

[28]

Meir-Hasson, Y., Kinreich, S., Podlipsky, I., Hendler, T. and Intrator, N. An EEG Finger-Print of fMRI deep regional activation. Neuroimage (2013), in press.

[29]

Mikhail, M., El-Ayat, K., El Kaliouby, R., Coan, J. and Allen, J. J. Emotion detection using noisy EEG data. In Proc. AH '10. ACM Press (2010), Article 7.

Digital Library

[30]

Nan, W., Rodrigues, J. P., Ma, J., Qu, X., Wan, F., Mak, P., Mak, P. U., Vai, M. I. and Rosa, A. Individual alpha neurofeedback training effect on short term memory. Int. J. Psychophysiol., 86, 1 (2012), 83--87.

[31]

Niv, S. Clinical efficacy and potential mechanisms of neurofeedback. Personality and Individual Differences, 54, 6 (2013), 676--686.

[32]

Ochsner, K. N. and Gross, J. J. The cognitive control of emotion. Trends Cogn. Sci. (Regul. Ed.), 9, 5 (2005), 242--249.

[33]

Oliveira, I., Grigore, O., Guimarães, N. and Duarte, L. Relevance of EEG input signals in the augmented human reader. In Proc. AH '10. ACM (2010), Article 5.

Digital Library

[34]

Peeters, F., Ronner, J., Bodar, L., van Os, J. and Lousberg, R. Validation of a neurofeedback paradigm: manipulating frontal EEG alpha-activity and its impact on mood. International Journal of Psychophysiology (2013), in press.

[35]

Porteous, J., Cavazza, M. and Charles, F. Applying planning to interactive storytelling: Narrative control using state constraints. ACM TIST, 1, 2 (2010), 1--21.

Digital Library

[36]

Raz, G., Winetraub, Y., Jacob, Y., Kinreich, S., Maron-Katz, A., Shaham, G., Podlipsky, I., Gilam, G., Soreq, E. and Hendler, T. Portraying emotions at their unfolding: A multilayered approach for probing dynamics of neural networks. Neuroimage, 60, 2 (2012), 1448--1461.

[37]

Seigneur, J. The emotional economy for the augmented human. In Proc. AH '11, ACM Press (2011), Article 24.

Digital Library

[38]

Smith, G. M. Film structure and the emotion system. Cambridge University Press, 2003.

[39]

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

[40]

Tan, E. S. Emotion and the structure of narrative film: Film as an emotion machine. Lawrence Erlbaum Associates, Mahwah, N.J., 1996.

[41]

Thagard, P. Hot thought: Mechanisms and applications of emotional cognition. MIT Press, Cambridge, 2006.

[42]

Tsetserukou, D. and Neviarouskaya, A. World's first wearable humanoid robot that augments our emotions. In Proc. AH '10. ACM Press (2010), Article 8.

Digital Library

[43]

Tullett, A. M., Harmon-Jones, E. and Inzlicht, M. Right frontal cortical asymmetry predicts empathic reactions: Support for a link between withdrawal motivation and empathy. Psychophysiology, 49, 8 (2012), 1145--1153.

[44]

Vidaurre, C. and Blankertz, B. Towards a cure for BCI illiteracy. Brain Topogr., 23, 2 (2010), 194--198.

[45]

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

[46]

Yoshida, S., Tanikawa, T., Sakurai, S., Hirose, M. and Narumi, T. Manipulation of an emotional experience by real-time deformed facial feedback. In Proc. AH '13. ACM Press (2013), 35--42.

Digital Library

[47]

Yuan, G., Lim, T. S., Juan, W. K., Ringo, H. M. and Li, Q. A GMM based 2-stage architecture for multi-subject emotion recognition using physiological responses. In Proc. AH '10. ACM Press (2010), Article 3.

Digital Library

[48]

Zotev, V., Phillips, R., young, K. D., Drevets, W. C. and Bodurka, J. Prefrontal Control of the Amygdala during Real-Time fMRI Neurofeedback Training of Emotion Regulation. Plos One, 8, 11 (2013), e79184.

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Index Terms

Towards emotional regulation through neurofeedback
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Other conferences

AH '14: Proceedings of the 5th Augmented Human International Conference

March 2014

249 pages

ISBN:9781450327619

DOI:10.1145/2582051

General Chair:
Tsutomu Terada
Kobe University, Japan
,
Program Chairs:
Masahiko Inami
Keio University, Japan
,
Kai Kunze
Osaka Prefecture University, Japan
,
Takuya Nojima
University of Electro-communications, Japan

Copyright © 2014 ACM.

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Published: 07 March 2014

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AH '14: 5th Augmented Human International Conference

March 7 - 8, 2014

Kobe, Japan

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https://dl.acm.org/doi/10.1145/3652988.3673952
Krogmeier CBravo EMousas C(2023)Using Experimental Filmmaking to Create an Engaging Brain-Computer InterfaceProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/35976246:2(1-10)Online publication date: 16-Aug-2023
https://dl.acm.org/doi/10.1145/3597624
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Ma HYarosh S(2023)A Review of Affective Computing Research Based on Function-Component-Representation FrameworkIEEE Transactions on Affective Computing10.1109/TAFFC.2021.310451214:2(1655-1674)Online publication date: 1-Apr-2023
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