September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Characteristics of face adaptation revealed by EEG
Author Affiliations
  • Owen Gwinn
    Department of Psychology, Center for Integrative Neuroscience, University of Nevada, Reno, USA
  • Talia Retter
    Department of Psychology, Center for Integrative Neuroscience, University of Nevada, Reno, USA
    Psychological Sciences Research Institute, Institute of Neuroscience, University of Louvain, Belgium
  • Sean O'Neil
    Department of Psychology, Center for Integrative Neuroscience, University of Nevada, Reno, USA
  • Michael Webster
    Department of Psychology, Center for Integrative Neuroscience, University of Nevada, Reno, USA
Journal of Vision August 2017, Vol.17, 269. doi:10.1167/17.10.269
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      Owen Gwinn, Talia Retter, Sean O'Neil, Michael Webster; Characteristics of face adaptation revealed by EEG. Journal of Vision 2017;17(10):269. doi: 10.1167/17.10.269.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Recent work has demonstrated robust face adaptation in neural responses monitored with electroencephalography and frequency tagging (Retter & Rossion, 2016). We examined factors controlling this adaptation and whether they exhibit similar properties to the face aftereffects measured behaviorally. An average female face was contracted or expanded along the horizontal or vertical axis to form four images. Observers viewed a 20-sec sequence of the faces presented at a rate of 6 Hz, while responses were recorded with high-density EEG. This resulted in a 6 Hz signal over occipital channels, indicating that responses to each of the four distortions were equal. This sequence was repeated after 20-sec adaptation to alternations between two of the faces (e.g. horizontal contracted and expanded), with the logic that a selective response change to the adapting faces should lead to asymmetric responses during the test phase and a signal at 3 Hz. This pair has the same mean (undistorted) as the test sequence and thus should not bias responses driven only by the mean. However, adaptation instead produced a 3 Hz response that was present over right occipito-temporal sites, consistent with selective adaptation to the distortion axis. Similar biases were found when the adapting distortions were twice the magnitude of test distortions, or when adapting to a single novel distortion (e.g. expanded both horizontal and vertical) that was not part of the test sequence. These effects argue against the alternative that the neural responses are driven by prior exposure to the same image or face during adaptation and test. Instead, the neural aftereffects appear to reflect response changes induced by both the mean distortion and the contrast (variance) of the distortions. While adaptation to the mean parallels perception, the neural adaptation to variance appears stronger and may reflect processes distinct from those underlying the perceived aftereffects.

Meeting abstract presented at VSS 2017

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