Abstract
What differentiates the joke writing strategy employed by professional comedians from non-comedians? Previous MRI work found that professional comedians relied to a greater extent on “bottom-up processes,” i.e., associations driven by the prompt stimuli themselves, while controls relied more on prefrontal lobe directed, “top-down” processes. In the present work, professional improv comedians and controls generated humorous captions to cartoons while their eye movements were tracked. Participants’ visual fixation patterns were compared to predictions of the saliency model (Harel et al. in Adv Neural Inf Process Syst 19:545–552, 2007)—a computer model for identifying the most salient locations in an image based on visual features. Captions generated by the participants were rated for funniness by independent raters. Relative to controls, professional comedians’ gaze was driven to a greater extent by the cartoons’ salient visual features. For all participants, captions’ funniness positively correlated with visual attention to salient cartoon features. Results suggest that comedic expertise is associated with increased reliance on bottom-up, stimulus-driven creativity, and that a bottom-up strategy results, on average, in funnier captions whether employed by comedians or controls. The cognitive processes underlying successful comedic creativity appear to adhere to the old comedians’ adage “pay attention to the elephant in the room.”
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© reprinted with permission). Middle right: saliency model predictions of eye-fixations based on low-level features. Left two columns: actual overall fixations of improv comedians and controls during the 3 experimental conditions (HUM, EXP, NOTH). Circles indicate visual fixations. Circle size indicates the total overall time spent fixating on a particular location. Circle color is meaningless, the purpose of varying the color is allowing a better understanding of the heatmaps when the fixation-circles partially overlap. Numbers under the heatmaps are ROC scores—the higher the score, the greater the fit between the model and the fixations
© reprinted with permission). Middle right: saliency model predictions of eye-fixations based on low-level visual features. Left two columns: actual overall fixations of improv comedians and controls during the trials that resulted in captions receiving the higher ratings (top) vs. lower ratings (bottom) all within the humorous condition. Circles indicate visual fixations. Circle size indicates the total overall time spent fixating on a particular location. Circle color is meaningless, the purpose of varying the color is allowing a better understanding of the heatmaps when the fixation-circles partially overlap. Numbers under the heatmaps are ROC scores—the higher the score, the greater the fit between the model and the fixations
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Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Notes
A saliency of a feature is often defined, in such context, to indicate the degree to which the feature attracts attention in the absence of a goal-oriented task (e.g., during free viewing; see Itti et al. 1998).
Anything that the joke is written about, e.g., a cartoon, improvised scene, news item.
Note that a process of the inhibition of previously activated associations may occur in the absence of top-down intervention (Martindale 2007). This extends to overt attention: in eye-tracking studies in which participates engage in a task free, free viewing of images, participants often do not redirect their gaze into image locations they recently scanned—a phenomenon known as inhibition of return (Wang & Klein, 2010).
References
Amir O (2016) The frog test: a tool for measuring humor theories’ validity and humor preferences. Front Hum Neurosci 10:40
Amir O, Biederman I (2016) The neural correlates of humor creativity. Front Hum Neurosci 10:597
Amir O, Xu X, Biederman I (2011) The spontaneous appeal by naïve subjects to nonaccidental properties when distinguishing among highly similar members of subspecies of birds closely resembles descriptions produced by experts. In: Vision sciences society annual meeting
