Participants were placed in a functional magnetic resonance imaging (fMRI) machine, which allows for real-time monitoring of brain activity. They were then shown abstract shapes on a screen. These shapes were programmed to "oscillate," and the volunteers were instructed to try to stop this movement using only their minds. The researchers had previously determined a specific pattern of brain activity associated with the new visual category. The team used real-time neuroimaging and second-by-second neurofeedback. When a participant's brain activity matched this target pattern, the oscillation ceased. At the same time, a feedback mechanism "sculpted" the participants' brain activity, directing them toward the desired pattern.
The image stabilized when participants successfully reproduced a predetermined neural pattern in their brains, rather than the familiar image of the object. Thus, the scientists developed a method for learning new object categories by changing not the categories themselves, but the way the brain perceives them.
"Participants were able to respond to new object categories and behave accordingly without even being aware of those categories. This suggests that implicit learning—the brain's ability to perceive and process information without conscious awareness—also extends to the formation of new neural connections," notes study co-author Jonathan Cohen, a cognitive neuroscientist at Princeton University.
According to the researchers, they didn't simply teach the participants; they actually "inscribed" a new category into their brains, simulating the natural learning process. The experiment showed that the volunteers were indeed able to perceive this new, artificially created category.
To motivate participants, they were given a monetary reward if they managed to stop the image from oscillating. Over six daily sessions, a considerable sum could accumulate.
Scientists are investigating the neurobiological basis of various neuropsychiatric disorders, such as depression and autism. This new method could become a new tool in clinical practice. By modifying patients' brain activity patterns, they can be brought closer to neurotypical values. This opens the door to new treatment strategies that can be used both independently and in conjunction with existing therapeutic approaches. In the future, this discovery will be useful in the development of brain-computer interfaces.
