Exploring extensions of neurotransmitter-based emotion models

João Ricardo Pinheiro; Paulo de Tarso Fernandes; Augusto Baffa; Bruno Feijó

doi:10.5753/jis.2025.5642

Authors

João Ricardo Pinheiro Pontifical Catholic University of Rio de Janeiro https://orcid.org/0009-0002-4460-3447
Paulo de Tarso Fernandes Pontifical Catholic University of Rio de Janeiro https://orcid.org/0009-0001-4051-6605
Augusto Baffa Pontifical Catholic University of Rio de Janeiro https://orcid.org/0000-0002-7039-4477
Bruno Feijó Pontifical Catholic University of Rio de Janeiro https://orcid.org/0000-0003-4441-2632

DOI:

https://doi.org/10.5753/jis.2025.5642

Keywords:

Emotion Modeling, Lövheim Cube, Plutchik’s Wheel, Fuzzy Logic, Neuroscience-inspired AI, Dynamic Emotional Responses, Behavioral Simulation, Emotion-driven NPCs

Abstract

Advancements in artificial intelligence have significantly enhanced the gaming experience, enabling more engaging and adaptive interactions between players and digital characters. A key aspect of this progress is the ability of non-player characters (NPCs) to display more lifelike realistic emotional responses that simulate the fluid and unpredictable nature of human emotions. This work presents a novel emotion model integrating Lövheim’s Cube of Emotions with Plutchik’s Wheel of Emotions, combining the dynamic aspects of the former with the detailed structure of the latter. The model was expanded from a 22-emotion, 21-point mapping to a more detailed version with 24 emotions across 52 points, allowing for better emotional differentiation. Two algorithms were upgraded and tested: an extended cube of emotions using the Euclidean distance, and the same cube incorporating fuzzy logic. Both methods showed significantly better results than their previous versions, with the Euclidean being the best overall. That indicates a more precise mapping of emotions. However, it can only return one emotion at a time. While the Fuzzy Logic method allows for more than one emotional response at the same time, associating neurotransmitters and emotions within fuzzy rules was quite complex.

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References

Adams, F. M. and Osgood, C. E. (1973). A crosscultural study of the affective meanings of color. Journal of Cross-Cultural Psychology, 4(2):135–156. DOI: https://doi.org/10.1177/002202217300400201.

Alvim, L. G. M. and de Oliveira Cruz, A. J. (2008). A fuzzy state machine applied to an emotion model for electronic game characters. In 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), pages 1956–1963. DOI: https://doi.org/10.1109/FUZZY.2008.4630637.

Arias, J. A., Williams, C., Raghvani, R., Aghajani, M., Baez, S., Belzung, C., Booij, L., Busatto, G., Chiarella, J., Fu, C. H., Ibanez, A., Liddell, B. J., Lowe, L., Penninx, B. W., Rosa, P., and Kemp, A. H. (2020). The neuroscience of sadness: A multidisciplinary synthesis and collaborative review. Neuroscience Biobehavioral Reviews, 111:199–228. DOI: https://doi.org/10.1016/j.neubiorev.2020.01.006.

Baffa, A., Sampaio, P., Feijó, B., and Lana, M. (2017). Dealing with the emotions of non player characters. In 2017 16th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), pages 76–87. DOI: https://doi.org/10.1109/SBGames.2017.00017.

Berridge, K. C. and Kringelbach, M. L. (2015). Pleasure systems in the brain. Neuron, 86(3):646–664. DOI: https://doi.org/10.1016/j.neuron.2015.02.018.

Bicalho, L. F., Feijó, B., and Baffa, A. (2020). A culture model for non-player characters’ behaviors in role-playing games. In 2020 19th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), pages 9–18, Brazil. IEEE. DOI: https://doi.org/10.1109/SBGames51465.2020.00013.

Cabral, A. (2020). Como usar a roda das emoções de plutchik no mapeamento de jornadas? Medium - Geração CX. [link], Accessed: 09 June 2025.

Chrysafiadi, K., Kamitsios, M., and Virvou, M. (2023). Fuzzy-based dynamic difficulty adjustment of an educational 3d-game. Multimedia Tools and Applications, 82:27525–27549. DOI: https://doi.org/10.1007/s11042-023-14515-w.

