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Adi Rosenthal, Vladislav Ayzenberg, Samuel Hunley, Stella Lourenco; Evolutionary-based threat modulates infants' predictive tracking of visual stimuli. Journal of Vision 2016;16(12):1047. doi: 10.1167/16.12.1047.
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Research with human and non-human primates suggests specialized visual processing of evolutionary-based threats (e.g., Ohman & Mineka, 2001). For instance, human adults and infants underestimate the arrival time of looming animals that are evolutionarily threatening (e.g., snakes and spiders) to a greater degree than nonthreatening animals (e.g., rabbits and butterflies) (Ayzenberg, Longo, & Lourenco, 2015; Vagoni, Lourenco, & Longo, 2012). However, it is unclear what accounts for this relationship between threat and visual perception. In the current study, we tested the possibility that human infants misperceive the speed of evolutionarily threatening animals. More specifically, we used a predictive tracking paradigm to determine whether the perceived speed of laterally moving images differed depending on the threat value. Twenty-six infants (8- to 11-month-olds) were presented with horizontally moving images of threatening (i.e., snakes, spiders) and non-threatening (i.e., rabbits, butterflies) animals at two velocities (50 mm/s and 100 mm/s). A portion of the movement trajectory was covered in the center by an occluder, thereby forcing infants to anticipate the image' reappearance. As in previous studies (Von Hofsten et al., 2007) infants predictively tracked the images through the occluder (p < .05) and the speed of anticipatory looks to the exit-side of the occluder scaled according to velocity (p < .05). Finally, and critically, preliminary results reveal that, among slow trials, infants' anticipatory looks were earlier for threatening than nonthreatening stimuli (p = .078, η2 = .205). These data suggest that infants' perception of speed may be modulated by the threat value of the animal, providing evidence for specialized spatiotemporal perceptual processing of evolutionary-based threat.
Meeting abstract presented at VSS 2016
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