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Emotion in Games pp 21–37Cite as

Affect Channel Model of Evaluation in the Context of Digital Games

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Part of the book series: Socio-Affective Computing ((SAC,volume 4))

Abstract

Psychological emotion theories are underused in digital game research, possibly because they are divided into several competing camps and because they do not provide a framework easily applied to a context of digital games. I present a first step towards an integration of the camps, especially by combining Panksepp’s view on primary processes, Scherer’s component process model, and Cacioppo and others’ evaluative space model. While specifying the different parts of the affect channel model of evaluation, I discuss how they are likely related to common game-related phenomena.

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Notes

  1. 1.

    The “domain-generality” does not imply that the functions are not specialized—only that the domain of specialization is not “emotion” (cf. [19], Chapter 2).

  2. 2.

    I prefer ‘evaluation’ over ‘appraisal’, because the latter is a strongly loaded term specifically related to appraisal theories and the theoretical constraints related to that literature.

  3. 3.

    I have ignored, among many details, the whole system of homeostatic functions (pain, hunger, thirst, uncomfortable temperature, fatigue) which I contend should be recognized as an affect channel on their own right (cf. [31]).

  4. 4.

    Following Kurzban [19], by “module” I mean “information-processing mechanism specialized to perform a particular function”—not the strong Fodorian module. Although I assume that the neural substrates of the modules can be found in the brain (see below), I do not assume that different modules are necessarily distinct from each other on the neural level. Therefore, I use expressions like “a module x is based on module y”, meaning that the neurons that carry out the functions are largely the same, but because the modules are related to the function, the modules may be different.

  5. 5.

    Note that by “stimulus” I do not mean, for example, a single seen object, as the visual system makes the distinction between objects relatively late ([10], Chapter 5). Instead, I mean the information that reaches an evaluator after being processed by different perception modules into some format that it can evaluate. That is, like the perception modules, the evaluators focus on very specific features of the perceptual information, from a simple feature like darkness, to a highly processed understanding of the environment and context. This also means that while I assume an external stimulus (such as a digital game), the model does not ignore self-caused (imagined or recalled) stimuli, that are treated no different from the external stimuli when they are fed to the evaluators. This is supported by the vast evidence that imagined situations lead to same kind of physical changes in the brain than external stimuli (e.g., [13]).

  6. 6.

    I also note that the levels seem to correspond roughly to the (probable) evolutionary and developmental order of appearance, but this is not the main purpose of the levels.

  7. 7.

    How can the elite Counter-Strike players play this extremely fast-paced game, if the simple evaluation of the consequences of an action is supposed to take half a second? The experiments about the timings have been carried out with abstract tasks that people have no previous experience with. When a familiar environment is navigated, the typical situations and their consequences are already associated to their evaluations and behavioral responses, allowing quick responding by automated motor patterns that border reflexes in extreme cases. Instead of absolute timings, the levels are meant to indicate the relative processing speeds of different processing types—the milliseconds are secondary.

  8. 8.

    Note that albeit the evolutionary function of the play module is to learn survival-relevant skills and understanding, the modules themselves do not regulate their operation according to whether there is actual use for the skills and understanding in the life in general. Procrastination and diabetes occur for the same reason: the modules behind our behavior have evolved in a much more resource-scarce environment where too much resources was never something we needed to adapt to. Play is the same—it was never “meant” to be available as often as it is in the modern world where we don’t have to focus on survival all the time. All play the individual had time for in the ancestral past was a bonus.

  9. 9.

    Cf. magic circle: [42].

  10. 10.

    Not in early pretend play, though: young children apparently mimic the activities, without imagining the mental worlds of mom and dad or police and robber [24].

References

  1. Andrade EB, Cohen JB (2007) On the consumption of negative feelings. J Consum Res 34(3):283–300. doi:10.1086/519498

    Article  Google Scholar 

  2. Barrett LF (2013) Psychological construction: the Darwinian approach to the science of emotion. Emot Rev 5(4):379–389. doi:10.1177/1754073913489753

    Article  Google Scholar 

  3. Bartsch A, Vorderer P, Mangold R, Viehoff R (2008) Appraisal of emotions in media use: toward a process model of meta-emotion and emotion regulation. Media Psychol 11(1):7–27. doi:10.1080/15213260701813447

    Article  Google Scholar 

  4. Bateman C, Nacke LE (2010) The neurobiology of play. In: Proceedings of the international academic conference on the future of game design and technology pp 1–8. ACM

