I am usually very cautious about predicting future technological development, informed by how poorly past predictions match the present. I will, however, occasionally go out on a limb and tentatively predict when I feel certain technologies are likely to have a huge impact in the future. After all – some past predictions were fairly accurate. In the early 1990’s we felt that the Internet was about to change the world, and it did.

One such technology that I have been following is the brain-machine interface (BMI). Researchers in several institutions have been making steady progress in getting computer chips to talk to brains and vice versa. There are occasional milestones worth pointing out in this research, and I believe we have just passed one – the development of a BMI that allows a rhesus monkey to control two robot arms simultaneously.

In this study researchers used implanted electrodes to monitor the activity of 374-497 neurons from frontal and parietal cortical areas on both sides of the brain. They connected these electrodes to a computer that decoded their firing pattern, and used that pattern to control two robot arms. Monkeys with the electrodes were training using two methods – using joysticks to control the robot arms or passively watching the arms move.

Eventually the monkeys learned how to control the arms by modulating their own brain activity. But it gets much better.

One of the reasons I am optimistic about this technology is because most if not all of the major theoretical potential limitations have all turned out to be quite favorable. This study adds further evidence to one major aspect of BMI that is critical to its utility – brain plasticity. The researchers found that the areas of the brain being monitored experienced “widespread plasticity.” They changed their wiring and activity as the monkeys learned. Their brains adapted to the new task of controlling the robot arms.

This study adds a new element to this picture – the monkeys were able to control both arms independently and simultaneously. Further, using one decoder algorithm for both arms worked better than using a separate decoder for each arm. In other words, the two sides of the brain were coordinating their activity to enhance bilateral control.

Further, pairwise correlations between the two sides initially increased and then decreased with further training. This might represent the monkeys learning to coordinate the two sides and then learning how better to operate each side independently.

What this study seems to show is that the brain’s plasticity in response to BMI is sufficient to learn how to control multiple limbs at once on both sides of the body.

In addition to this plasticity of the brain, previous BMI research has also shown that primate brains can learn to adapt incoming sensory information. Further, that a robotically-controlled artificial limb can feel completely natural – it can become incorporated into the body’s sense of ownership. All of this also seems to apply equally to virtual limbs as physical limbs.

Functional BMI (real or virtual) is possible because, as neuroscientists have been learning over the last couple of decades, our brains actively construct their models of reality, including your own sense of self, that you own and control your body. This is an active process in which your brain compares several streams of sensory information with its own internal state of intention to determine how and what parts of your body it controls.

Because this is an active dynamic process, it can be hijacked and used for a BMI (and also BMBI – brain-machine-brain interfaces).

At this point the research suggests there is no practical limit to the extent to which our brains can adapt through plasticity to interfaces with machines, at least for basic sensory and motor function. It remains to be seen how BMI will work with higher cortical functions, like language. Can we implant a computer chip into our brains and instantly learn a language, or a thousand languages?

The only limitation now is the development of the technology itself. This is non-trivial. There are limits to the sensitivity with which we can read brain activity from the surface. Having wires go through the skull into the brain carries with it the risk of infection and scar tissue. Fully implanting computer chips requires portable power and has an issue with heat dissipation.

This is not going to be an easy technology to develop for practical use outside the lab. But all of the hurdles can potentially be overcome, and we are making steady progress. As computer, portable electronic, battery, and heat dissipation technologies advance, BMI will advance in lock step. Stead and significant improvement in BMI, therefore, seems inevitable.

The potential applications are enormous: replacing lost limbs with functional robotic limbs, direct brain control of remote or virtual machines, communicating with those who are locked in or similarly paralyzed, and giving them a way to control their environment, and allowing people to occupy fully virtual worlds, to name just a few of the most obviously. I’ll leave it to my readers to imagine other possible uses.

Steven Novella, M.D. is the JREF's Senior Fellow and Director of the JREF’s Science-Based Medicine project.