Advertisement

Comparable search efficiency for human and animal targets in the context of natural scenes

  • Katja M. MayerEmail author
  • Ian M. Thornton
  • Quoc C. Vuong
Article
  • 40 Downloads

Abstract

In a previous series of studies, we have shown that search for human targets in the context of natural scenes is more efficient than search for mechanical targets. Here we asked whether this search advantage extends to other categories of biological objects. We used videos of natural scenes to directly contrast search efficiency for animal and human targets among biological or nonbiological distractors. In visual search arrays consisting of two, four, six, or eight videos, observers searched for animal targets among machine distractors, and vice versa (Exp. 1). Another group searched for animal targets among human distractors, and vice versa (Exp. 2). We measured search slope as a proxy for search efficiency, and complemented the slope with eye movement measurements (fixation duration on the target, as well as the proportion of first fixations landing on the target). In both experiments, we observed no differences in search slopes or proportions of first fixations between any of the target–distractor category pairs. With respect to fixation durations, we found shorter on-target fixations only for animal targets as compared to machine targets (Exp. 1). In summary, we did not find that the search advantage for human targets over mechanical targets extends to other biological objects. We also found no search advantage for detecting humans as compared to other biological objects. Overall, our pattern of findings suggests that search efficiency in natural scenes, as elsewhere, depends crucially on the specific target–distractor categories.

Keywords

Visual search Natural scenes Biological motion Biological form Eyetracking Animal motion 

Notes

Acknowledgements

Special thanks to Y. Tadmor for the provision of lab space and help with analyzing the eyetracking data.

Statement of Availability

The behavioral and eyetracking raw data will be made available upon request.