Amir O, Biederman I, Wang Z, Xu X (2013) Ha Ha! Versus Aha! A direct comparison of humor to nonhumorous insight for determining the neural correlates of mirth. Cereb Cortex 25(5):1405–1413
Aziz-Zadeh L, Liew SL, Dandekar F (2013) Exploring the neural correlates of visual creativity. Soc Cogn Affect Neurosci 8(4):475–480
Basadur M (1995) Optimal ideation-evaluation ratios. Creat Res J 8(1):63–75
Beaty RE, Silvia PJ, Nusbaum EC, Jauk E, Benedek M (2014) The roles of associative and executive processes in creative cognition. Mem Cognit 42(7):1186–1197
Beaty RE, Kenett YN, Christensen AP, Rosenberg MD, Benedek M, Chen Q, Silvia PJ (2018) Robust prediction of individual creative ability from brain functional connectivity. Proc Natl Acad Sci 115(5):1087–1092
Bernal J, Sánchez FJ, Vilariño F, Arnold M, Ghosh A, Lacey G (2014) Experts vs. novices: applying eye-tracking methodologies in colonoscopy video screening for polyp search. In: Proceedings of the symposium on eye tracking research and applications, pp 223–226
Bowden EM, Jung-Beeman M, Fleck J, Kounios J (2005) New approaches to demystifying insight. Trends Cogn Sci 9:322–328
Brawer J, Amir O (2021) Mapping the ‘funny bone’: neuroanatomical correlates of humor creativity in professional comedians. Soc Cogn Affect Neurosci
Chen Q, Beaty RE, Cui Z, Sun J, He H, Zhuang K, Qiu J (2019) Brain hemispheric involvement in visuospatial and verbal divergent thinking. Neuroimage 202:116065
Chen Q, Beaty RE, Qiu J (2020) Mapping the artistic brain: common and distinct neural activations associated with musical, drawing, and literary creativity. Hum Brain Map
Dalmaijer ES, Mathôt S, Van der Stigchel S (2014) PyGaze: an open-source, cross-platform toolbox for minimal-effort programming of eye tracking experiments. Behav Res Methods 46:913–921
Dietrich A, Kanso R (2010) A review of EEG, ERP, and neuroimaging studies of creativity and insight. Psychol Bull 136:822–848
Erhard K, Kessler F, Neumann N, Ortheil HJ, Lotze M (2014) Professional training in creative writing is associated with enhanced fronto-striatal activity in a literary text continuation task. Neuroimage 100:15–23
Frith E, Kane MJ, Welhaf MS, Christensen AP, Silvia PJ, Beaty RE (2021) Keeping creativity under control: contributions of attention control and fluid intelligence to divergent thinking. Creat Res J 1–20
Gegenfurtner A, Lehtinen E, Säljö R (2011) Expertise differences in the comprehension of visualizations: a meta-analysis of eye-tracking research in professional domains. Educ Psychol Rev 23(4):523–552
Greengross G, Martin RA, Miller G (2012) Personality traits, intelligence, humor styles, and humor production ability of professional stand-up comedians compared to college students. Psychol Aesthet Creat Arts 6(1):74
Harding P, Robertson NM (2009) A comparison of feature detectors with passive and task-based visual saliency. In: Scandinavian conference on image analysis, pp 716–725. Springer, Berlin
Harel J, Koch C, Perona P (2007) Graph-based visual saliency. Adv Neural Inf Process Syst 19:545–552
Harel J, Koch C, Perona P (2006) Graph-based visual saliency. Advances in neural information processing systems, 19
Hirsch J, Curcio CA (1989) The spatial resolution capacity of human foveal retina. Vis Res 29(9):1095–1101
Houston JP, Mednick SA (1963) Creativity and the need for novelty. Psychol Sci Public Interest 66(2):137
Howard-Jones PA, Blakemore SJ, Samuel EA, Summers IR, Claxton G (2005) Semantic divergence and creative story generation: an fMRI investigation. Cogn Brain Res 25:240–250
Hummel JE, Biederman I (1992) Dynamic binding in a neural network for shape recognition. Psychol Rev 99(3):480
Hurley MM, Dennett DC, Adams RB Jr., Adams RB (2011) Inside jokes: using humor to reverse-engineer the mind. MIT Press
Itti L, Koch C (2000) A saliency-based search mechanism for overt and covert shifts of visual attention. Vis Res 40(10–12):1489–1506
Itti L (2000) Models of bottom-up and top-down visual attention. California Institute of Technology
Itti L, Koch C (2001) Computational modelling of visual attention. Nat Rev Neurosci 2(3):194–203
Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254–1259
