Participants were placed in a functional magnetic resonance imaging (fMRI) machine that allows them to track brain activity in real time. They were then shown abstract shapes on a screen. These shapes were programmed to “wobble,” and the volunteers were instructed to try to stop the movement using only their minds. The researchers had previously identified 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 wobble stopped. In doing so, a feedback mechanism “sculpted” the participants’ brain activity, guiding them toward the desired pattern.
The image stabilized when participants successfully reproduced in their brains not the familiar image of the object, but a predetermined neural template. Thus, the scientists developed a method for teaching new categories of objects by changing not the categories themselves, but the way the brain perceives them.
“Participants were able to respond to and behave accordingly to new categories of objects without even being aware of those categories, suggesting that implicit learning, the brain’s ability to perceive and process information without conscious input, extends to the formation of new neural connections,” said study co-author Jonathan Cohen, a cognitive neuroscientist at Princeton University.
According to the researchers, they did not simply train the participants, but actually “inscribed” a new category into their brains, simulating the process of natural learning. 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 studying the neurobiological basis of various neuropsychiatric disorders, such as depression and autism. The new method could become a new tool in clinical practice. By modifying the patterns of patients' brain activity, it is possible to bring them closer to neurotypical indicators. This opens up prospects for creating new treatment tactics that can be used both independently and in combination with existing therapeutic approaches. In the future, this discovery will be useful in the development of brain-computer interfaces.
