A team of scientists from the University of Washington and Carnegie Mellon University have developed a method by which three people can play a Tetris<\/i>-like multiplayer decision-making game together using only their minds.<\/p>\n
Researchers, Linxing Jiang, Andrea Stocco, Darby Losey, Justin Abernethy, Chantel Prat, and Rajesh Rao, created the interface, dubbed BrainNet. It\u2019s \u201cthe first multi-person non-invasive direct brain-to-brain interface for collaborative problem solving,\u201d according to their reseasrch\u00a0paper<\/a>. It allows three people in separate rooms to, essentially, network their brains and work together.<\/p>\n In order to demonstrate the effectiveness of the interface, the team came up with a new twist on the old Tetris<\/i> game. Players in Tetris<\/i> are tasked with manipulating falling blocks in order to form lines at the bottom of their screens. In the scientist\u2019s version, three players are split into two senders and one receiver.<\/p>\n The receiver is the only player that can actually manipulate the falling blocks, but they can\u2019t see the bottom of the screen to tell whether the pieces need to be rotated. The senders can see the bottom of the screen, but they can\u2019t manipulate the blocks. Thus, the senders are tasked with observing each piece and then answering the question \u201cshould this block be rotated?\u201d<\/p>\n Since humans don\u2019t have the inherit ability to transmit their thoughts to one another, the researchers got creative. They presented the senders with the options for \u201cyes\u201d and \u201cno\u201d on the screen and asked them to concentrate on the correct answer. The options on the screen pulsed with light at different frequencies. This allowed an\u00a0EEG headset device to determine which answer the sender was concentrating on by measuring their brain response.<\/p>\n The system then transmitted that information over the internet to a device that flashed a light in the receiver\u2019s eye indicating which answer had been chosen. Finally, the receiver chooses a final answer by concentrating on \u201cyes\u201d or \u201cno\u201d in the same way the senders did.<\/p>\n The researchers then fudged the experiment a bit by flipping one of the sender\u2019s answers to see if the receiver would catch on and become savvy to the fact that one of the senders was getting things wrong.<\/p>\n According to the paper:<\/p>\n Specifically, for each session, one Sender was randomly chosen as the \u201cBad\u201d Sender and, in 10 out of sixteen trials, this Sender\u2019s decision when sent to the Receiver was forced to be incorrect, both in the first and second round of each trial \u2026 We found that like conventional social networks, BrainNet allows Receivers to learn to trust the Sender who is more reliable, in this case, based solely on the information transmitted directly to their brains.<\/p>\n<\/blockquote>\n There\u2019s a veritable cornucopia of implications for this technology. The researchers posit that BrainNet could scale to enable a global brain-to-brain network. This could lead to nearly\u00a0frictionless collaboration between humans \u2013 like a social network for brains.<\/p>\n The team also hypothesizes humans using these kinds of interfaces could learn to filter out mental \u201cnoise\u201d from bad actors \u2014 possibly by developing an instinctual method for detecting that something\u2019s off<\/em> when people intentionally concentrate on an incorrect answer.<\/p>\n![\"\"](\"https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2019\/07\/bci.jpg\")
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