Imagine seeing a dozen pictures flash by in a fraction of a second. You might think it would be impossible to identify any images you see for such a short time. However, a team of MIT neuroscientists has found that the human brain can process entire images seen for as little as 13 milliseconds—the first evidence of such rapid processing speed.
In the study, which appeared in Attention, Perception, and Psychophysics, researchers asked subjects whether they saw a particular type of image, such as “picnic” or “smiling couple,” as they viewed a series of six or 12 images, each presented for between 13 and 80 milliseconds. Previous studies had suggested that the brain needed to see an image for at least 100 milliseconds to identify it. The MIT team, led by brain and cognitive sciences professor Mary Potter, decided to gradually reduce the exposure until subjects’ answers were no more accurate than guesses. All images were new to the viewers.
To their surprise, the researchers found that although overall performance declined, subjects continued to perform better than chance as the image exposure time dropped from 80 milliseconds to 53 milliseconds, then 40 milliseconds, then 27, and finally 13—the shortest possible with the computer monitor being used.
“The fact that you can do that at these high speeds indicates to us that what vision does is find concepts,” Potter says. This rapid-fire processing may help direct the eyes as they shift their gaze three times per second. The eyes not only get information into the brain but “allow the brain to think about it rapidly enough to know what you should look at next,” she says.
The findings also suggest that information flowing in one direction—from the retina through the brain’s visual processing centers—is enough to identify concepts without any further feedback processing, which would add time.
Keep Reading
Most Popular
This new data poisoning tool lets artists fight back against generative AI
The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models.
Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist
An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.
Data analytics reveal real business value
Sophisticated analytics tools mine insights from data, optimizing operational processes across the enterprise.
Driving companywide efficiencies with AI
Advanced AI and ML capabilities revolutionize how administrative and operations tasks are done.
Stay connected
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.