Attention, Perception, & Psychophysics

, Volume 81, Issue 2, pp 420–432 | Cite as

Trypophobic images induce oculomotor capture and inhibition

  • Risako ShiraiEmail author
  • Hayaki Banno
  • Hirokazu Ogawa


It is known that unpleasant images capture our attention. However, the causes of the emotions evoked by these images can vary. Trypophobia is the fear of clustered objects. A recent study claimed that this phobia is elicited by the specific power spectrum of such images. In the present study, we measured saccade trajectories to examine how trypophobic images possessing a characteristic power spectrum affect visual attention. The participants’ task was to make a saccade in the direction that was indicated by a cue. Four irrelevant images with different emotional content were presented as periphery distractors at 0 ms, 150 ms, and 450 ms in terms of cue-image onset asynchrony. The irrelevant images consisted of trypophobic, fearful, or neutral scenes. The presence of saccade trajectory deviations induced by trypophobic images suggest that intact trypophobic images oriented attention to their location. Moreover, when the images were phase scrambled, the saccade curved away from the trypophobic images, suggesting that trypophobic power spectra also triggered attentional capture, which was weak and then led to inhibition. These findings suggest that not only the power spectral characteristics but also the gist of a trypophobic image affect attentional deployment.


Trypophobia Saccade trajectory Attention Emotion 


  1. American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Washington, DC: Author.Google Scholar
  2. Bannerman, R. L., Hibbard, P. B., Chalmers, K., & Sahraie, A. (2012). Saccadic latency is modulated by emotional content of spatially filtered face stimuli. Emotion, 12(6), 1384–1392. doi:
  3. Banno, H., & Saiki, J. (2015). The use of higher-order statistics in rapid object categorization in natural scenes. Journal of Vision, 15(2), 1–20. doi:
  4. Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2007). Threat-related attentional bias in anxious and nonanxious individuals: A meta-analytic study. Psychological Bulletin, 133(1), 1–24. doi:
  5. Brainard, D. H. (1997). The psychophysics toolbox. Spatial Vision, 10, 433–436.Google Scholar
  6. Cole, G. G., & Wilkins, A. J. (2013). Fear of holes. Psychological Science, 24(10), 1–6. doi:
  7. Conlon, E., Lovegrove, W., Hine, T., Chekaluk, E., Piatek, K., & Hayes-Williams, K. (1998). The effects of visual discomfort and pattern structure on visual search. Perception, 27(1), 21–33. doi:
  8. Devue, C., Belopolsky, A. V., & Theeuwes, J. (2011). The role of fear and expectancies in capture of covert attention by spiders. Emotion, 11(4), 768–775. doi:
  9. Fernandez, D., & Wilkins, A. J. (2008). Uncomfortable images in art and nature. Perception, 37, 1098–1113. doi:
  10. Field, D. J., & Brady, N. (1997). Visual sensitivity, blur and the sources of variability in the amplitude spectra of natural scenes. Vision Research, 37, 3367–3383. doi:
  11. Fox, E., Russo, R., Bowles, R., & Dutton, K. (2001). Do threatening stimuli draw or hold visual attention in subclinical anxiety? Journal of Experimental Psychology: General, 130(4), 681–700.CrossRefGoogle Scholar
  12. Gao, X., LoBue, V., Irving, J., & Harvey, T. (2017). The effect of spatial frequency information and visual similarity in threat detection. Cognition and Emotion, 31(5), 912–922. doi:
  13. Godijn, R., & Theeuwes, J. (2004). The relationship between inhibition of return and saccade trajectory deviations. Journal of Experimental Psychology: Human Perception and Performance, 30, 538–554. doi:
  14. Hegde, J. (2008). Time course of visual perception: Coarse-to-fine processing and beyond. Progress in Neurobiology, 84(4), 405–439. doi:
  15. Kauffmann, L., Ramanoël, S., & Peyrin, C. (2014). The neural bases of spatial frequency processing during scene perception. Frontiers in Integrative Neuroscience, 8. doi:
  16. Kissler, J., & Keil, A. (2008). Look—Don’t look! How emotional pictures affect pro- and anti-saccades. Experimental Brain Research, 118, 214–222.
  17. Kovesi, P. (2000). Phase congruency: A low-level image invariant. Psychological Research, 64(2), 136–148. doi:
  18. Kovesi, P. (2003). Phase congruency detects corners and edges. In C. Sun, H. Talbot, S. Ourselin, & T. Adriaansen (Eds.), Proceedings of the VIIth Digital Image Computing: Techniques and Applications Conference (pp. 309–318). Sydney, Australia: DICTA.Google Scholar
  19. Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2005). International affective picture system (IAPS): Digitized photographs, instruction manual and affective ratings (Technical Report A-6). Gainesville: University of Florida.Google Scholar
