Neuroscience Advances Toward a “Social Network of Brains”

Source: Siphotography/istockphoto

Imagine engaging with others on social media over the cloud using only the thoughts in your brain to communicate — no texting, typing, or speech required. A recent neuroscientific breakthrough is ushering a new phase in the evolution of brain-to-brain interface (BBI) that accelerates the possibility of a “social network of brains” over the internet.

On September 23, 2018, pioneering scientists at the University of Washington and Carnegie Mellon University announced that BrainNet achieved “the first successful demonstration of multi-person non-invasive direct brain-to-brain interaction for solving a task [1].” The researchers describe BrainNet as a scalable BBI solution and the first to combine both brain stimulation and recording in a single human subject.

In the study, three participants located in different rooms were tasked to collaborate on a project that resembles a simplified version of Tetris — the once wildly-popular 80’s puzzle video game. The only communication method allowed among the three participants was through BrainNet.

Source: arXiv

BrainNet uses a non-invasive combination of electroencephalography (EEG) for recording signals from the brain, and transcranial magnetic stimulation (TMS) to stimulate the brain’s visual cortex. Two senders each use a brain-computer interface (BCI) based on EEG to impart information over a TCP/IP network to the brain of a receiver who is outfitted with a computer-brain interface (CBI) based on TMS. The senders’ decisions are converted into single TMS pulses that are delivered to the receiver’s occipital cortex. The magnetic pulse is sensed as a light flash by the receiver.

Both the senders and the receiver use steady state visually evoked potentials (SSVEPs). Participants communicated “yes” and “no” decisions regarding whether or not to rotate game pieces by directing a computer cursor using SSVEPs based on EEG. To achieve this, participants focused their attention on either a 17 Hz flashing LED to signal a “rotate,” or a 15 Hz flashing LED for a “do not rotate” decision for the puzzle piece.

The receiver makes an independent decision after integrating the decisions transmitted by the senders. If the senders’ information does not match, it is up to the receiver to decide which sender’s information is more reliable to use. Then, the receiver uses a BCI based on EEG to carry out his or her own decided maneuver. The senders are able to see the result of the receiver’s action, and are able to impart corrections to the receiver if needed.

The current study is based on binary “yes” or “no” decisions where only one bit of data is transmitted per iteration. In future studies, the research team plans to increase the bandwidth to deliver more complex data by potentially incorporating functional Magnetic Resonance Imaging (fMRI) technology in the solution.

The research team reports that BrainNet achieved results that were “significantly higher than the performance expected by chance,” with an average accuracy of 81.25% among the five triads of participants.

Scientists believe that a cloud-based BBI server could one-day enable interactions between brains worldwide, and that BrainNet is a step in that direction. What might have seemed like science-fiction is fast advancing towards becoming a reality in the not-so-far-away future.

Copyright © 2018 Cami Rosso All rights reserved.