12 April 2002 Visual evoked potential study of attention
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Abstract
Many objects in our visual field compete for neural representation. Both bottom-up, sensory-driven processes (luminance detection) as well as top-down mechanisms (attention and familiarity) can affect the result of this competition. In this study, visual evoked potentials were used to measure the changes induced by both stimulus variables and attention processes. The stimulus set consisted of a grayscale sine wave grating pattern with different degrees of spatially random noise. This stimulus set was generated using the ALOPEX optimization algorithm. This algorithm generated a series of sequential images while converging from a completely random noise pattern to the sine wave grating pattern template. All of the patterns in the stimulus set were normalized for average luminance during the ALOPEX convergence process. Additionally, the stimulus content of each pattern was quantified using a number of image processing algorithms including space-averaged global contrast, image entropy, central moments, 2D Fourier transform, and 2D wavelet transform. The visual evoked potentials were recorded using the same pattern set for different attention states of the subjects. The results presented demonstrate the contrasting affects of noise and attention on both the time and frequency components of the visual evoked potential recorded from different lobes of the brain.
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Elizabeth Uyeda, Paul J. Wojnicki, Evangelia Micheli-Tzanakou, "Visual evoked potential study of attention", Proc. SPIE 4686, Medical Imaging 2002: Image Perception, Observer Performance, and Technology Assessment, (12 April 2002); doi: 10.1117/12.462688; https://doi.org/10.1117/12.462688
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