Linxing Jiang, Andrea Stocco, Darby M. Losey, Justin A. Abernethy, Chantel S. Prat & Rajesh, BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains, Scientific Reports 9, Article number: 6115, 16 April 2019, https://doi.org/10.1038/s41598-019-41895-7.
Abstract: We present BrainNet which, to our knowledge, is the first multi-person non-invasive direct brain-to-brain interface for collaborative problem solving. The interface combines electroencephalography (EEG) to record brain signals and transcranial magnetic stimulation (TMS) to deliver information noninvasively to the brain. The interface allows three human subjects to collaborate and solve a task using direct brain-to-brain communication. Two of the three subjects are designated as “Senders” whose brain signals are decoded using real-time EEG data analysis. The decoding process extracts each Sender’s decision about whether to rotate a block in a Tetris-like game before it is dropped to fill a line. The Senders’ decisions are transmitted via the Internet to the brain of a third subject, the “Receiver,” who cannot see the game screen. The Senders’ decisions are delivered to the Receiver’s brain via magnetic stimulation of the occipital cortex. The Receiver integrates the information received from the two Senders and uses an EEG interface to make a decision about either turning the block or keeping it in the same orientation. A second round of the game provides an additional chance for the Senders to evaluate the Receiver’s decision and send feedback to the Receiver’s brain, and for the Receiver to rectify a possible incorrect decision made in the first round. We evaluated the performance of BrainNet in terms of (1) Group-level performance during the game, (2) True/False positive rates of subjects’ decisions, and (3) Mutual information between subjects. Five groups, each with three human subjects, successfully used BrainNet to perform the collaborative task, with an average accuracy of 81.25%. Furthermore, by varying the information reliability of the Senders by artificially injecting noise into one Sender’s signal, we investigated how the Receiver learns to integrate noisy signals in order to make a correct decision. 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. Our results point the way to future brain-to-brain interfaces that enable cooperative problem solving by humans using a “social network” of connected brains.
Brain-to-brain interfaces also span across species, with humans using noninvasive methods similar to those in the BrainNet study to control cockroaches or rats that had surgically implanted brain interfaces. In one report, a human using a noninvasive brain interface linked, via computer, to the BCI of an anesthetized rat was able to move the animal’s tail. While in another study, a human controlled a rat as a freely moving cyborg.The investigators in the new paper point out that it is the first report in which the brains of multiple humans have been linked in a completely noninvasive manner. They claim that the number of individuals whose brains could be networked is essentially unlimited. Yet the information being conveyed is currently very simple: a yes-or-no binary instruction. Other than being a very complex way to play a Tetris-like video game, where could these efforts lead?The authors propose that information transfer using noninvasive approaches could be improved by simultaneously imaging brain activity using functional magnetic resonance imaging (fMRI) in order to increase the information a sender could transmit. But fMRI is not a simple procedure, and it would expand the complexity of an already extraordinarily complex approach to sharing information. The researchers also propose that TMS could be delivered, in a focused manner, to specific brain regions in order to elicit awareness of particular semantic content in the receiver’s brain.Meanwhile the tools for more invasive—and perhaps more efficient—brain interfacing are developing rapidly. Elon Musk recently announced the development of a robotically implantable BCI containing 3,000 electrodes to provide extensive interaction between computers and nerve cells in the brain. While impressive in scope and sophistication, these efforts are dwarfed by government plans. The Defense Advanced Research Projects Agency (DARPA) has been leading engineering efforts to develop an implantable neural interface capable of engaging one million nerve cells simultaneously. While these BCIs are not being developed specifically for brain–to-brain interfacing, it is not difficult to imagine that they could be recruited for such purposes.
Color me skeptical, Why we'll never be able to build technology for Direct Brain-to-Brain Communication. Yes, such tech IS being built, but how far can it go?