• Korean Journal of Cognitive Science
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• v.27 no.1
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• pp.1-25
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• 2016

The present study investigated the effect size of attention and consciousness on change detection. We confirmed the effect size of consciousness by comparing the condition which combined attention and consciousness and the condition of attention without consciousness. Then, we confirmed the effect size of attention by comparing the condition of attention without consciousness and the control condition which excluded attention and consciousness. For this purpose, change detection task and continuous flash suppression (CFS) were used. CFS renders a highly visible image invisible. In CFS, one eye is presented with a static stimulus, while the other eye is presented with a series of rapidly changing stimuli, such as mondrian patterns. The result is that the static stimulus becomes suppressed from conscious awareness by the stimuli presented in the other eye. We used a customized device with smartphone and google cardboard instead of stereoscope to trigger CFS. In Experiment 1-1, we reenacted some study to validate our experimental setup. Our experimental setup produced the duration of stimulus suppression that were similar to those of preceding research. In Experiment 1-2, we reenacted a study for attention without consciousness using an customized device. The results showed that attention without consciousness more strongly work as a cue. We think that it is reasonable to use CFS treatment employing smartphone and google cardboard for a follow-up study. In Experiment 2, when performing the change detection task, we measured the effect size of consciousness and attention by manipulating the consciousness level of cue. We used the method in which everything but the variable of interest kept being fixed. That way, the difference this independent variable makes to the action of the entire system can be isolated. We found that there was significant difference of correct response rate on change detection performance among different consciousness level of cue. In this study, we investigated that not only the role of attention and consciousness were different also we were able to estimated the effect size.

• Science of Emotion and Sensibility
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• v.23 no.3
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• pp.47-62
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• 2020

The snake detection theory posits that, due to competition with snakes, the primate visual system has been evolved to detect camouflaged snakes. Specifically, one of its hypotheses states that the subcortical visual pathway mainly consisting of koniocellular cells enables humans to automatically detect the threat of snakes without consuming mental resources. Here we tested the hypothesis by comparing human participants' responses to snakes with those to fearful faces and flowers. Participants viewed either original images or converted ones, which lacked the differences in color, luminance, contrast, and spatial frequency energies between categories. While participants in Experiment 1 produced valence and arousal ratings to each image, those in Experiment 2 detected target images in the breaking continuous flash suppression (bCFS) paradigm. As a result, visual factors influenced the responses to snakes most strongly. After minimizing visual differences, snakes were rated as being less negative and less arousing, and detected more slowly from suppression. In contrast, the images of the other categories were less affected by image conversion. In particular, fearful faces were rated as greater threats and detected more quickly than other categories. In addition, for snakes, changes in arousal ratings and those in bCFS response times were negatively correlated: Those snake images, the arousal ratings of which decreased, produced increased detection latency. These findings suggest that the influence of snakes on human responses to threat is limited relative to fearful faces, and that detection responses in bCFS share common processing mechanisms with conscious ratings. In conclusion, the current study calls into question the assumption that snake detection in humans is a product of unconscious subcortical visual processing.