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Yale University researchers have developed a brain-computer interface that allows users to control a video game without using their hands, learning the system in less than an hour...
A team of researchers from Yale University has developed a new brain-computer interface (BCI), which allows people to control a computer using only their brain activity. Using real-time functional magnetic resonance imaging (fMRI), the researchers showed that users can play video games and control movements on the screen with just their thoughts. The results of the study were published in the scientific journal Nature Neuroscience.
According to the researchers, the key to success lies in adapting the system to the natural way the brain works. The study showed that cerebral activity follows already consolidated neural pathways and that the learning process becomes significantly easier when the interface builds on these natural patterns, rather than contradicting them.
When the system matches the natural organization of the brain, users quickly gain control over it and the brain itself adapts to support the learning process. In contrast, systems that do not respect this structure do not bring significant improvements.
"The impact of these results is broad, from helping people with motor or communication disorders to treating depression and anxiety, as well as developing the next generation of technologies," said Erica Busch, the study's lead author.
Although brain-computer interfaces have been studied for years, many have had limited success. Previous fMRI-based systems required up to ten long training sessions, and about a third of participants failed to use them effectively.
To develop the new system, the researchers enrolled healthy young adults in four fMRI sessions. First, participants played a game where they controlled an avatar with a joystick while their brain activity was recorded.
The team then used the T-PHATE algorithm to identify the natural structure of each individual’s brain activity, known as a “neuronal manifold.” Based on this data, the researchers created three different control methods: one based on the brain’s most natural patterns, one on less dominant patterns, and one on patterns that the brain doesn’t naturally produce. The system translated brain activity into movement commands for the avatar every two seconds.
The results showed that participants learned to control the avatar in less than an hour when the system was aligned with the natural structure of the brain. In contrast, they failed to learn to use the system that relied on artificial patterns of brain activity.
The researchers also observed that, during the learning process, the brain reorganized its activity to adapt to the demands of the system. These changes extended beyond the initial target areas, indicating that BCI training affects broader neuronal networks.
According to the authors, the discovery could contribute to the development of more reliable brain-computer technologies, help people with motor or communication difficulties, and pave the way for new treatments in the field of mental health.
"By better understanding the structure of our brains, we can become better versions of ourselves," Busch said.
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