It is named BrainNet and it is the first multi-person non-invasive direct brain-to-brain interface. Developed by scientists at Cornell University, BrainNet allows humans to collaborate and solve a task using only brain-to-brain communication, combining the electroencephalogram (EEG) to record brain signals and transcranial magnetic stimulation (TMS) to provide information to the brain.
What is a Brain-to-Brain Interface?
Direct brain-to-brain (BBI) interfaces in humans are interfaces that combine neurostimulation and neuroimaging methods to extract and deliver information between brains, enabling direct brain-brain communication.
A BBI extracts specific contents from the neural signals of a “sending” brain, digitizes it and delivers it to a “receiver” brain. Due to ethical and safety considerations, existing human BBIs rely on non-invasive technologies, typically electroencephalography (EEG), to record neural activity and transcranial magnetic stimulation (TMS) to provide information to the brain.
First attempts to create Brain-to-Brain interfaces
The first time human brains were connected was in 2013 as part of the University of Washington research. The first BBI interface decoded the motor intention signals using the EEG in the sender and transmitted the intention via TMS directly to the motor cortex of the receiver to complete a visual-motor task.
Scientists of the University of Washington have subsequently shown in 2015 that a sender and a receiver can exchange information in an iterative way using a BBI to identify an unknown object from a list, thanks to a question and answer paradigm similar to the game “20 questions”.
However, these early attempts at BBI lack some key features of real human communication and present different limits:
- first of all, interactivity degree is minimal, for example, in the case of the BBI “20 Questions”, the sender responds only to the question chosen by the Recipient and the recipient’s performance does not affect the sender’s decision;
- secondly, this interface requires a physical action: the receiver touches the screen to select a question. Therefore, the communication cycle is completed through an engine output channel rather than a brain interface;
- thirdly, brain-to-brain communication occurs only between two subjects.
A new generation interface that overcomes the limitations of existing BBIs
BrainNet is a new generation BBI that solves many of the limitations of the previous BBIs. First, BrainNet is designed to be a brain-to-brain interface for more than two human subjects; its current implementation allows two senders and a receiver to communicate, but can easily be resized to include more senders.
Senders have the same role in observing the current status of the task and transmitting their decisions to the receiver. The receiver has the role of integrating these independent decisions and deciding on a course of action. Secondly, the BrainNet project incorporates the second cycle of interactions between the senders and the receiver, so that the receiver’s action in the first round can be perceived by the senders, giving them a second chance to transmit (potentially corrective) decisions to the receiver. Thirdly, the receiver is equipped with both TMS (to receive senders’ decisions) and EEG (to perform an action in the task), completely eliminating the need to use any physical movement to transmit information.
BrainNet: the experimental study
Scientists experimented with brain-to-brain communication of some individuals involved in a Tetris-like game. Two of the three subjects are “senders”: their brain signals are decoded using real-time EEG data analysis to extract decisions on how to rotate a block before it is released to fill a line. Senders’ decisions are transmitted by the internet to the brain of a third person, the “receiver”, who cannot see the game screen.
Decisions are delivered to the receiver’s brain by magnetic stimulation of the occipital cortex. The Receiver integrates the information received and makes a decision using an EEG interface on how to rotate the block or keep it in the same position. A second round of the game gives senders an extra chance to validate and provide feedback to the receiver’s action.
From the results of the tests, five groups of three subjects successfully used BrainNet to perform the Tetris task, with an average accuracy of 0.813. Furthermore, scientists have discovered that by varying the reliability of a sender’s information with the artificial addition of noise in the signal, Recipients are able to understand which sender is more reliable based solely on the information transmitted to their brain.
Researchers believe that the development of research could pave the way for future brain-to-brain interfaces, that can help solve problems that require the collaboration of multiple individuals using a social network of connected brains. The potential of the project is, therefore, remarkable and thanks to the internet can extend to global collaboration.
There is the potential to open up not only new frontiers in cerebral interconnection networks but also to better understand the human brain.
~Andrea Stocco, Assistant Professor and Researcher at the University of Washington
expressing all his enthusiasm by describing his vision about the potential of this study