References

  1. Bahrick, L. E., Gogate, L. J., & Ruiz, I. (2002). Attention and memory for faces and actions in infancy: The salience of actions over faces in dynamic events. Child Development, 73, 1629–1643. doi: https://doi.org/10.1111/1467-8624.00495 CrossRefPubMedGoogle Scholar
  2. Bardi, L., Regolin, L., & Simion, F. (2011). Biological motion preference in humans at birth: Role of dynamic and configural properties. Developmental Science, 14, 353–359. doi: https://doi.org/10.1111/j.1467-7687.2010.00985.x CrossRefPubMedGoogle Scholar
  3. Beintema, J. A., & Lappe, M. (2002). Perception of biological motion without local image motion. Proceedings of the National Academy of Sciences, 99, 5661–5663. doi: https://doi.org/10.1073/pnas.082483699 CrossRefGoogle Scholar
  4. Bellefeuille, A., & Faubert, J. (1998). Independence of contour and biological-motion cues for motion-defined animal shapes. Perception, 27, 225–235. doi: https://doi.org/10.1068/p270225 CrossRefPubMedGoogle Scholar
  5. Bertenthal, B. I., Proffitt, D. R., & Cutting, J. E. (1984). Infant sensitivity to figural coherence in biomechanical motions. Journal of Experimental Child Psychology, 37, 213–230. doi: https://doi.org/10.1016/0022-0965(84)90001-8 CrossRefPubMedGoogle Scholar
  6. Bindemann, M., Scheepers, C., Ferguson, H. J., & Burton, A. M. (2010). Face, body, and center of gravity mediate person detection in natural scenes. Journal of Experimental Psychology: Human Perception and Performance, 36, 1477–1485. doi: https://doi.org/10.1037/a0019057 CrossRefPubMedGoogle Scholar
  7. Blake, R., & Shiffrar, M. (2007). Perception of human motion. Annual Review of Psychology, 58, 47–73. doi: https://doi.org/10.1146/annurev.psych.57.102904.190152 CrossRefPubMedGoogle Scholar
  8. Boucart, M., Lenoble, Q., Quettelart, J., Szaffarczyk, S., Despretz, P., & Thorpe, S. J. (2016). Finding faces, animals, and vehicles in far peripheral vision. Journal of Vision, 16(2), 10. doi: https://doi.org/10.1167/16.2.10 CrossRefPubMedGoogle Scholar
  9. Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433–436. doi: https://doi.org/10.1163/156856897X00357 CrossRefPubMedGoogle Scholar
  10. Bülthoff, I., Bülthoff, H., & Sinha, P. (1998). Top-down influences on stereoscopic depth-perception. Nature Neuroscience, 1, 254–257. doi: https://doi.org/10.1038/699 CrossRefPubMedGoogle Scholar
  11. Cavanagh, P., Labianca, A. T., & Thornton, I. M. (2001). Attention-based visual routines: Sprites. Cognition, 80, 47–60. doi: https://doi.org/10.1016/s0010-0277(00)00153-0 CrossRefPubMedGoogle Scholar
  12. Downing, P. E., Bray, D., Rogers, J., & Childs, C. (2004). Bodies capture attention when nothing is expected. Cognition, 93, B27–B38. doi: https://doi.org/10.1016/j.cognition.2003.10.010 CrossRefPubMedGoogle Scholar
  13. Duncan, J., & Humphreys, G. W. (1989). Visual search and stimulus similarity. Psychological Review, 96, 433–458. doi: https://doi.org/10.1037/0033-295X.96.3.433 CrossRefPubMedGoogle Scholar
  14. Eckstein, M. P. (2011). Visual search: A retrospective. Journal of Vision, 11(5), 14. doi: https://doi.org/10.1167/11.5.14 CrossRefPubMedGoogle Scholar
  15. Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149–1160. doi: https://doi.org/10.3758/BRM.41.4.1149 CrossRefPubMedGoogle Scholar
  16. Fox, R., & McDaniel, C. (1982).The perception of biological motion by human infants. Science, 218, 486–487. doi: https://doi.org/10.1126/science.7123249 CrossRefPubMedGoogle Scholar
  17. Giese, M. A., & Poggio, T. (2003). Neural mechanisms for the recognition of biological movements. Nature Reviews Neuroscience, 4, 179–192. doi: https://doi.org/10.1038/nrn1057 CrossRefPubMedGoogle Scholar
  18. Grossman, E., Donnelly, M., Price, R., Pickens, D., Morgan, V., Neighbor, G., & Blake, R. (2000). Brain areas involved in perception of biological motion. Journal of Cognitive Neuroscience, 12, 711–720. doi: https://doi.org/10.1162/089892900562417 CrossRefPubMedGoogle Scholar
  19. Han, Z. Z., Bi, Y. C., Chen, J., Chen, Q. J., He, Y., & Caramazza, A. (2013). Distinct regions of right temporal cortex are associated with biological and human-agent motion: Functional magnetic resonance imaging and neuropsychological evidence. Journal of Neuroscience, 33, 15442–15453. doi: https://doi.org/10.1523/jneurosci.5868-12.2013 CrossRefPubMedGoogle Scholar
  20. Hiris, E. (2007). Detection of biological and nonbiological motion. Journal of Vision, 7(12), 4. doi: https://doi.org/10.1167/7.12.4 CrossRefPubMedGoogle Scholar
  21. JASP Team. (2018). JASP (Version 0.10.0) [Computer software]. Retrieved from https://jasp-stats.org/download/
