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Brain to Brain Interface: The Science of Telepathy

By: Sai Srihaas Potu

Many of the greatest contemporary technological developments have centered on advancing human communication. From the telegraph to the Internet, the primary utility of these game-changing innovations has been to increase the range of audiences that an individual can reach.

However, most current methods for communicating are still limited by the words and symbols available to the sender and understood by the receiver. Direct brain-to-brain interfaces (BBIs) in humans are interfaces that combine neuroimaging and neurostimulation methods to extract and deliver information between brains, allowing direct brain-to-brain communication.

In a recent study, researchers have electronically linked the brains of pairs of rats for the first time, enabling them to communicate directly to solve simple behavioral puzzles. A further test of this work successfully linked the brains of two animals thousands of miles apart—one in Durham, N.C., and one in Natal, Brazil.

The results of these projects suggest the future potential for linking multiple brains to form what the research team is calling an organic computer, which could allow the sharing of motor and sensory information among groups of animals. To test this hypothesis, the researchers first trained pairs of rats to solve a simple problem: to press the correct lever when an indicator light above the lever switched on, which rewarded the rats with a sip of water. They next connected the two animals’ brains via arrays of microelectrodes inserted into the area of the cortex that processes motor information.

One of the two rodents was designated as the encoder animal. This animal received a visual cue that showed it which lever to press in exchange for a water reward. Once this encoder rat pressed the right lever, a sample of its brain activity that coded its behavioral decision was translated into a pattern of electrical stimulation that was delivered directly into the brain of the second rat, known as the decoder animal.

The decoder rat had the same types of levers in its chamber, but it did not receive any visual cue indicating which lever it should press to obtain a reward. Therefore, to press the correct lever and receive the reward it craved, the decoder rat would have to rely on the cue transmitted from the encoder via the brain-to-brain interface.

The researchers then conducted trials to determine how well the decoder animal could decipher the brain input from the encoder rat to choose the correct lever. The decoder rat ultimately achieved a maximum success rate of about 70 percent, only slightly below the possible maximum success rate of 78 percent that the researchers had theorized was achievable based on success rates of sending signals directly to the decoder rat’s brain.

Importantly, the communication provided by this brain-to-brain interface was two-way. For instance, the encoder rat did not receive a full reward if the decoder rat made a wrong choice. The result of this peculiar contingency led to the establishment of a behavioral collaboration between the pair of rats.

The researchers saw that when the decoder rat committed an error, the encoder changed both its brain function and behavior to make it easier for its partner to get it right. The encoder improved the signal-to-noise ratio of its brain activity that represented the decision, so the signal became cleaner and easier to detect. And it made a quicker, cleaner decision to choose the correct lever to press. Invariably, when the encoder made those adaptations, the decoder got the right decision more often, so they both got a better reward.

In the second set of experiments, the researchers trained pairs of rats to distinguish between a narrow or wide opening using their whiskers. If the opening was narrow, they were taught to nose-poke a water port on the left side of the chamber to receive a reward; for a wide opening, they had to poke a port on the right side.

The researchers then divided the rats into encoders and decoders. The decoders were trained to associate stimulation pulses with the left reward poke as the correct choice, and an absence of pulses with the right reward poke as correct. During trials in which the encoder detected the opening width and transmitted the choice to the decoder, the decoder had a success rate of about 65 percent, significantly above chance.

To test the transmission limits of the brain-to-brain communication, the researchers placed an encoder rat in Brazil, at the Edmond and Lily Safra International Institute of Neuroscience of Natal, and transmitted its brain signals over the Internet to a decoder rat in Durham, N.C. They found that the two rats could still work together on the tactile discrimination task. The researchers pointed out that, in theory, such a system is not limited to a pair of brains, but instead could include a network of brains or brain-net. Researchers at Duke are now working on experiments to link multiple animals cooperatively to solve more complex behavioral tasks.

This study of the sensory cortex of the decoder rats in these experiments shows that the decoder’s brain began to represent in its tactile cortex not only its whiskers but the encoder rat’s whiskers, too. The researchers detected cortical neurons that responded to both sets of whiskers, which means that the rat created a second representation of a second body on top of its own. Basic studies of such adaptations could lead to a new field called the neurophysiology of social interaction.

Such complex experiments will be enabled by the laboratory’s ability to record brain signals from almost 2,000 brain cells at once. The researchers hope to record the electrical activity produced simultaneously by 10-30,000 cortical neurons in the next five years. Such massive brain recordings will enable more precise control of motor neuroprocessing to restore motor control to paralyzed people. However, further research needs to be done to better understand the neurobiological processes that control the neural circuits in the BBI setting.


1. Hongladarom S. Brain-brain integration in 2035: metaphysical and ethical implications. Journal of Information, Communication, and Ethics in Society. 2015.

2. Miguel Pais-Vieira, Mikhail Lebedev, Carolina Kunicki, Jing Wang, Miguel A. L. Nicolelis. A Brain-to-Brain Interface for Real-Time Sharing of Sensorimotor Information. Scientific Reports. 2013.

3. Wang Y, Jung T-P. A collaborative brain-computer interface for improving human performance. PLOS ONE. 2011.


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