#human computer interface

“Humans are social beings who communicate with each other to cooperate and solve problems that none of us can solve on our own,” said corresponding author Rajesh Rao, the CJ and Elizabeth Hwang professor in the UW’s Paul G. Allen School of Computer Science & Engineering and a co-director of the Center for Neurotechnology. “We wanted to know if a group of people could collaborate using only their brains. That’s how we came up with the idea of BrainNet: where two people help a third person solve a task.”

As in Tetris, the game shows a block at the top of the screen and a line that needs to be completed at the bottom. Two people, the Senders, can see both the block and the line but can’t control the game. The third person, the Receiver, can see only the block but can tell the game whether to rotate the block to successfully complete the line. Each Sender decides whether the block needs to be rotated and then passes that information from their brain, through the internet and to the brain of the Receiver. Then the Receiver processes that information and sends a command — to rotate or not rotate the block — to the game directly from their brain, hopefully completing and clearing the line.

The team asked five groups of participants to play 16 rounds of the game. For each group, all three participants were in different rooms and couldn’t see, hear or speak to one another.

The Senders each could see the game displayed on a computer screen. The screen also showed the word “Yes” on one side and the word “No” on the other side. Beneath the “Yes” option, an LED flashed 17 times per second. Beneath the “No” option, an LED flashed 15 times a second.

“Once the Sender makes a decision about whether to rotate the block, they send ‘Yes’ or ‘No’ to the Receiver’s brain by concentrating on the corresponding light,” said first author Linxing Preston Jiang, a student in the Allen School’s combined bachelor’s/master’s degree program.

The Senders wore electroencephalography caps that picked up electrical activity in their brains. The lights’ different flashing patterns trigger unique types of activity in the brain, which the caps can pick up. So, as the Senders stared at the light for their corresponding selection, the cap picked up those signals, and the computer provided real-time feedback by displaying a cursor on the screen that moved toward their desired choice. The selections were then translated into a “Yes” or “No” answer that could be sent over the internet to the Receiver.

“To deliver the message to the Receiver, we used a cable that ends with a wand that looks like a tiny racket behind the Receiver’s head. This coil stimulates the part of the brain that translates signals from the eyes,” said co-author Andrea Stocco, a UW assistant professor in the Department of Psychology and the Institute for Learning & Brain Sciences, or I-LABS. “We essentially ‘trick’ the neurons in the back of the brain to spread around the message that they have received signals from the eyes. Then participants have the sensation that bright arcs or objects suddenly appear in front of their eyes.”

If the answer was, “Yes, rotate the block,” then the Receiver would see the bright flash. If the answer was “No,” then the Receiver wouldn’t see anything. The Receiver received input from both Senders before making a decision about whether to rotate the block. Because the Receiver also wore an electroencephalography cap, they used the same method as the Senders to select yes or no.

The Senders got a chance to review the Receiver’s decision and send corrections if they disagreed. Then, once the Receiver sent a second decision, everyone in the group found out if they cleared the line. On average, each group successfully cleared the line 81% of the time, or for 13 out of 16 trials.

The researchers wanted to know if the Receiver would learn over time to trust one Sender over the other based on their reliability. The team purposely picked one of the Senders to be a “bad Sender” and flipped their responses in 10 out of the 16 trials — so that a “Yes, rotate the block” suggestion would be given to the Receiver as “No, don’t rotate the block,” and vice versa. Over time, the Receiver switched from being relatively neutral about both Senders to strongly preferring the information from the “good Sender.”

The team hopes that these results pave the way for future brain-to-brain interfaces that allow people to collaborate to solve tough problems that one brain alone couldn’t solve. The researchers also believe this is an appropriate time to start to have a larger conversation about the ethics of this kind of brain augmentation research and developing protocols to ensure that people’s privacy is respected as the technology improves. The group is working with the Neuroethics team at the Center for Neurotechnology to address these types of issues.

“But for now, this is just a baby step. Our equipment is still expensive and very bulky and the task is a game,” Rao said. “We’re in the ‘Kitty Hawk’ days of brain interface technologies: We’re just getting off the ground.”

The ability to read electrical activities from cells is the foundation of many biomedical procedures, such as brain activity mapping and neural prosthetics. Developing new tools for intracellular electrophysiology (the electric current running within cells) that push the limits of what is physically possible (spatiotemporal resolution) while reducing invasiveness could provide a deeper understanding of electrogenic cells and their networks in tissues, as well as new directions for human-machine interfaces.

In a paper published by Nature Nanotechnology, scientists from Surrey's Advanced Technology Institute (ATI) and Harvard University detail how they produced an array of the ultra-small U-shaped nanowire field-effect transistor probes for intracellular recording. This incredibly small structure was used to record, with great clarity, the inner activity of primary neurons and other electrogenic cells, and the device has the capacity for multi-channel recordings.

Dr Yunlong Zhao from the ATI at the University of Surrey said: "If our medical professionals are to continue to understand our physical condition better and help us live longer, it is important that we continue to push the boundaries of modern science in order to give them the best possible tools to do their jobs. For this to be possible, an intersection between humans and machines is inevitable.

"Our ultra-small, flexible, nanowire probes could be a very powerful tool as they can measure intracellular signals with amplitudes comparable with those measured with patch clamp techniques; with the advantage of the device being scalable, it causes less discomfort and no fatal damage to the cell (cytosol dilation). Through this work, we found clear evidence for how both size and curvature affect device internalisation and intracellular recording signal."

Professor Charles Lieber from the Department of Chemistry and Chemical Biology at Harvard University said: "This work represents a major step towards tackling the general problem of integrating 'synthesised' nanoscale building blocks into chip and wafer scale arrays, and thereby allowing us to address the long-standing challenge of scalable intracellular recording.

"The beauty of science to many, ourselves included, is having such challenges to drive hypotheses and future work. In the longer term, we see these probe developments adding to our capabilities that ultimately drive advanced high-resolution brain-machine interfaces and perhaps eventually bringing cyborgs to reality."

Professor Ravi Silva, Director of the ATI at the University of Surrey, said: "This incredibly exciting and ambitious piece of work illustrates the value of academic collaboration. Along with the possibility of upgrading the tools we use to monitor cells, this work has laid the foundations for machine and human interfaces that could improve lives across the world."