This study attempts to exploit the effects of perceptual filling-in by using an inkblot, low contrast, mild deceit, and a lack of visual cues to disrupt “normal” perceptive processes to isolate visual perception away from visual reality and measure any perceptive differences under blue light or red light exposure. Blind spots, or scotomas, are present in every functional human eye. The brain “fills-in” these scotomas with what it “expects” to see. It has been shown that stimuli can contribute to visual perception, such as color, collinear facilitation, contrast, and mood. Is it possible to influence light stimulus in such a way that the filling-in process is altered, thus manipulating visual perception as well? Future testing and implications are discussed while any extraneous variables are brought to light and debated.
When Charles Darwin claimed the eye is “an organ of extreme perfection” (Stone, 2012), he may have been unaware that the inadequacies of the eye are often corrected by the brain. For instance, every seeing person has a scotoma, or blind spot, in her vision where the optic nerve exits the retina. Most people are unaware of any scotomas due to a neural process called “filling-in” (Komatsu, 2006). This process allows a person to view a scene without any holes or gaps in his vision so that the scene itself is filled-in, making it appear seamless. The literature review focuses on various factors which have been shown to affect visual perception. Knowing that vision can be influenced by certain stimuli and that every person has at least one scotoma in each eye which must be filled-in, is it possible to influence visual perception by distorting visual context and using light as a substitute stimulus?
“When there is too little information, the brain is forced to replace the missing information with its best guess as to what that information would be” (Stone, 2012). Or as E.T. Jaynes stated, “Seeing is not a direct apprehension of reality, as we often like to pretend. Quite the contrary: seeing is inference from incomplete information…” (Stone, 2012). If all vision is partially reliant on an ability to interpret contextual surroundings to develop a filled-in picture, what factors possibly contribute to that visual perception? Though there may be limitless answers to this question, research indicates that certain stimuli can have a direct impact. As more studies emerge in the fields of visual perception and visual cognition, contrast, mood, and color have already been shown to have influences.
In their study of form perception, Ellenbogen, Polat, and Spitzer demonstrated that “Contour integration and collinear facilitation are prominent properties of form perception” (2006). When attempting to focus on an image, the contrast of nearby images adds (or subtracts) to the perceived contrast of the central image. A lower surrounding contrast (peripheral) adds to the perceived higher contrast in the central image. Conversely, a higher surrounding contrast leads the central image to be perceived as having less contrast. Both of these surrounding contrast phenomenons were shown to be influenced by the proximity of contextual stimuli or collinear facilitation (Ellenbogen, et al, 2006; Sakaguchi, 2006). In other words, contrast, in relation to collinear facilitation, can indeed influence form perception.
Mood is an amazing contributor when it comes to visual perception, specifically depression. In their study on defocused attention and depressed mood, authors von Hecker and Meiser found that “Depressed participants were better able than nondepressed participants to remember a context attribute that was irrelevant to the task at hand” (2005). Although this study was mainly to determine memory in depressed versus nondepressed persons, it found that the focus of attention was one of the largest differences. While overall performance and key detail memory was similar between the two groups, the depressed subjects showed a much higher awareness of peripheral information, or noncentral and irrelevant aspects (von Hecker, Meiser, 2005). This leads to the notion that perhaps depressed persons really do pay attention to things that don’t matter.
In addition to mood affecting perception, color has been shown to affect mood. For instance, color studies have linked certain attributes with various colors. Red has frequently been used to convey a sense of liveliness, adrenaline, or excitement as it has been shown to increase blood pressure and heart rate. Blue is known to have a calming effect and is often used to denote positions of authority. Yellow often has the greatest color impact, conveying happiness and warmth (Sask, 2011; Labrecque & Milne, 2011). One look at the marketing industry reveals the vast importance of color on product perception. As Labrecque and Milne discuss in their study of color effects in marketing, “…color carries intrinsic meaning that becomes central to the brand’s identity [and] contributes to brand recognition…” (2011). In general, colors with longer wavelengths have been shown to induce states of arousal and excitement (Labrecque and Milne, 2011), as reinforced in their study. This effect seems to be exacerbated by hue and saturation, which coincides with color wavelengths.
A study performed by Plitnick, Figueiro, Wood, and Rea attempted to discover any effects colored light had upon mood and alertness (2009). Attempting to detect differences between red and blue light, the researchers found that both red and blue light decreased sleepiness on self-reported tests, increased alertness measured by brain activity, and improved self-reports of mood. Much like this proposed study, the authors were unable to determine an inferential way to compare the results of the blue light to that of the red to determine any significant differences. However, it was reaffirmed that colored light (red and blue) can affect mood and alertness on the whole. To take this one step further, researchers Balas and Sinha (2007) examined the effects of color on perceptual filling-in and found that grayscale was often misinterpreted as color, but not the inverse. This adds to the phenomenon that the brain fills in color expectations besides just that of general image expectations.
