RockedBuzz 
There has been a significant development in the scientific world, and for the first time the human brain has been wirelessly connected to a computer. Neuroscientists say the system transmits signals “at a single neuron resolution.”
Researchers from Brown University in the US say the system is able to transmit brain signals at “single neuron resolution and full broadband precision.”
A clinical trial of BrainGate technology involved a small transmitter that connects to a person’s brain motor cortex.
Paralyzed people who participated in the experiment used a tablet computer using the system, the scientific journal IEEE Transactions on Biomedical Engineering reported.
Typing, pointing and clicking accuracy ensured
John Simeral, a professor of engineering at Brown University, said:
“We have shown that this wireless system is functionally equivalent to wired systems, which are considered the gold standard.
The signals are recorded and transmitted with similar precision accordingly, which means we can use the same decoding algorithms we use on wired equipment.
The only difference is that people no longer need to be physically attached to our equipment, which opens up new possibilities for how the system can be used. “
Neural interface technologies are also on the radar of Elon Musk and Facebook
Musk recently announced that the Neuralink initiative is already testing a wireless chip in a monkey brain that allows the monkey to play video games.
Two participants, 35 and 63 years old, in the last trial were paralyzed due to spinal cord injuries. They were able to use the wireless system continuously for up to 24 hours while at home instead of in the lab.
The relative ease of use allows trained caregivers to establish wireless connections, which means that work can continue even in conditions where the pandemic makes it impossible to visit participants’ homes.
Leigh Hochberg, a professor of engineering at Brown University and pioneering the BrainGate clinical trial, said:
“With this system, we can monitor brain activity at home and for long periods that would have been almost impossible before.
This will help us design decoding algorithms that provide smooth, intuitive, reliable communication and mobility improvement for people with paralysis. “
