I’m starting a new series on the blog where I discuss the science of or related to other interests I have, not just data management. One my all time favorite things to do is research a topic. I love searching the literature for that perfect article, or scouring reference sections for that rabbit hole that will take me to a new discovery. I realize that this makes me not just a nerd, by a huge nerd and I’m OK with that. (See you who call a nerd the next time you need to find an esoteric fact on the internet).
As much as I love researching, I think I might love fashion a little bit more. Although my personal style has evolved into classic minimalist with the occasional pop of something interesting, I always devour the latest fashion trends and runway looks. It only makes sense then that the first blog of this new series be about fashion….sort of.
As the warm and hazy days of summer are giving way to the crisp, cool, and in Seattle, smoky, days of fall, it’s time to bring out the plaid. That’s right, that ubiquitous fall pattern that seems to be eternally re-inventing itself. Plaid is so versatile that it can work just a well on a large scarf wrapped around a classic camel trench coat and for the iconic Alexander McQueen dress worn by Sarah Jessica Parker at the Met Gala (https://www.popsugar.com.au/celebrity/photo-gallery/41111859/image/41111810/Alexander-McQueen-Sarah-Jessica-Parker-2006) Now I know that “fall florals” are a big hit again this year, but I don’t think anything screams “Autumn is here! Start looking for a pumpkin!” quite as much as a good plaid.
A funny thing happened on the way to the Forum…oops…sorry…that’s for another time. A funny thing happened when I combined this interest in the quintessential fall pattern with my finesse for research. I found myself immersed in the world of pattern recognition and visual processing. This subject is no where near my areas of expertise and much of the jargon was hard to parse out, it was overall very fascinating.
It turns out that the plaid pattern is very useful in studying early vision processing, specifically “how the visual system processes a scene containing multiple image components with different orientations”. (1) There have been a number of studies using plaid patterns to untangle how our visual system takes multiple individual features of an image and integrates those into one perception of an object. (1)
So what is a plaid and why is it useful in this research? Plaid can be defined, very scientifically, as a “combination of two gratings whose orientations are orthogonal to each other with the same or similar contrasts”(1), or more succinctly, a pattern of unevenly spaced repeated stripes crossing at right angles. There are two features of of plaids that are useful for research into vision perception. The first is that how we perceive plaids can be altered by changing the contrast. Plaids can either be seen as checkerboards or as diamond patterns depending on the contrast of its components (1).
The coolest thing, for me at least, about plaids in visual research is the role they have played in identifying what processes are involved in spatial visual recognition. Using plaids, researchers have determined the grouping and of the outputs of the orientation spatial filters. These are components of the mammalian visual cortex that are involved with oriented lines and edges (2). These findings have been further defined by additional studies on plaids to discover contrast gain mechanisms that mediate plaid pattern detection (1).
While this hasn’t been an in-depth review of all the literature related to vision perception or plaid’s role in the research, I hope it’s given you a different perspective on fall’s signature pattern. So the next time you see that classic Burberry print or a colorful tartan, you’ll think about orientation-tuned spatial filters.
- Huang, PC and Chen, CC (2016) Contrast Gain Control in Plaid Pattern Detection. PLoS ONE 11(10): e0164171.
- Georgeson, MA and Meese, TS. (1997). Perception of Stationary Plaids: The Role of Spatial Filters in Edge Analysis. Vision Research. 37(23): pp 3255-3271.