  20. Li, F. F., VanRullen, R., Koch, C., & Perona, P. (2002). Rapid natural scene categorization in the near absence of attention. Proceedings of the National Academy of Sciences, 99(14), 9596–9601. doi:
  21. LoBue, V., & DeLoache, J. S. (2007). Detecting the snake in the grass: Attention to fear-relevant stimuli by adults and young children. Psychological Science, 19(3), 284–289. doi:
  22. Marks, I. M., & Nesse, R. M. (1994). Fear and fitness: An evolutionary analysis of anxiety disorders. Ethology and Sociobiology, 15(5), 247–261. doi:
  23. Merckelbach, H., & Muris, P. (1997). The etiology of childhood spider phobia. Behaviour Research and Therapy, 35(11), 1031–1034. doi:
  24. McPeek, R. M., Han, J. H., & Keller, E. L. (2003). Competition between saccade goals in the superior colliculus produces saccade curvature. Journal of Neurophysiology, 89(5), 2577–2590. doi:
  25. McPeek, R. M., Skavenski, A. A., & Nakayama, K. (2000). Concurrent processing of saccades in visual search. Vision Research, 40(18), 2499–2516. doi:
  26. McSorley, E., Cruickshank, A. G., & Inman, L. A. (2009). The development of the spatial extent of oculomotor inhibition. Brain Research, 1298, 92–98. doi:
  27. McSorley, E., Haggard, P., & Walker, R. (2006). Time course of oculomotor inhibition revealed by saccade trajectory modulation. Journal of Neurophysiology, 96(3), 1420–1424. doi:
  28. Nummenmaa, L., Hyönä, J., & Calvo, M. G. (2006). Eye movement assessment of selective attentional capture by emotional pictures. Emotion, 6(2), 257–268. doi:
  29. Nummenmaa, L., Hyönä, J., & Calvo, M. G. (2009). Emotional scene content drives the saccade generation system reflexively. Journal of Experimental Psychology: Human Perception and Performance, 35, 305–323. doi:
  30. O’Hare, L., & Hibbard, P. B. (2011). Spatial frequency and visual discomfort. Vision Research, 51, 1767–1777. doi:
  31. Öhman, A., Flykt, A., & Esteves, F. (2001a). Emotion drives attention: Detecting the snake in the grass. Journal of Experimental Psychology: General, 130(2), 466–478. doi:
  32. Öhman, A., Lundqvist, D., & Esteves, F. (2001b). The face in the crowd revisited: A threat advantage with schematic stimuli. Journal of Personality and Social Psychology, 80(3), 381–396. doi:
  33. Peirce, J. W. (2007). PsychoPy—Psychophysics software in Python. Journal of Neuroscience Methods, 162(1/2), 8–13. doi:
  34. Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437–442. doi:
  35. Petrova, K., & Wentura, D. (2012). Upper–lower visual field asymmetries in oculomotor inhibition of emotional distractors. Vision Research, 62, 209–219. doi:
  36. Russell, J. A., Weiss, A., & Mendelsohn, G. A. (1989). Affect Grid: A single-item scale of pleasure and arousal. Journal of Personality and Social Psychology, 57(3), 493–502. doi:
  37. Schmidt, L. J., Belopolsky, A. V., & Theeuwes, J. (2012). The presence of threat affects saccade trajectories. Visual Cognition, 20(3), 284–299. doi:
  38. Thorpe, S., Fize, D., & Marlot, C. (1996). Speed of processing in the human visual system. Nature, 381(6582), 520–522. doi:
  39. Thorpe, S. J., Gegenfurtner, K. R., Fabre-Thorpe, M., & Bülthoff, H. H. (2001). Detection of animals in natural images using far peripheral vision. European Journal of Neuroscience, 14(5), 869–876. doi:
  40. Tipples, J., Young, A.W., Quinlan, P., Broks, P., & Ellis, A.W. (2002). Searching for threat. Quarterly Journal of Experimental Psychology. A: Human Experimental Psychology, 55(3), 1007–1026. doi:
  41. Van der Stigchel, S., & Theeuwes, J. (2005). Relation between saccade trajectories and spatial distractor locations. Cognitive Brain Research, 25(2), 579–582. doi:
  42. Van der Stigchel, S., Meeter, M., & Theeuwes, J. (2006). Eye movement trajectories and what they tell us. Neuroscience and Biobehavioral Reviews, 30, 666–679. doi:
  43. Weaver, M. D., Lauwereyns, J., & Theeuwes, J. (2011). The effect of semantic information on saccade trajectory deviations. Vision Research, 51, 1124–1128. doi:
  44. Wilkins, A., Nimmo-Smith, I., Tait, A., McManus, C., Della Sala, S., Tilley, A., . . . Scott, S. (1984). A neurological basis for visual discomfort. Brain: A Journal of Neurology, 107 (4), 989–1017.Google Scholar
  45. Willenbockel, V., Sadr, J., Fiset, D., Horne, G. O., Gosselin, F., & Tanaka, J. W. (2010). Controlling low-level image properties: The SHINE toolbox. Behavior Research Methods, 42(3), 671–684.
  46. Witt, J. K., & Sugovic, M. (2013). Spiders appear to move faster than non-threatening objects regardless of one’s ability to block them. Acta Psychologica, 143(3), 284–291. doi:

Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  1. 1.Department of Integrated Psychological SciencesKwansei Gakuin UniversityNishinomiya-shiJapan
  2. 2.Tokyo Metropolitan UniversityTokyoJapan

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