December 12, 2024

Rachel Truong 

12th Grade

Fountain Valley High School

Introduction

Telekinesis, once a thing of fiction, might not be as impossible as we think. With brain-computer interfaces, humans can control computing systems to do whatever they want using their brain. This technological development could be one little but promising step toward manipulating objects with our brain and restoring muscle movements in those afflicted with paralysis or muscle entropy. 

In 1924, Hans Berger’s electroencephalography (EEG) facilitated the discovery of electrical activity in the brain, laying the groundwork for our current understanding of the brain. As EEG became a viable way to detect brain activity externally, Jacques Vidal began his research based on that notion, and in 1973, introduced the concept of the brain-computer interface (BCI). He demonstrated how feasible BCIs could translate brain signals detected by external devices into commands that could be executed by computers. This interface became a system which expanded the field of neurotechnology by linking more immediate connections to the neuromuscular system.

What are BCIs

Brain-computer interfaces are computer-based systems that allow individuals to control computing devices in real time by acting as a direct communication between the brain and an external output. Neural activity caused by electrical impulses are detected by invasive techniques such as implanting electrodes and removing brain tissue or non-invasive techniques which involve EEG sensors. First, signal acquisition is achieved by recording brain signals and brain wave patterns by sensors or implanted electrodes. Then, those signals are processed by algorithms to filter and digitize significant signal characteristics from extraneous content. Those significant signal characteristics that indicate the user’s intent are then reduced to compact and meaningful forms that can be interpreted by the computing system. The signals are then classified to become more viable, and then, the command is then relayed to the device that is to be controlled. The output device then displays the command which could be an action or a movement. In this way, BCIs allow individuals to control computers, robots, even prosthetics.

Applications that use BCIs 

In many instances, BCIs have proven to restore muscle movements affected by paralysis and enable movement in prostheses by only using the brain. Neuralink, one of the biggest neurotechnology companies, have developed implantable BCIs, fundamaiming to restore autonomy to those with debilitating conditions. Earlier this year, Neuralink implanted an “experimental implantable brain-computer interface” in Noland Arbaugh, who was paralyzed from a swimming accident. The connective threads from the BCI surgically implanted in his brain recorded his neural activity which then displayed the decoded message on his computer. However, this wasn’t the only patient who received a BCI implant which facilitated communication. In August, UC Davis Health developed a BCI which was the most accurate of its kind. The recipient was Casey Harrell, who suffered a neurological disorder that affects the nervous system in the brain and spinal cord, which was known as ALS. Microelectrode arrays were implanted into the left precentral gyrus, the brain region responsible for speech. This process also gave him the capability to communicate to people based on the output displayed on the screen. Even before that, researchers from Carnegie Mellon University collaborated with the University of Minnesota and built a robotic hand that could be controlled via non-invasive BCI. Many prosthetics developed in the same manner could increase the feasibility of movement for amputees in their daily lives. Enhanced with artificial intelligence, the development of BCIs could become commercially viable as less training and time is required to increase its accuracy.

Brain-computer interfaces possess the capacity to enhance cognitive performance and address neuromuscular disorders resulting from amyotrophic lateral sclerosis (ALS), myasthenia gravis, strokes, etc. As the push for a non-invasive method of accurately recording neural activity for other applications increases, brain-computer interfaces have the potential to essentially change how we move.