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A Model for a Filling-in Process Triggered by Edges Predicts “Conflicting” Afterimage Effects

The goal of our research was to develop a compound computational model that predicts the “opposite” effects of the alternating aftereffects stimuli, such as the “color dove illusion” (Barkan and Spitzer, 2017), and the “filling in the afterimage after the image” (van Lier et al., 2009). The model is...

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Detalles Bibliográficos
Autores principales: Cohen-Duwek, Hadar, Spitzer, Hedva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6107801/
https://www.ncbi.nlm.nih.gov/pubmed/30174580
http://dx.doi.org/10.3389/fnins.2018.00559
Descripción
Sumario:The goal of our research was to develop a compound computational model that predicts the “opposite” effects of the alternating aftereffects stimuli, such as the “color dove illusion” (Barkan and Spitzer, 2017), and the “filling in the afterimage after the image” (van Lier et al., 2009). The model is based on a filling-in mechanism, through a diffusion equation where the color and intensity of the perceived surface are obtained through a diffusion process of color from the stimulus edges. The model solves the diffusion equation with boundary conditions that takes the locations of the chromatic edges of the chromatic inducer (chromatic stimulus) and the achromatic remaining contours into account. These contours (edges) trigger the diffusion process. The same calculations are done for both types of afterimage effects, with the only difference related to the location of the remaining contour. While a gradient toward the inducing color produces a perception of the complementary color, an opposite gradient yields the perception of the same color as that of the chromatic inducer. Furthermore, we show that the same computational model can also predict new alternating aftereffects stimuli, such as the spiral stimulus, and the averaging of colors in alternating afterimage stimuli described by Anstis et al. (2012). The suggested model is able to predict most of the additional properties related to the “conflicting” phenomena that have been recently described in the literature, and thus supports the idea that a shared visual mechanism is responsible for both the positive and the negative effects.