Itti L (2000) Models of bottom-up and top-down visual attention. California Institute of Technology
Kinchla RA, Wolfe JM (1979) The order of visual processing:“Top-down”,“bottom-up”, or “middle-out.” Percept Psychophys 25(3):225–231
Le Meur O, Le Callet P, Barba D, Thoreau D (2006) A coherent computational approach to model the bottom-up visual attention. IEEE Trans Pattern Anal Mach Intell 28:802–817
Le Meur O, Le Callet P, Barba D (2007) Predicting visual fixations on video based on low-level visual features. Vis Res 47(19):2483–2498
Limb CJ, Braun AR (2008) Neural substrates of spontaneous musical performance: an fMRI study of jazz improvisation. PLoS ONE 3:e1679. https://doi.org/10.1371/journal.pone.0001679
McGraw AP, Warren C (2010) Benign violations: Making immoral behavior funny. Psychol Sci 21(8):1141–1149
Martin RA, Ford T (2018) The psychology of humor: an integrative approach. Academic press
Martindale C (2007) Creativity, primordial cognition, and personality. Personality Individ Differ 43(7):1777–1785. https://doi.org/10.1016/j.paid.2007.05.014
Mednick S (1962) The associative basis of the creative process. Psychol Rev 69(3):220. https://doi.org/10.1037/h0048850
Melloni L, van Leeuwen S, Alink A, Müller NG (2012) Interaction between bottom-up saliency and top-down control: how saliency maps are created in the human brain. Cereb Cortex 22(12):2943–2952
Navon D, Kasten R (2011) A demonstration of direct access to colored stimuli following cueing by color. Acta Physiol (oxf) 138(1):30–38
Parkhurst D, Law K, Niebur E (2002) Modeling the role of salience in the allocation of overt visual attention. Vis Res 42(1):107–123
Pinho AL, de Manzano O, Fransson P, Eriksson H, Ullen F (2014) Connecting to create: expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas. J Neurosci 34(18):6156–6163
Raskin V (2012) Semantic mechanisms of humor, Vol 24. Springer
Rominger C, Papousek I, Perchtold CM, Benedek M, Weiss EM, Weber B, Fink A (2020) Functional coupling of brain networks during creative idea generation and elaboration in the figural domain. NeuroImage, 207
Ruch W (2001) The perception of humor. In: Emotions, qualia, and consciousness, pp 410–425
Ruch W, Attardo S, Raskin V (1993) Toward an empirical verification of the general theory of verbal humor. Humor Int J Humor Res 6(2):123–136
Schlegel A, Alexander P, Fogelson SV, Li X, Lu Z, Kohler PJ et al (2015) The artist emerges: visual art learning alters neural structure and function. Neuroimage 105:440–451
Shah C, Erhard K, Ortheil HJ, Kaza E, Kessler C, Lotze M (2013) Neural correlates of creative writing: an fMRI study. Hum Brain Mapp 34(5):1088–1101
Shahaf D, Horvitz E, Mankoff R (2015) Inside jokes: identifying humorous cartoon captions. In: Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining, pp 1065–1074
Suls JM (1972) A two-stage model for the appreciation of jokes and cartoons: an information-processing analysis. Psychol Humor Theoret Perspect Empir Issues 1:81–100
Tatler BW, Baddeley RJ, Gilchrist ID (2005) Visual correlates of fixation selection: effects of scale and time. Vis Res 45(5):643–659
Theeuwes J (2010) Top–down and bottom–up control of visual selection. Acta Physiol (oxf) 135(2):77–99
Villarreal MF, Cerquetti D, Caruso S, Schwarcz Lopez Aranguren V, Gerschcovich ER, Frega AL, Leiguarda RC (2013) Neural correlates of musical creativity: differences between high and low creative subjects. PLoS ONE 8(9):75427
Wolfe JM, Horowitz TS, Van Wert MJ, Kenner NM, Place SS, Kibbi N (2007) Low target prevalence is a stubborn source of errors in visual search tasks. J Experim Psychol :General 136(4):623
Wang Z, Klein RM (2010) Searching for inhibition of return in visual search: a review. Vis Res 50(2):220–228
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The research was supported by an NSF grant IIS-1948517 to AP and a Pomona College Faculty Grant to OA.
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Amir, O., Utterback, K.J., Lee, J. et al. The elephant in the room: attention to salient scene features increases with comedic expertise. Cogn Process 23, 203–215 (2022). https://doi.org/10.1007/s10339-022-01079-0
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DOI: https://doi.org/10.1007/s10339-022-01079-0