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Contextual and social cues may dominate natural visual search

Published online by Cambridge University Press:  24 May 2017

Linda Henriksson  and
Riitta Hari
Linda Henriksson
Affiliation:
Department of Neuroscience and Biomedical Engineering, Aalto University, 00076 AALTO, Finland; [email protected]://people.aalto.fi/linda_henriksson
Riitta Hari
Affiliation:
Department of Neuroscience and Biomedical Engineering, Aalto University, 00076 AALTO, Finland; [email protected]://people.aalto.fi/linda_henriksson Department of Art, Aalto University, 00076 AALTO, Finland. [email protected]://people.aalto.fi/riitta_hari
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Abstract

A framework where only the size of the functional visual field of fixations can vary is hardly able to explain natural visual-search behavior. In real-world search tasks, context guides eye movements, and task-irrelevant social stimuli may capture the gaze.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 40 , 2017 , e139
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Copyright
Copyright © Cambridge University Press 2017 

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References

Birmingham, E., Bischof, W. F. & Kingstone, A. (2008) Social attention and real-world scenes: The roles of action, competition and social content. Quarterly Journal of Experimental Psychology (Hove) 61(7):986–98.Google Scholar
Castelhano, M. S. & Henderson, J. M. (2008) Stable individual differences across images in human saccadic eye movements. Canadian Journal of Experimental Psychology 62(1):1–14.Google Scholar
Cerf, M., Frady, E. P. & Koch, C. (2009) Faces and text attract gaze independent of the task: Experimental data and computer model. Journal of Vision 9(12):10 11–15.Google Scholar
Crouzet, S. M., Kirchner, H. & Thorpe, S. J. (2010) Fast saccades toward faces: Face detection in just 100 ms. Journal of Vision 10(4):16 11–17.Google Scholar
Devue, C., Belopolsky, A. V. & Theeuwes, J. (2012) Oculomotor guidance and capture by irrelevant faces. PLoS ONE 7(4):e34598.Google Scholar
Hari, R., Henriksson, L., Malinen, S. & Parkkonen, L. (2015) Centrality of social interaction in human brain function. Neuron 88(1):181–93.Google Scholar
Hsiao, J. H. & Cottrell, G. (2008) Two fixations suffice in face recognition. Psychological Science 19(10):998–1006.Google Scholar
Krizhevsky, A., Sutskever, I. & Hinton, G. E. (2012) ImageNet classification with deep convolutional neural networks. In: Conference of Advances in neural information processing systems, ed. Pereira, F., Burges, C. J. C., Bottou, L. & Weinberger, K. Q., pp. 1097–105. Neural Information Processing Systems Foundation. Available at: https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.Google Scholar
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(6):e39145.Google Scholar
Kümmerer, M., Theis, L. & Bethge, M. (2014) Deep Gaze I: Boosting saliency prediction with feature maps trained on ImageNet. arXiv preprint arXiv:1411.1045. Available at: http://arxiv.org/abs/1411.1045.Google Scholar
Kundel, H. L., Nodine, C. F., Conant, E. F. & Weinstein, S. P. (2007) Holistic component of image perception in mammogram interpretation: Gaze-tracking study. Radiology 242(2):396–402.CrossRefGoogle ScholarPubMed
Neider, M. B. & Zelinsky, G. J. (2006) Scene context guides eye movements during visual search. Vision Research 46(5):614–21.Google Scholar
Or, C. C., Peterson, M. F. & Eckstein, M. P. (2015) Initial eye movements during face identification are optimal and similar across cultures. Journal of Vision 15(13):12.CrossRefGoogle ScholarPubMed
Peterson, M. F. & Eckstein, M. P. (2012) Looking just below the eyes is optimal across face recognition tasks. Proceedings of the National Academy of Sciences of the United States of America 109(48):E3314–23.Google ScholarPubMed
Pihko, E., Virtanen, A., Saarinen, V. M., Pannasch, S., Hirvenkari, L., Tossavainen, T., Haapala, A. & Hari, R. (2011) Experiencing art: The influence of expertise and painting abstraction level. Frontiers in Human Neuroscience 5:94.Google Scholar
Riby, D. M., Brown, P. H., Jones, N. & Hanley, M. (2012) Brief report: Faces cause less distraction in autism. Journal of Autism and Developmental Disorders 42(4):634–39.Google Scholar
Rosenholtz, R. (2016) Capabilities and limitations of peripheral vision. Annual Review of Vision Science 2:437–57.Google Scholar
Torralba, A., Oliva, A., Castelhano, M. S. & Henderson, J. M. (2006) Contextual guidance of eye movements and attention in real-world scenes: The role of global features in object search. Psychological Review. 113(4):766–86.Google Scholar
Unema, P. J. a., Pannasch, S., Joos, M. & Velichkovsky, B. M. (2005) Time course of information processing during scene perception: The relationship between saccade amplitude and fixation duration. Visual Cognition 12(3):473–94. doi: 10.1080/13506280444000409.Google Scholar
Wang, S., Jiang, M., Duchesne, X. M., Laugeson, E. A., Kennedy, D. P., Adolphs, R. & Zhao, Q. (2015) Atypical visual saliency in Autism spectrum disorder quantified through model-based eye tracking. Neuron 88(3):604–16.Google Scholar
Yarbus, A. L. (1967) Eye movements and vision. Plenum Press.Google Scholar