This news item combines two technologies that I have been eagerly following, graphene and brain-machine interface. Researchers have developed a 1-molecule thick graphene electrode that is transparent and can be used for high-resolution electrophysiological recordings of brain cell activity.

Before I explain why this is such a cool advance, I will quickly review these technologies. Graphene is an allotrope of carbon – it is made of a single atom thick layer of carbon atoms arranged in a hexagonal sheet like chickenwire. This arrangement is very stable with strong bonds, making for a strong material. It is also flexible and has useful electrical properties. It can be manufactured as a sheet or rolled up into carbon nanotubes.

Graphene is an incredibly promising material that is likely to be the cornerstone of future electronics, promising small, efficient, and flexible components. It conducts both heat and electricity very efficiently and it is a semiconductor. “Doping” the graphene with other elements also has the potential to tweak its physical properties, expanding the number of applications.

The limiting factor is the technology for manufacturing graphene in large enough sheets to be useful. This is an area of steady advance, but right now it is still expensive to make graphene of sufficient quality. Once someone figures out how to mass produce graphene is large amounts and high quality, I think it will really take off as the next revolutionary material.

For this reason I am always excited when I hear about actual applications of graphene. In this case we are talking about specially manufactured very tiny electrodes (so not mass production), but still it’s good to see graphene put to use.

I have also been following the various research programs exploring the circuitry of the brain and ways to interface between computers and that circuitry. One limiting factor is (as you probably guessed by now) the electrodes. Electrodes can be irritating to the brain, they can be brittle or fragile, they can be opaque and not MRI friendly and therefore can interfere with imaging, and they can be noisy limiting the resolution of electrophysiological imaging. It has been very difficult, therefore, to obtain high resolution imaging and electrophysiological recordings of the same part of the brain for research.

Small thin graphene electrodes essentially solve all of these problems. The new study demonstrates an array of graphene electrodes that are thin, small, transparent, strong, flexible (so they can conform to the brain tissue), with great electrical properties (little noise). They are also less caustic than previous electrodes.

This allows for researchers to obtain high resolution mapping of the electrical activity of a part of the brain that they can also image, so that they can better correlate the anatomical structures with their electrical activity.

The present application is to study the hippocampus of rat brains. However, there are many possible applications, both research and clinical. Such electrodes could be used for better detection and characterization of seizures for possible surgical treatment, for example.

Graphene electrodes also are likely to have a much longer lifespan when transplanted into a living brain, because they are strong, small, and not caustic. They also dissipate heat very efficiently. A graphene-based computer chip would use much less energy and and produce much less heat than silicon chips.

In short graphene electrodes, computer chips, and even batteries, make transplantable brain-computer interfaces much more feasible.

Conclusion

Both graphene and the brain-machine interface are two technologies that have the potential to transform the 21st century. It is always difficult to predict future technology. It’s possible, for example, that mass production of graphene will never become economical, or that some other material will leapfrog over graphene. It’s also possible that practical applications of the brain-machine interface may be more of a technology for the 22nd century than the 21st.

Right now, however, the indicators are very good that these two technologies are going to be increasingly important in the not-too-distant future.