Scientists have finally solved the challenging puzzle of optical illusions

For more than a century, scientists have widely understood why these illusions occur, but in all that time, experts have been unable to agree on exactly how they trick the brain. There are two possible explanations. The first explanation is that hallucinations begin with low-level neural activity and do not require past exposure to these types of hallucinations. A second explanation is that the illusion requires higher-order brain functions and reflects what the brain has already learned about the brightness and color of light over time.

In a study recently published in the journal Computational Biology has been published, researchers used a new computer model to settle this debate once and for all.

The researchers’ new model uses computer code to mimic how the network of brain cells, or neurons, that first receive data from the eye begin to decode the image before sending the data to higher-order areas of the brain for full processing. The computer model divides the image into several segments, measures the brightness of each segment, and then combines its evaluations into a single report.

The beauty of this model is that it allows individual segments to be processed at the same speed as human neurons can evaluate them, so the model matches the limitations of our vision, explains study co-author Jolyon Trosianko from the University of Exeter in the UK. The new model takes into account the speed at which neurons fire, or how quickly neurons send messages, and “this aspect of the model is new, and no one seems to have considered the impact of this on visual processing before,” Trosyanko says.