Look at the picture below. Does something pop out at you that you really can’t miss?
A psychologist called Ann Treisman made a study of the properties of simple patterns that make us see certain shapes (targets) within a group of distracters very distinctly. Her research found that in general the time it takes an observer to recognise and respond to the target doesn’t depend on the number of distracters. Treisman thought this was because an automatic parallel process was going on in the brain prior to the observer engaging with the pattern attentively. She called this phenomenon “pre-attentive processing”.
Pop-out effects depend on the properties of the targets in relation to the surrounding objects. If the target has a distinct property that is a feature channel of our primary visual cortex, it can be seen in a single eye fixation within less than 0.1 seconds. Features that don’t pop out require several eye movements to find, which happen at a rate of about 3 per second. The difference may appear relatively small, but in reality this is the difference between ‘at a glance’ recognition and a search that requires real cognitive effort.
Simple features that can be used to create pop outs are colour, orientation, size, motion and stereoscopic depth.
Now look at this picture and hunt for the green squares.
That took longer, didn’t it? The problem is that our primary visual cortex can be tuned to find square shapes, or green shapes, but not a target based on these two features simultaneously. Neurons sensitive to these more complex visual conjunctions are only found further up the “what” processing pathway in the brain, which can’t be used to plan eye movements.
For a pop out to exist, the feature must be sufficiently large and distinct from the variation in the feature channel in the background.
So, if you want to make something on a graph or table easy to find, make it different from its surroundings using a property of a primary visual channel. Give it a colour that is quite distinct from all the other colours on the chart, or a size that is significantly different from all the other sizes.
But what if you need to make several things searchable all at the same time? The way to do this is by using different channels that can be processed separately by the brain (most importantly orientation, size, colour and motion). You can think of these as more or less independent channels for processing visual information.
For example, in the scatter plot below (that uses simulated data) we are interested in understanding how per capita consumption of beer measured in monetary terms (and including excise duty) is determined by variations in price and volume consumed across various countries.
We have used 2D position to encode for each country the per capita consumption of beer (x axis) and unit price of beer in £ per litre (y axis). The area of each bubble represents per capita consumption of beer in £. Developing & Emerging (D&E) economies are represented by dark blue bubbles, whilst Developed (D) economies are shown by pale blue bubbles.
What pops out from this chart is that D&E markets have relatively high per capita volume consumption of beer, but their relatively low unit price means that per capita consumption measured in monetary terms is similar to all but the top 4 countries of Australia, Finland, Norway and Ireland.