If light affects mood and mood affects perception, is it possible light affects perception? This study would expound upon the findings of Plitnick, et al, to advance the knowledge base of whether there is a perceptual difference between the colors red and blue. As the literature review indicates, color can have an influence on mood, alertness, perception, sleepiness, and more, but is that true for all colors or do different ones elicit different responses? Although this study would not be able to make an inference as to how or how much perceptual differences vary, it would detect whether colored light (blue or red) has some overall impact on visual perception measured by positive and negative responses on a post-test questionnaire. This study attempts to disrupt the “normal” visual process by removing all visual stimuli other than the independent variable of either red light or blue light shown upon an image. Being unable to identify the image through an inkblot and low-contrast should completely isolate the light’s effect on the subject’s visual perception of the image. Therefore, the hypothesis of this study is that subjects who are shown a low contrast inkblot image illuminated in either red light or blue light will detail statistically significant positive or negative associations to describe the image shown.
Expected Findings and Discussion
This study would reaffirm that color has influence over perception as noted by marketing and other color studies. Previous studies have attempted to manipulate stimuli to achieve a different response. One of the purposes of this project is to eliminate virtually all stimuli so that all context is removed from a viewed image. Adding the stimulus (IV) of either red light or blue will be the only context, hoping to isolate any perceived emotion evoked upon the image due to the light.
Although it’s difficult to see where this laboratory phenomenon would exist, it is only meant to correlate color to the visual filling-in process. Next steps would be to test other colors to detect additional differences, yellow most notably, since it was determined to have a large effect on mood enhancement (Labrecque & Milne, 2011). Additionally, it would be interesting to note whether or not the images were following previous color studies; e.g. red = passion, blue = relaxing, yellow = warmth, and so on. It should be noted that there is no control group in this study. While red light may give one overwhelming response and blue another, how is that same image viewed under “normal” white light? Perhaps the picture itself appears scary to the average person. If so, which light, red or blue, more closely follows “normal” conditions? Besides building a profile of colors, it would be prudent to establish a control group.
One possible confounder is, do depressed participants view the low-contrast inkblot as periphery or an essential element as they focus more on the irrelevant details (von Hecker & Meiser, 2005)? No depression screening will be administered to exclude depressed subjects. The objective of this study is to determine the light’s effect on perception. Even if a participant were depressed, the lack of contextual information and no collinear stimuli would seem to render a depressed state irrelevant.
Another confounding influence is that different colored wavelengths (red and blue, presently) reach the eye at different times (Stone, 2012). Could this possibly have any effect on visual reality versus that of a manipulated laboratory environment? If it were to become definitive that color has an effect on visual perception, does that mean the “first” color seen (longest wavelength) is the one with the most influence, or perhaps only influence? If this is an actual confounder, it would presumably be the same extraneous variable found in every visual experiment ever conducted and most likely also irrelevant.
Cultural differences could have an undesired impact on color, but again, a large sample size should minimize any influence, if any. Besides, although two different cultures may have differing meanings or relationships with colors, it does not necessarily mean those connotations are opposite in perception. In other words, red could have two varying cultural associations, and both could be considered positive.
Though red or blue light may be inconsequential in and of itself, the results would lend larger implications to the effects of light on visual perception, which are on a much grander scale. As the brain completes a visual scene through perceptual filling-in, it contextually guesses what “should” be present. Well, what if a positive influence aided context in the process? Perhaps looking through rose-colored glasses really could make an actual difference.
Balas, B., & Sinha, P. (2007). “Filling-in” colour in natural scenes. Visual Cognition, 15(7), 765-778. doi:10.1080/13506280701295453.
Ellenbogen, T., Polat, U., & Spitzer, H. (2006). Chromatic collinear facilitation, further evidence for chromatic form perception. Spatial Vision, 19(6), 547-568. doi:10.1163/156856806779194062.
Komatsu, H. (2006). The neural mechanisms of perceptual filling-in. Nature Reviews.Neuroscience, 7(3), 220-31. doi:http://dx.doi.org/10.1038/nrn1869
Labrecque, L., & Milne, G. (2012). Exciting red and competent blue: The importance of color in marketing. Academy of Marketing Science Journal, 40(5), 711-727. doi:10.1007/s11747-010-0245-y.
Plitnick, B., Figueiro, M. G., Wood, B., & Rea, M. S. (2010). The effects of red and blue light on alertness and mood at night. Lighting Research and Technology, 42(4), 449-458. doi:http://dx.doi.org/10.1177/1477153509360887.
Sakaguchi, Y. (2006). Contrast dependency in perceptual filling-in. Vision Research, 46(20), 3304-3312.
Sask, R. (2011, January 22). How color affects the mood.
Stone, J. V. (2012). Vision and brain: how we perceive the world. Cambridge, MA: MIT Press.
Von Hecker, U., & Meiser, T. (2005). Defocused Attention in depressed mood: evidence from source monitoring. Emotion, 5(4), 456-463.