New research into how the brain processes illusions bombarded mice’s neural cells with lasers, artificially reproducing the brain activity associated with false pattern recognition.
Performed by researchers at the University of California, Berkeley, and the Allen Institute, the new work identified the neural circuit and cell type in mouse brains that allow them to produce illusions. This circuit highlights the outer edges of an illusion, helping the brain predict what may be missing, according to a new paper in Nature Neuroscience.
IC-Encoder Neurons
The cells responsible for this illusion-detection activity are called “IC-encoder neurons.” Their role is to send signals prompting the brain to perceive things that aren’t actually there, through a process called recurrent pattern completion. In this process, the brain recognizes patterns and fills in missing information, helping organisms make sense of the world around them.
“Because IC–encoder neurons have this unique capacity to drive pattern completion, we think that they might have specialized synaptic output connectivity that allows them to recreate this pattern in a very effective manner,” said Hyeyoung Shin Ph.D., a researcher involved with the study who is now with Seoul University.
“We also know that they receive top-down inputs from higher visual areas,” Shin continued. “The representation of the illusion arises in higher visual areas first and then gets fed back to the primary visual cortex; and when that information is fed back, it’s received by these IC–encoders in the primary visual cortex.”
Controlling the Lower Brain
Shin, along with colleague Hillel Adesnik, led the team in presenting mice with optical illusions such as the Kanizsa triangle and monitoring their electrical brain activity. They focused on the IC-encoder neurons, using a method called two-photon holographic optogenetics to bombard the neurons with lasers. Remarkably, the same brain activity patterns appeared even when no illusion was present.
The findings help clarify the brain’s hierarchy, showing how higher regions instruct the lower visual cortex, much like a supervisor directing an employee. By comparing visual input against known images, the brain predicts what should be there. Higher levels then direct the visual cortex to “see” what isn’t actually present—something the visual cortex alone wouldn’t detect.
Illusions Help Understand the Brain
The researchers emphasize that their work has broader implications beyond illusions. Certain diseases disrupt these pattern-making processes, which the team hopes to better understand.
“In certain diseases, you have patterns of activity that emerge in your brain that are abnormal, and in schizophrenia, these are related to object representations that pop up randomly,” said co-author Jerome Lecoq. “If you don’t understand how those objects are formed and a collective set of cells work together to make those representations emerge, you’re not going to be able to treat it; so understanding which cells and in which layer this activity occurs is helpful.”
Shin and Adesnik’s project is part of the Allen Institute’s OpenScope program, which provides outside researchers with access to the institute’s advanced equipment used in parts of the experiments.
This is also the first time a feedback loop between higher and lower brain regions has been observed in mice, offering valuable context for understanding brains of varying complexity. The results show that even in simpler brains, vision is not just a passive recording, but more like a video game engine actively processing the environment.
The paper, “Recurrent Pattern Completion Drives the Neocortical Representation of Sensory Inference,” appeared in Nature Neuroscience on September 15, 2025.
Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.