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PSY 3002 SUO Illusory Stimuli & Loss of Optical Field Article Analysis

PSY 3002 SUO Illusory Stimuli & Loss of Optical Field Article Analysis

Sample Answer 

PSY 3002 SUO Illusory Stimuli & Loss of Optical Field Article Analysis

Question description

Using the South University Online Library, find two peer-reviewed journal articles on the filling-in phenomenon associated with blind spots. In your synopsis, you will include:

  • A summary of each of the journal articles
  • The main points discussed in each of the journal articles and how they relate to the week’s course and text readings
  • Your thoughts and perspectives regarding the concepts covered in each of the journal articlesPSY 3002 SUO Illusory Stimuli & Loss of Optical Field Article Analysis

Submission Details:

  • Support your responses with examples.
  • Cite any sources in APA format.

Sample Illusory Stimuli & Loss of Optical Field Article Analysis Completed Example

Article Analysis: Blind Spot

In this first article, “Computational identity between digital image inpainting and filling-in process at the blind spot” the aim is to understand digital image inpainting and its relation to filling- in process at the blind spot. Digital image inpainting is known as an algorithm in computer that has the ability to restore missing information of images that are lost in old paintings (Satoh, 2012).  This can happen with our visual system as well, known as blind spot.  In order to repair or restore old paintings or fill in missing information in the cracks and scratches of a painting a process known as retouching or inpainting must be done, using available information that surrounds such scratches.

There is a relation between filling- in process and image restoration as the article suggest that mathematical algorithms can be used to restore missing information apparent in the human eye. This can also be done through the evaluation function that is reflected upon the physiological evidence, meaning that the optimal steepest descent algorithm is used in order to obtain those resorted images in a shorter amount of time (Satoh, 2012). This fits in well with the courses readings as it relates to how computational algorithms and elements can help restore information that is missing in our eyes and the article also speaks of the consequences of such blind spot

PSY 3002 SUO Illusory Stimuli & Loss of Optical Field Article Analysis

In this second article, “Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot” the main focus is to provide new perspectives about the computational mechanism involved in filling-in process, particularly the framework of arranged predictive coding, as it provides an understanding to various neural responses that are found within the cortex. Filling-in at the blind spot is regard to as a perceptual phenomenon, as the visual system fills what is known as the informational void, this happens because of the lack of retinal input that is parallel to the optic disc which surrounds visual characteristics (Raman & Sarkar, 2016). When filling-in occurs, nonlinear neural responses can be seen particularly in the early visual area that is associated with perception. Due to the absence of photoreceptors in the optic disc, our retina cannot send a proper signal to the brain, therefore it hides a piece of our visual field, which is what we know as blind spot (Raman & Sarkar, 2016). Although it is interesting that we never notice at first glance this irregularity in our visual field.

Meanwhile, filling-in can also take place in other areas of the visual input such as both the artificial and natural retinal scotoma. Filling- in can also take place as visual illusions like neon color spreading (Raman & Sarkar, 2016). On the other hand, there have been many attempts to thoroughly understand computational mechanisms as illusory contour and surface, but only a handful of studies have been conducted to better understand the computational mechanisms of filling-in at the blind spot. Although recent research has shown that neural activities in the blind spot, particularly those found in the deep layers of V1, are in fact correlated with filling-in completion. While also suggesting that the filling-in could be a representation guided by the learned statistical regularities that are rather on the natura scene. The article correlates well with these weeks course readings, in its relation to how the brain essentially has to involve numerous process in order to actually create a whole image in our eyes.


Raman, R., & Sarkar, S. (2016). Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot. PLoS ONE, 11(3), 1–17

Satoh, S. (2012). Computational identity between digital image inpainting and filling-in process at the blind spot. Neural Computing & Applications, 21(4), 613–621.

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