The colourful (or not so colourful) dress that managed to cause a massive social media divide has now become the subject of three individual scientific papers.
It’s been three months since the multi-coloured dress became the topic of Internet opinion-frenzies, and since then, scientists have been attempting to explain just how the viral phenomenon came to be. Or more specifically, how could one distinct object (picture) be so differently perceived by so many people.
The three papers were then published in Current Biology, on Thursday, each proposing a slightly different explanation for the seemingly unexplained conundrum.
The majority of viewers – 57 percent- perceived the dress as being blue and black (in normal light) while 30 percent described it as being white and gold. The remaining 11 percent saw the dress as blue and brown while 2 percent named other categories.
So despite the low quality of the picture, visual neuroscientists are finding immense study value in this unexpected tool.
One of the studies published in Current Biology claims that the color blue is ambiguous in the sense that, in blue lighting, the color blue cannot be discerned by the majority of viewers. According to Nevada University psychologist, Michael Webster, human vision is capable of determining whether white objects are being viewed in red light, however, the process isn’t the same for all colors.
Blue is, he says, a problematic color.
Webster’s approach was to initially ask participants to say whether the dress had blue or white stripes. Then, he had the dress’s colors inverted. When presented with this inverted picture, approximately 95 percent of respondents identified the dress as being yellow and black.
A second study focused on gender differences and age discrepancies in color perception. Bevil Conway, Wellesley College professor, together with his co-authors, discovered that women and elderly people were far more likely to describe the dress’ color as being white and gold.
Contrastingly, men and younger people saw it as black and blue.
Conway’s hypothesis claims that women and elderly people have different circadian rhythm particularities. They often spend their awake time during the day, so that blue sky contaminates their visual world.
Based on past experiences, your brain assumes that any ambiguity most conform to previously encountered models so it decides what a particular color is. Natural lighting and artificial lighting slightly alter this color pattern that your brain is accustomed to.
Therefore, if people spend most of their time under artificial lighting, their color perception differs from that of people spending most of their time in natural lighting. Consequently, their brain’s assumptions differ.
The third study involved a slightly smaller group of participants and was conducted at the Giessen University in Germany. A total of 15 volunteers were provided with a color wheel they could alter in order to show what colors they saw on the dress.
What Karl Gegenfurtner, lead author found, was that the colors were being perceived differently even in those groups that had identified the dress as being the same colors.
Because participants were given the option of adjusting the color they saw on the dress on a computer screen, each of them chose slightly different shades of the same color. Where some saw the color as light blue, participants explained that the tones were coming from the lighting and not the dress itself.
“Your visual system is always trying to separate out what color is coming from the lighting and what color is coming from the object,” Webster explains.
It seems that color consistency will therefore become an even more scientifically valuable topic in the future and time will tell whether scientists will be privy to additional information based on their findings.
Image Source: NY Times
Latest posts by Christina Langfold (see all)
- Scientists Discover the Second Fastest Spinning Pulsar In The Universe - Sep 9, 2017
- Coral Reef Damage Scares Florida Keys Researchers and Businesses - Jun 26, 2017
- Nike to Slash Global Workforce by 1,400 - Jun 16, 2017