Coleman, J. A., Green, E. M., and Gouaux, E. (2016). X-ray structures and mechanism of the human serotonin transporter. Nature, 532:334–339. DOI: https://doi.org/10.1038/nature17629.

Cuevas, J. (2007). Neurotransmitters and their life cycle. In Enna, S. and Bylund, D. B., editors, xPharm: The Comprehensive Pharmacology Reference, pages 1–7. Elsevier, New York. DOI: https://doi.org/10.1016/B978-008055232-3.60016-9.

Ekman, P., Friesen, W., and Simons, R. (1985). Is the startle reaction an emotion? Journal of Personality and Social Psychology, 49(5):1416–1426. DOI: https://doi.org/10.1037//0022-3514.49.5.1416.

Fernandes, P., Baffa, A., and Feijó, B. (2024). An emotion model for non-player characters inspired by neurotransmitters. In Anais do XXIII Simpósio Brasileiro de Jogos e Entretenimento Digital, pages 547–562, Porto Alegre, RS, Brasil. SBC. DOI: https://doi.org/10.5753/sbgames.2024.241365.

Galvão, V. F., Maciel, C., Nunes, E. P. d. S., and Rodrigues, K. R. d. H. (2025). A framework to support the development of empathetic games. Journal on Interactive Systems, 16(1):25–53. DOI: https://doi.org/10.5753/jis.2025.4100.

Gasper, K., Spencer, L., and Hu, D. (2019). Does neutral affect exist? how challenging three beliefs about neutral affect can advance affective research. Frontiers in Psychology, 10:2476. DOI: https://doi.org/10.3389/fpsyg.2019.02476.

Goldstein, E. B. (2010). Sensation and Perception 8th edition. Cengage Learning. 496 pages.

Hanada, M. (2018). Correspondence analysis of color–emotion associations. Color Research & Application, 43(2):224–237. DOI: https://doi.org/10.1002/col.22171.

Heudin, J.-C. (2016). A connexionist model for emotions in digital agents. In International Conference on Agents and Artificial Intelligence, volume 2, pages 272–279. SCITEPRESS. DOI: https://doi.org/10.5220/0005669202720279.

Hine, T. (1997). The Total Package: The Secret History and Hidden Meanings of Boxes, Bottles, Cans, and Other Persuasive Containers. Back Bay Books. 289 pages.

Jiang, Y., Zou, D., Li, Y., Gu, S., Jie, D., Ma, X., Xu, S., Wang, F., and Huang, J. (2022). Monoamine neurotransmitters control basic emotions and affect major depressive disorders. Pharmaceuticals (Basel), 15(10):1203. DOI: https://doi.org/10.3390/ph15101203.

Johansson, A. and Dell’Acqua, P. (2012). Emotional behavior trees. In 2012 IEEE Conference on Computational Intelligence and Games (CIG), pages 355–362, Granada, Spain. IEEE. DOI: https://doi.org/10.1109/CIG.2012.6374177.

Kaneko, K. and Okada, Y. (2024). Emotion-Based 3D CG Character Behaviors, pages 645–653. Springer International Publishing, Cham. DOI: https://doi.org/10.1007/978-3-031-23161-2_35.

Kolmogorova, A., Kalinin, A., and Malikova, A. (2021). Semiotic function of empathy in text: Emotion assessment. Biosemiotics, 14:329–344. DOI: https://doi.org/10.1007/s12304-021-09434-y.

Kołakowska, A., Landowska, A., Szwoch, M., Szwoch, W., and Wróbel, M. (2015). Modeling emotions for affectaware applications, pages 55–67. Faculty of Management University of Gdańsk.

Li, L. and Campbell, J. (2010). Emotion modeling and interaction of npcs in virtual simulation and games. In The International Journal of Virtual Reality, pages 1–6. DOI: https://doi.org/10.20870/IJVR.2010.9.4.2784.

Lövheim, H. (2012). A new three-dimensional model for emotions and monoamine neurotransmitters. Medical Hypotheses, 78(2):341–348. DOI: https://doi.org/10.1016/j.mehy.2011.11.016.

Mateas, M. (2003). Expressive ai: Games and artificial intelligence. In Proceedings of Level Up: Digital Games Research Conference 2003, volume 2, Utrecht, Netherlands. DOI: https://doi.org/10.26503/dl.v2003i1.99.