  22. Jastorff, J., Kourtzi, Z., & Giese, M. A. (2006). Learning to discriminate complex movements: Biological versus artificial trajectories. Journal of Vision, 6(8), 791–804. doi: https://doi.org/10.1167/6.8.3 CrossRefPubMedGoogle Scholar
  23. Johansson, G. (1973). Visual-perception of biological motion and a model for its analysis. Perception & Psychophysics, 14, 201–211. doi: https://doi.org/10.3758/bf03212378 CrossRefGoogle Scholar
  24. Jeffreys, H. (1961). Theory of probability. Oxford, UK: Oxford University Press.Google Scholar
  25. Kaiser, M. D., Shiffrar, M., & Pelphrey, K. A. (2012). Socially tuned: Brain responses differentiating human and animal motion. Social Neuroscience, 7, 301–310. doi: https://doi.org/10.1080/17470919.2011.614003 CrossRefPubMedGoogle Scholar
  26. Kleiner, M., Brainard, D., & Pelli, D. (2007). What’s new in Psychtoolbox-3? Perception, 36(ECVP Abstract Suppl.), 14.Google Scholar
  27. Koch, C., & Ullman, S. (1985). Shifts in selective visual attention: Toward the underlying neural circuitry. Human Neurobiology, 4, 219–227.PubMedGoogle Scholar
  28. Kozlowski, L. T., & Cutting, J. E. (1977). Recognizing sex of a walker from a dynamic point-light display. Perception & Psychophysics, 21, 575–580. doi: https://doi.org/10.3758/bf03198740 CrossRefGoogle Scholar
  29. Kujala, M. V., Kujala, J., Carlson, S., & Hari, R. (2012). Dog experts’ brains distinguish socially relevant body postures similarly in dogs and humans. PLoS ONE, 7, e39145. doi: https://doi.org/10.1371/journal.pone.0039145 CrossRefPubMedPubMedCentralGoogle Scholar
  30. Lange, J., & Lappe, M. (2006). A model of biological motion perception from configural form cues. Journal of Neuroscience, 26, 2894–2906.CrossRefGoogle Scholar
  31. Lobue, V., & DeLoache, J. S. (2008). Detecting the snake in the grass—Attention to fear-relevant stimuli by adults and young children. Psychological Science, 19, 284–289. doi: https://doi.org/10.1111/j.1467-9280.2008.02081.x CrossRefPubMedGoogle Scholar
  32. Mather, G., & West, S. (1993). Recognition of animal locomotion from dynamic point-light displays. Perception, 22, 759–766. doi: https://doi.org/10.1068/p220759 CrossRefPubMedGoogle Scholar
  33. Mayer, K. M., Vuong, Q. C., & Thornton, I. M. (2015). Do people “pop out”? PLoS ONE, 10, e139618. doi: https://doi.org/10.1371/journal.pone.0139618 CrossRefGoogle Scholar
  34. Mayer, K. M., Vuong, Q. C., & Thornton, I. M. (2017). Humans are detected more efficiently than machines in the context of natural scenes. Japanese Psychological Research, 59, 178–187. doi: https://doi.org/10.1111/jpr.12145 CrossRefGoogle Scholar
  35. New, J., Cosmides, L., & Tooby, J. (2007). Category-specific attention for animals reflects ancestral priorities, not expertise. Proceedings of the National Academy of Sciences, 104, 16598–16603. doi: https://doi.org/10.1073/pnas.0703913104 CrossRefGoogle Scholar
  36. Öhman, A., Flykt, A., & Esteves, F. (2001). Emotion drives attention: Detecting the snake in the grass. Journal of Experimental Psychology: General, 130, 466–478. doi: https://doi.org/10.1037/0096-3445.130.3.466 CrossRefGoogle Scholar
  37. Papeo, L., Wurm, M. F., Oosterhof, N. N., & Caramazza, A. (2017). The neural representation of human versus nonhuman bipeds and quadrupeds. Scientific Reports, 7, 14040. doi: https://doi.org/10.1038/s41598-017-14424-7 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Parkhurst, D., Law, K., & Niebur, E. (2002). Modeling the role of salience in the allocation of overt visual attention. Vision Research, 42, 107–123. doi: https://doi.org/10.1016/S0042-6989(01)00250-4 CrossRefPubMedGoogle Scholar
  39. Pavlova, M., Krageloh-Mann, I., Sokolov, A., & Birbaumer, N. (2001). Recognition of point-light biological motion displays by young children. Perception, 30, 925–933. doi: https://doi.org/10.1068/p3157 CrossRefPubMedGoogle Scholar
  40. Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision, 10, 437–442. doi: https://doi.org/10.1163/156856897X00366 CrossRefPubMedGoogle Scholar
  41. Pinto, J., & Shiffrar, M. (2009). The visual perception of human and animal motion in point-light displays. Social Neuroscience, 4, 332–346. doi: https://doi.org/10.1080/17470910902826820 CrossRefPubMedGoogle Scholar
  42. Pollick, F. E., Kay, J. W., Heim, K., & Stringer, R. (2005). Gender recognition from point-light walkers. Journal of Experimental Psychology: Human Perception and Performance, 31, 1247–1265. doi: https://doi.org/10.1037/0096-1523.31.6.1247 CrossRefPubMedGoogle Scholar