    Google Scholar 

  5. Brosch T, Sander D (2013) Comment: the appraising brain: towards a neuro-cognitive model of appraisal processes in emotion. Emot Rev 5(2):163–168. doi:10.1177/1754073912468298

    Article  Google Scholar 

  6. Cacioppo JT, Berntson GG (1994) Relationship between attitudes and evaluative space: a critical review, with emphasis on the separability of positive and negative substrates. Psychol Bull 115(3):401–423. doi:10.1037/0033-2909.115.3.401

    Article  Google Scholar 

  7. Caroux L, Isbister K, Le Bigot L, Vibert N (2015) Player–video game interaction: a systematic review of current concepts. Comput Human Behav 48:366–381. http://doi.org/10.1016/j.chb.2015.01.066

    Google Scholar 

  8. Chatfield T (2010) 7 ways games reward the brain [video]. TEDGlobal. Retrieved from http://www.ted.com/talks/tom_chatfield_7_ways_games_reward_the_brain#t-966410

  9. Cunningham WA, Dunfield KA, Stillman PE (2013) Emotional states from affective dynamics. Emot Rev 5(4):344–355. doi:10.1177/1754073913489749

    Article  Google Scholar 

  10. Gazzaniga MS, Ivry RB, Mangun GR (1998) Cognitive neuroscience. The biology of the mind. W.W. Norton & Company, New York

    Google Scholar 

  11. Gentsch K, Grandjean D, Scherer KR (2013) Temporal dynamics of event-related potentials related to goal conduciveness and power appraisals. Psychophysiology 50(10):1010–1022. doi:10.1111/psyp.12079

    PubMed  Google Scholar 

  12. Grandjean D, Scherer KR (2008) Unpacking the cognitive architecture of emotion processes. Emotion 8(3):341–351. doi:10.1037/1528-3542.8.3.341

    Article  PubMed  Google Scholar 

  13. Holmes EA, Mathews A (2010) Mental imagery in emotion and emotional disorders. Clin Psychol Rev. doi:10.1016/j.cpr.2010.01.001

    PubMed  Google Scholar 

  14. Horberg EJ, Oveis C, Keltner D, Cohen AB (2009) Disgust and the moralization of purity. J Pers Soc Psychol 97(6):963–976. doi:10.1037/a0017423

    Article  CAS  PubMed  Google Scholar 

  15. Izard CE (ed) (2010) On defining emotion [Special section]. Emot Rev 2(4):363–385

    Google Scholar 

  16. Kahneman D (2011) Thinking, fast and slow. Book. Farrar, Straus and Giroux, New York

    Google Scholar 

  17. Kivikangas JM, Chanel G, Cowley B, Ekman I, Salminen M, Järvelä S, Ravaja N (2011) A review of the use of psychophysiological methods in game research. J Gaming Virtual Worlds 3(3):181–199. doi:10.1386/jgvw.3.3.181_1

    Article  Google Scholar 

  18. Koster R (2013) Theory of fun for game design. O’Reilly Media, Inc., Sebastopol

    Google Scholar 

  19. Kurzban R (2010) Why everyone (else) is a hypocrite. Evolution and the modular mind. Princeton University Press, Princeton

    Google Scholar 

  20. Lang A (2006) Motivated cognition (LC4MP): the influence of appetitive and aversive activation on the processing of video games. In: Messaris P, Humphreys L (eds) Digital media: transformation in human communication. Peter Lang Publishing, New York, pp 237–256

    Google Scholar 

  21. LeDoux JE (2012) Rethinking the emotional brain. Neuron 73(5):653–676. doi:10.1016/j.neuron.2012.02.004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. LeDoux JE (2014) Comment: what’s basic about the brain mechanisms of emotion? Emot Rev 6(4):318–320. doi:10.1177/1754073914534506

    Article  Google Scholar 

  23. LeDoux JE, Phelps EA (2008) Emotional networks in the brain. In: Lewis M, Haviland-Jones JM, Barrett LF (eds) Handbook of emotions, 3rd edn. Guilford Press, New York, pp 159–179

    Google Scholar 

  24. Lillard A (1993) Pretend play skills and the child’s theory of mind. Child Dev. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/j.1467-8624.1993.tb02914.x/full

  25. Mandryk RL, Atkins M (2007) A fuzzy physiological approach for continuously modeling emotion during interaction with play technologies. Int J Hum-Comput Stud 65(4):329–347. doi:10.1016/j.ijhcs.2006.11.011

