Radiologists Can’t Find a Gorilla – Selective Attention

February 11th, 2013 | Brain

Before reading this post, watch the 2 videos below:

If you’re like 50% of the people who watch the first video, you did not notice a gorilla pounding his chest in the middle of the scene.  And if you are already familiar with that one, the second video can trick you in a new way.  The basic idea of selective attention is that individuals have a tendency to process information from only one part of the environment with the exclusion of other parts.  This can be extremely important in every day life.  Consider for instance, you are driving through an intersection, and you are only looking for other cars that might hit you. While focusing on the cars, you may miss seeing a kid crossing on his bicycle.

And even more striking evidence for the importance of selective attention has recently come out of the Wolfe Lab at Harvard, it was demonstrated that radiologists may also suffer from this phenomenon at some level. The radiologists were given the image below…

Selective Attention

and were asked to search for cancerous nodules in the image. Surprisingly, 83% of the professionally trained doctors didn’t notice a size-able gorilla shaking its arm at them.

This effect worked because cancerous nodules will show up as white circles on the image, so they are “inattentionally blind” to the black gorilla — the same reason you may have missed the gorilla in the video.

Here’s how one commenter broke it down:

“I’m a radiologist. Air on xray/CT is black. The gorilla in this CT image is black. Black things in the lungs usually have no clinical significance. Cancer is white. Pneumonia is white. Acute disease (other than a collapsed lung) is white. A collapsed lung is not in this location. While the “fact” that all the radiologists missed the gorilla may be shocking to lay people, the reality is that, given appearance/location/etc in this “experiment”, it just doesn’t matter.”

Gaining a better understanding of how our brain processes information can hopefully lead to safety nets that prevent mistakes.


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