  43. Pyles, J. A., Garcia, J. O., Hoffman, D. D., & Grossman, E. D. (2007). Visual perception and neural correlates of novel “biological motion.” Vision Research, 47, 2786–2797. doi: https://doi.org/10.1016/j.visres.2007.07.017 CrossRefPubMedGoogle Scholar
  44. Ruffieux, N., Ramon, M., Lao, J. P., Colombo, F., Stacchi, L., Borruat, F. X., … Caldara, R. (2016). Residual perception of biological motion in cortical blindness. Neuropsychologia, 93, 301–311. doi: https://doi.org/10.1016/j.neuropsychologia.2016.11.009 CrossRefPubMedGoogle Scholar
  45. Saygin, A. P. (2007). Superior temporal and premotor brain areas necessary for biological motion perception. Brain, 130, 2452–2461. doi: https://doi.org/10.1093/brain/awm162 CrossRefPubMedGoogle Scholar
  46. Shi, J. F., Weng, X. C., He, S., & Jiang, Y. (2010). Biological motion cues trigger reflexive attentional orienting. Cognition, 117, 348–354. doi: https://doi.org/10.1016/j.cognition.2010.09.001 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Simion, F., Regolin, L., & Bulf, H. (2008). A predisposition for biological motion in the newborn baby. Proceedings of the National Academy of Sciences, 105, 809–813. doi: https://doi.org/10.1073/pnas.0707021105 CrossRefGoogle Scholar
  48. Thompson, J., & Parasuraman, R. (2012). Attention, biological motion, and action recognition. NeuroImage, 59, 4–13.CrossRefGoogle Scholar
  49. Thornton, I. M., Rensink, R. A., & Shiffrar, M. (2002). Active versus passive processing of biological motion. Perception, 31, 837–853.CrossRefGoogle Scholar
  50. Thornton, I. M., & Vuong, Q. C. (2004). Incidental processing of biological motion. Current Biology, 14, 1084–1089. doi: https://doi.org/10.1016/j.cub.2004.06.025 CrossRefPubMedGoogle Scholar
  51. Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12, 97–136. doi: https://doi.org/10.1016/0010-0285(80)90005-5 CrossRefPubMedGoogle Scholar
  52. Treisman, A., & Souther, J. (1985). Search asymmetry—A diagnostic for preattentive processing of separable features. Journal of Experimental Psychology: General, 114, 285–310. doi: https://doi.org/10.1037/0096-3445.114.3.285 CrossRefGoogle Scholar
  53. Troje, N. F., & Westhoff, C. (2006). The inversion effect in biological motion perception: Evidence for a “life detector”? Current Biology, 16, 821–824. doi: https://doi.org/10.1016/j.cub.2006.03.022 CrossRefPubMedGoogle Scholar
  54. van Boxtel, J. J., & Lu, H. (2012). Signature movements lead to efficient search for threatening actions. PLoS ONE, 7, e37085. doi: https://doi.org/10.1371/journal.pone.0037085 CrossRefPubMedPubMedCentralGoogle Scholar
  55. Wagenmakers, E.-J., Wetzels, R., Borsboom, D., & van der Maas, H. L. J. (2011). Why psychologists must change the way they analyze their data: The case of psi. Comment on Bem (2011). Journal of Personality and Social Psychology, 100, 426–432. doi: https://doi.org/10.1037/a0022790 CrossRefPubMedGoogle Scholar
  56. Walther, D., & Koch, C. (2006). Modeling attention to salient proto-objects. Neural Networks, 19, 1395–1407.CrossRefGoogle Scholar
  57. Wan, M., Bolger, N., & Champagne, F. A. (2012). Human perception of fear in dogs varies according to experience with dogs. PLoS ONE, 7, e51775. doi: https://doi.org/10.1371/journal.pone.0051775 CrossRefPubMedPubMedCentralGoogle Scholar
  58. Wolfe, J. M. (1998). What can 1 million trials tell us about visual search? Psychological Science, 9, 33–39. doi: https://doi.org/10.1111/1467-9280.00006 CrossRefGoogle Scholar
  59. Wolfe, J. M., & Horowitz, T. S. (2004). What attributes guide the deployment of visual attention and how do they do it? Nature Reviews Neuroscience, 5, 495–501. doi: https://doi.org/10.1038/nrn1411 CrossRefPubMedGoogle Scholar
  60. Wolfe, J. M., & Horowitz, T. S. (2017). Five factors that guide attention in visual search. Nature Human Behaviour, 1, 0058. doi: https://doi.org/10.1038/s41562-017-0058 CrossRefGoogle Scholar
  61. Zhang, X., Dash, R. K., Jacobs, E. R., Camara, A. K. S., Clough, A. V., & Audi, S. H. (2018). Integrated computational model of the bioenergetics of isolated lung mitochondria. PLoS ONE, 13, e0197921. doi: https://doi.org/10.1371/journal.pone.0197921 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© The Psychonomic Society, Inc. 2019

Authors and Affiliations

  • Katja M. Mayer
    • 1
    • 2
    Email author
  • Ian M. Thornton
    • 3
  • Quoc C. Vuong
    • 2
  1. 1.Institute for PsychologyUniversity of MuensterMuensterGermany
  2. 2.Institute of NeuroscienceNewcastle UniversityNewcastle upon TyneUK
  3. 3.Department of Cognitive Science, Faculty of Media and Knowledge SciencesUniversity of MaltaMsidaMalta

Personalised recommendations