UCLA neuroscientist Matt Lieberman posted the 'no red pixels' image on the left. It's developed from an original by Experimental Psychologist Akiyoshi Kitaoka (right).

Remember internet kerfuffle that was 'the dress' ? Well, there's another optical illusion that's puzzling the internet right now. Behold: the red strawberries that aren't really red. Or more specifically, the image of the strawberries contains no 'red pixels.'

The important distinction to make here is that there is red information in the image (and, crucially, the relationships between colors are preserved). But despite what your eyes might be telling you, there are no pixels that appear at either end of the 'H' axis of the HSV color model. i.e. there is no pixel that, in isolation, would be considered to be red, hence: no 'red pixels' in the image.

So it's not that your brain is being tricked into inventing the red information, it's that your brain knows how much emphasis to give this red information, so that colors that it would see as cyan or grey in other contexts are interpreted as red here.

As was the case with 'the dress,' it all relates to a concept called color constancy, which relates to the human brain's ability to perceive objects as the same color under different lighting (though in this case there are unambiguous visual cues to what the 'correct' answer is).

This should immediately bring to mind a familiar photographic concept: white balance. Although there's a significant cyan cast to the whole image, your brain is able to correct for it without you having to consciously identify a neutral part of the image (as you'd need to in processing software). Does the brain's ability to correct risk us taking for granted the challenge it represents for a camera?

This got us thinking: how well would a camera's auto white balance cope with the significant color cast in this image?

Here's what a Nikon D7200's auto white balance algorithms made of the image (defocused slightly, to avoid moiré from the monitor's pixels)

The answer? Pretty well, actually. We don't know whether it's been able to detect the overall cyan cast or has assumed that the brightest point in the image is probably neutral, (and for anyone wondering whether the fact they're strawberries plays a role, it's pretty unlikely that this camera has 'strawberry recognition' mode) but it's done a good job.

We have Experimental Psychologist Akiyoshi Kitaoka to thank for turning this puzzle loose on the world, and neuroscientist Matt Lieberman for turning it viral.