Analysis: Brain-Computer Interface Technology

Written By Bobby Arvanitakis
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Brain-computer interface (BCI) technology provides a communication link between the brain and an external machine, that can be programmed to interpret the signals received from the brain to do any specific task (Shih et. al 2012). The importance of BCI technology is that it will disrupt the way we communicate with technology, and with one another, completely. With just thinking with our brain, we can control machines, we can send messages amongst ourselves, and we can allow people who are otherwise paralysed to walk, and renew their lease on life.

BCI research started off in the early 1920s by scientist Hans Berger whose work later developed to be what we now know as electroencephalography (EEG). Based on the work of scientists like Berger, the Defense Advanced Research Projects Agency (DARPA) in the 1970s would then begin developing BCI for military and defence applications. With a growing interest in military application, and the profitability of contracts awarded to industry, private organisations began incrementally developing BCI to what it is today.

Today, there are open source BCI systems that can be created cheaply through OpenBCI and NeuroScale which have brought the technology closer to home. Nodes that pick up brain signals are becoming more accurate and noninvasive, headgear is getting lighter, and equipment used to translate brain signals to usable data are getting faster and smaller.

Organisations like DARPA (Mukherjee, 2017), Facebook (Greenemeier, 2017), and Neuralink Corp (Reuters, 2017) are accelerating the development of BCI and hope to make a larger impact. Examples include typing directly from the brain on a computer.

There are two examples of BCI that’ve helped patients with paralysis which this report will cover. One example focuses on locked-in syndrome or ALS where, over time, the body’s muscles are no longer responsive, artificial respiratory devices are used to breathe, and the mouth can no longer be used to communicate. Eventually, all motion, including blinking, is no longer an option for this person and they are essentially “locked-in” to their body with full cognitive function. BCI aims to assist patients suffering from this degenerative disease by allowing them to communicate again through a computer by just using their mind.

The second example assists primates with spinal cord injury regain their ability to move again. Similarly to people with ALS, while clinical trials are showing that the technology can be used on primates, the aim of the trials is to introduce this solution to humans who’ve been in accidents and have damaged their spinal cord. BCI aims to allow the person to walk again by bypassing the signals that would not be able to pass through the spinal cord and transmitting them after the place of injury.

 

BCI Communication in Completely Locked-In State

Diagram 1: The flow diagram of BCI for communication in ALS patients. (Chaudhary, 2017)

Previous to BCI technology, people who suffered from the degenerative locked-in syndrome (ALS) were able to use nonverbal communication like finger movement, and eye tracking to communicate on a limited basis. They were typically unable to speak, as their muscles in their chest had stopped responding and breathing had to be performed artificially through the mouth. However, when the disease begins to impact the finger and eye muscles, communication is severed and the patient is considered completely locked-in (CLIS).

In an article published by PLOS (Chaudhary et. al. 2017), there is some success with BCI applications for communication with those suffering with CLIS. Patients were able to answer personal questions using “yes” or “no” response, read using a functional near-infrared spectroscopy (fNIR) machine, and then interpreted by a computer to provide the response the patient transmitted. The correct response rate was above the rate of chance and at over 70%. EEG was also used, however performance on this BCI device was less than that of the fNIR machine.

 

BCI Communication in Spinal Cord Injury

Diagram 2: Flow of how BCI enables movement again. (Capogrosso, 2016)

When a severe injury severs the spinal cord, communication from the point of injury to the rest of the body is no longer possible. While surgery is required to decompress the spine and limit chronic pain, complete severs are irreversible. BCI aims to re-establish the connection by bypassing the injury, and restoring communication between the brain and the rest of the body.

This is possible, as the region of the brain that manages movement is located in the motor cortex. A BCI interface was developed to communicate with a brain implant in the motor cortex, and send wireless signals to a pulse generator attached to a spinal implant after the injury. The pulse generator creates electrical impulses similar to those that travel down the spine, sending the signals through the remaining normal pathways to the muscles for movement. The study was successful, and a primate was able to walk again, six days after the spinal injury. (Capogrosso et. al 2016)

 

Our Analysis

Both examples use BCI to fix an issue with communication. The first example shows how people who cannot communicate without any other means, can use their mind to answer yes/no or true/false questions. The second example shows how communication can be repaired within the body.

While the second example was successful with primates (non-humans), clinical trials are being performed with humans.

Each example used different ways of reading brain activity. fNIR is non-invasive, and patients only had to wear headgear with electrodes for the trial to succeed. Whereas, an actual sensor had to be implanted into the primate’s brain, and in a specific region of the brain, for the trial to be a success.

Invasive sensors can be expensive ranging from between $5-10k (in 2017), and there is a potential of death, and complications after surgery like scar tissue developing and the body rejecting the implant. Non-invasive sensor headgear like the one in the first example costs a couple of hundred dollars. fNIR equipment is costly however, at around $10-15k. (Buccino et. al 2016)

fNIR machines are also not very mobile, so the patient has to come to the machine, and there’s no flexibility with such a large and expensive piece of equipment (Chaudhary, 2017). In contrast to the custom developed BCI interface used in the second example, the primate is able to move about and not be constrained to the technology. The custom device is light, wireless, and runs on batteries. The batteries need to be changed. (Capogrosso, 2016)

Both examples attempt to use BCI is two very different ways, but ultimately, they’re used to improve the quality of life of someone who’s lost function they previously had. The technology is attempting to reverse the impact of a disease or injury. Sometimes, not completely to the original state, but at a state that is better than the one where BCI wasn’t previously an option.

BCIs are not yet ready for commercial use. They’re expensive to operate in the case of the two examples provided, and their success rate isn’t at the level that would be compliant with everyday societal norms. While it is promising that BCI can be used to enable motor function in a spinal cord injury primates, human clinical trials need to be performed for this to become a commercial reality. There is hope, and the technology has moved leaps and bounds since brain activity was first discovered in the 1920s. With the introduction of heavy private investors, this could become a reality sooner than we expect.

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References & Further Reading

  • Chaudhary, U., Xia, B., Silvoni, S., Cohen, L.G. and Birbaumer, N., 2017. Brain–computer interface–based communication in the completely locked-in state. PLoS biology, 15(1), p.e1002593.

  • Shih, J.J., Krusienski, D.J. and Wolpaw, J.R., 2012, March. Brain-computer interfaces in medicine. In Mayo Clinic Proceedings (Vol. 87, No. 3, pp. 268-279). Elsevier.

  • Capogrosso, M., Milekovic, T., Borton, D., Wagner, F., Moraud, E.M., Mignardot, J.B., Buse, N., Gandar, J., Barraud, Q., Xing, D. and Rey, E., 2016. A brain-spine interface alleviating gait deficits after spinal cord injury in primates. Nature, 539(7628), pp.284-288. Vancouver.

  • Speier, W., Chandravadia, N., Roberts, D., Pendekanti, S. and Pouratian, N., 2017. Online BCI typing using language model classifiers by ALS patients in their homes. Brain-Computer Interfaces, 4(1-2), pp.114-121.

  • Alessio Paolo Buccino, Hasan Onur Keles, and Ahmet Omurtag, “Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks,” ed. Bin He, PLoS ONE 11, no. 1 (January 5, 2016): e0146610, doi:10.1371/journal.pone.0146610.

Bobby Arvanitakis https://hba.consulting
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