McCarley, K. E. (2009). The Humiliation Experience: Causes, Emotional Correlates, and Behavioral Consequences. PhD thesis, University of Denver. Colorado, USA.

Miller, E. G. and Kahn, B. E. (2011). Shades of meaning: the effects of color and flavor names on purchase intentions. English (Philadelphia, Pennsylvania, USA: University of Pennsylvania, The Wharton School, Ph. D. dissertation). Psychology, terminology, pages 1–32. DOI: https://doi.org/10.1086/429602.

Mohmed, G., Lotfi, A., and Pourabdollah, A. (2020). Enhanced fuzzy finite state machine for human activity modelling and recognition. Journal of Ambient Intelligence and Humanized Computing, 11:6077–6091. DOI: https://doi.org/10.1007/s12652-020-01917-z.

Moret, C. and Briley, M. (2011). The importance of norepinephrine in depression. Neuropsychiatric Disease and Treatment, 7(Suppl 1), pages 9–13. DOI: https://doi.org/10.2147/NDT.S19619.

Murgia, A., Tourani, P., Adams, B., and Ortu, M. (2014). Do developers feel emotions? an exploratory analysis of emotions in software artifacts. In Proceedings of the 11th Working Conference on Mining Software Repositories, MSR 2014, page 262–271, New York, NY, USA. Association for Computing Machinery. DOI: https://doi.org/10.1145/2597073.2597086.

Parrott, W. G. (2001). Emotions in Social Psychology. Psychology Press, USA.

Plutchik, R. (1980). Chapter 1 - a general psychoevolutionary theory of emotion. In Plutchik, R. and Kellerman, H., editors, Theories of Emotion, pages 3–33. Academic Press. DOI: https://doi.org/10.1016/B978-0-12-558701-3.50007-7.

Plutchik, R. (2001). The nature of emotions. American Scientist, 89:344–350. DOI: https://doi.org/10.1511/2001.28.344.

Pop-Jordanova, N. (2021). Grief: Aetiology, symptoms and management. PRILOZI, 42:9–18. DOI: https://doi.org/10.2478/prilozi-2021-0014.

Popescu, A., Broekens, J., and Someren, M. (2014). Gamygdala: An emotion engine for games. In IEEE Transactions on Affective Computing, volume 5, pages 32–44. DOI: https://doi.org/10.1109/T-AFFC.2013.24.

Russell, J. A. (1980). A circumplex model of affect. In Journal of Personality and Social Psychology, volume 39, page 1161–1178. DOI: https://doi.org/10.1037/h0077714.

Suk, H.-J. and Irtel, H. (2010). Emotional response to color across media. Color Research & Application, 35(1):64–77. DOI: https://doi.org/10.1002/col.20554.

Terenzi, D., Liu, L., Bellucci, G., and Park, S. Q. (2021). Determinants and modulators of human social decisions. Neuroscience and Biobehavioral Reviews, 128:383–393. DOI: https://doi.org/10.1016/j.neubiorev.2021.06.041.

Tomkins, S. S. and McCarter, R. (1964). What and where are the primary affects? some evidence for a theory. Perceptual and Motor Skills, 18:119–158. DOI: https://doi.org/10.2466/pms.1964.18.1.119.

Waltham, M. and Moodley, D. (2016). An analysis of artificial intelligence techniques in multiplayer online battle arena game environments. In Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists (SAICSIT ’16), page 1–7, Johannesburg, South Africa. ACM. DOI: https://doi.org/10.1145/2987491.2987513.

Yannakakis, G., Karpouzis, K., Paiva, A., and Hudlicka, E. (2011). Emotion in games. In D’Mello, S., Graesser, A., Schuller, B., Martin, J. C. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, volume 6975, page 497. DOI: https://doi.org/10.1007/978-3-642-24571-8_62.

Yin, M. and Xiao, R. (2024). Press a or wave: User expectations for npc interactions and nonverbal behaviour in virtual reality. Proc. ACM Hum.-Comput. Interact., 8(CHI PLAY). DOI: https://doi.org/10.1145/3677098.

Zadeh, L. (1988). Fuzzy logic. Computer, 21(4):83–93. DOI: https://doi.org/10.1109/2.53.