    Article  Google Scholar 

  26. Martínez H, Yannakakis GN (2011) Analysing the relevance of experience partitions to the prediction of players’ self-reports of affect. In: Affective computing and intelligent interaction, part II, LNCS 6975, Springer, Berlin/Heidelberg, pp 538–546

    Google Scholar 

  27. Montola M (2011) The painful art of extreme role-playing. J Gaming Virtual Worlds 3(3):219–237

    Google Scholar 

  28. Munroe R (2011) Standards. Retrieved from http://xkcd.com/927/

  29. Norman GJ, Norris CJ, Gollan J, Ito TA, Hawkley LC, Larsen JT, … Berntson GG (2011) Current emotion research in psychophysiology: the neurobiology of evaluative bivalence. Emot Rev 3(3):349–359. doi:10.1177/1754073911402403

    Google Scholar 

  30. Norris CJ, Gollan J, Berntson G, Cacioppo JT (2010) The current status of research on the structure of evaluative space. Biol Psychol 84(3):422–436

    Article  PubMed  PubMed Central  Google Scholar 

  31. Panerai AE (2011) Pain emotion and homeostasis. Neurol Sci: Off J Ital Neurol Soc Ital Soc Clin Neurophysiol 32(Suppl 1):S27–S29. doi:10.1007/s10072-011-0540-5

    Article  Google Scholar 

  32. Panksepp J, Biven L (2012) The archaeology of mind: neuroevolutionary origins of human emotions (Norton series on interpersonal neurobiology). W.W. Norton & Company, New York

    Google Scholar 

  33. Peifer C (2012) Psychophysiological correlates of flow-experience. Adv Flow Res:139–164. Retrieved from http://link.springer.com/10.1007/978-1-4614-2359-1_8

  34. Poels K, van den Hoogen W, IJsselsteijn WA, de Kort YAW (2012) Pleasure to play, arousal to stay: the effect of player emotions on digital game preferences and playing time. Cyberpsychol Behav Soc Netw 15(1):1–6. doi:10.1089/cyber.2010.0040

    Article  PubMed  Google Scholar 

  35. Russell JA (2003) Core affect and the psychological construction of emotion. Psychol Rev 110(1):145–172. doi:10.1037/0033-295X.110.1.145

    Article  PubMed  Google Scholar 

  36. Russell JA (2009) Emotion, core affect, and psychological construction. Cognit Emot 23(7):1259–1283. doi:10.1080/02699930902809375

    Article  Google Scholar 

  37. Russell JA (ed) (2012) On defining emotion [Special section]. Emot Rev 4(4):337–393

    Google Scholar 

  38. Scherer KR (2001) Appraisal considered as a process of multi-level sequential checking. In: Scherer KR, Schorr A, Johnstone T (eds) Appraisal processes in emotion: theory, methods, research. Oxford University Press, New York, pp 92–120

    Google Scholar 

  39. Scherer KR (2009) The dynamic architecture of emotion: evidence for the component process model. Cognit Emot 23(7):1307–1351. doi:10.1080/02699930902928969

    Article  Google Scholar 

  40. Scherer KR (2013) The nature and dynamics of relevance and valence appraisals: theoretical advances and recent evidence. Emot Rev 5(2):150–162. doi:10.1177/1754073912468166

    Article  Google Scholar 

  41. Scherer KR, Schorr A, Johnstone T (2001) In: Scherer KR, Schorr A, Johnstone T (eds) Appraisal processes in emotion: theory, methods, research. Oxford University Press, Canary

    Google Scholar 

  42. Stenros J (2014) In defence of a magic circle: the social, mental and cultural boundaries of play. Trans Digit Games Res Assoc 1(2):147–185

    Google Scholar 

  43. Tooby J, Cosmides L (2008) The evolutionary psychology of the emotions and their relationship to internal regulatory variables. In: Lewis M, Haviland-Jones JM, Barrett LF (eds) Handbook of emotions, 3rd edn. Guilford Press, New York, pp 114–137

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Information and Service Economy, Aalto University, Helsinki, Finland

    J. Matias Kivikangas

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  1. J. Matias Kivikangas
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Correspondence to J. Matias Kivikangas .

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Editors and Affiliations

  1. Institute of Communication and Computer Systems, National Technical University of Athens, Zographou, Greece

    Kostas Karpouzis

  2. Institute of Digital Games, University of Malta, Msida, Malta

    Georgios N. Yannakakis

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Kivikangas, J.M. (2016). Affect Channel Model of Evaluation in the Context of Digital Games. In: Karpouzis, K., Yannakakis, G. (eds) Emotion in Games. Socio-Affective Computing, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-41316-7_2

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