Brain-computer interface (BCI)

A brain-computer interface is a system that links the electrical activity of a living brain to an electronic device such as a robot or computer. Although the term first appeared in the 1970s, groundbreaking experiments into the natural electrical processes of the body had already been taking place for about two centuries by that time. Modern brain-computer interface technologies are most commonly used in the medical field to help people offset some of the limitations of physical disabilities by sending brain commands directly to computers or robots that can perform desired tasks.

The modern brain-computer interface process typically involves three main components. The first is a device that records the brain’s electrical activity. This device is commonly a headset or a tight-fitting cap covered in small sensors that can measure electrical impulses within the brain. That device sends its data to a computer that analyzes the patterns of the activity and, using complex instructions based on prior brain research, interprets the meaning of the signals. The computer then sends its interpretations to a third device, often another computer or robot, that can perform the intended action.

Background

The brain may be the most complex and mysterious part of the human body, yet its functions are essential for survival and successful everyday living. The brain serves as a command center and information repository for the rest of the body, controlling many of its behaviors and activities. This extremely complicated process is mainly accomplished through the work of millions of neurons, or brain cells.

Neurons exist within the brain where they form intricate networks that serve various purposes among the body’s functions. Certain neural networks oversee when and how the body moves; regulate the functions of the various bodily systems, such as the respiratory and circulatory systems; interpret the information brought to the brain via the senses of sight, hearing, feeling, taste, and smell; and perform many other tasks important for regular daily living.

Neurons operate by sending information to other neurons and networks. Their means of communication are tiny signals in which chemical reactions create electricity, a process known as electrochemical signaling. An activated neuron will send a signal to a neighboring neuron that will in turn pass it along until the signal has reached the intended recipient. The passing of electrical signals from neuron to neuron is a fast and efficient way of relaying information around the brain.

People began to suspect a connection between electrical energy and the brain in ancient times. For example, in ancient Egypt and Rome, some physicians used marine animals that created electrical charges in their medical therapies. Applying these animals to a patient’s head would often result in an electric shock that, practitioners believed, could relieve headaches, arthritis, and other ailments. Despite such early experiments, the true nature of electricity and the brain remained a mystery for many more centuries.

Real understanding of the role of electricity within the body only began to develop in the eighteenth century with the work of experts such as Italian scientist Luigi Galvani, who in the 1780s used electrical jolts to cause muscle contractions in dead frogs. Almost a century later, in 1875, British scientist Richard Caton found ways to measure electrical activity within the brains of living rabbits and other animals, proving that electricity played a significant role in brain as well as muscle activity.

In 1893, a young German man named Hans Berger was seriously injured by a wagon wheel in an unforeseeable accident. Earlier that day, prior to the accident, his sister had expressed serious concerns about his safety, which seemed to Berger to have been premonitory, as if she was seeing the future. This event inspired Berger to devote much of the rest of his life to studying the mysteries of the brain.

Previous scientists had experimented with detecting and measuring electrical activity in animal brains, but Berger took this study farther to explore human brains. In the 1920s, he debuted a technique called human electroencephalography (EEG) in which electrodes, or small electric sensors, were attached to a patient’s scalp. These sensors picked up electrical activity in the brain and translated it into a wobbly pattern in ink. Though poorly understood at first, the EEG patterns showed how neurons activated and transmitted signals through the brain.

Overview

The work of these and other scientific pioneers created new horizons for study. When computer technology began to appear in the middle of the twentieth century, new generations of scientists found ways to connect the natural electronics of the brain to the artificial electronics of digital devices. Sometimes, this meant implanting computerized devices into patients’ brains. Other times, the process was non-invasive, using instead external headgear that performed largely the same functions without the need for surgery.

Experiments in the 1960s and 1970s began investigating how computer technology and brain functions might interact in living subjects. Spanish scientist José Manuel Rodríguez Delgado implanted an electrical device into the brain of a living bull. In 1964, he demonstrated that he could stop the bull from charging by sending radio signals to that embedded device. In 1969, German American scientist Eberhard E. Fetz used computerized technology to prove that monkeys could purposely alter their brain activity, as measured by the rates and patterns of electrical signals being transmitted in their brains.

The American Defense Advanced Research Projects Agency (DARPA) began investigating the nature and uses of EEG in 1970. Three years later, American scientist Jacques Vidal, working at the University of California, coined the term “brain-computer interface” (BCI) to describe the ongoing and ever-advancing research into the links between natural neural electricity and electrical devices. Vidal himself added to the study with numerous experiments that included having a human subject move a pointer through a simple maze on a computer screen using only brain electrical impulses.

This sort of experiment became the standard for many BCI tests in the coming decades, though the technology involved and the tasks being performed became increasingly advanced. Much of the research also became more practical in nature, focusing on helping people with physical disabilities perform physical tasks with the power of their brains. Scientists found ways to implant devices in animals, and then humans, by which the subjects could control robots and other computerized devices with their brain impulses.

One of the most remarkable early demonstrations of this capability was the case of Matt Nagle, an American who became paralyzed from the neck down after being stabbed. He was the first person to receive a BCI device to restore some of his lost capabilities. The procedure, which took place in 2004, ultimately enabled Nagle to perform tasks such as playing simple electronic games, opening emails, and changing television stations through the power of his brain without any physical intervention.

Modern BCI, especially in the medical context, may be used to bypass physical limitations. In a normally functioning brain, neurons send electrical impulses that carry information and instructions. Some of these instructions are known as “functional intent,” or the desire to perform a task. That task may be to speak, lift an object, stand up, or perform any other voluntary physical activity. In people with physical disabilities, the brain may be able to transmit this information about functional intent, but the body is not able to comply; for example, a person with paralysis may mentally intend to walk but be physically incapable of doing so.

Using BCI devices and techniques, a person in that situation may be able to bypass physical limitations and perform a task using technology. In short, a BCI device may read the electrical activity of the person’s brain, interpret it, and send its own signal to a robot or computer to perform the desired task. For example, a person might transmit the functional intent to pick up a book; the signal will be read by a BCI device that will instruct a robotic arm to pick up the book. Using this system, a person may be able to overcome many physical limitations.

Often, modern BCI setups correctly interpret brain signals and perform the associated tasks with high efficiency. However, sometimes they do not function as intended. For that reason, modern BCI uses artificial intelligence (AI) to “learn” and adapt using feedback from the user. For example, a user might have the intention of turning on a lamp, but the computer moves the lamp instead. The user may then provide feedback to the computer or to human operators that describes the mistake. Through this process, the computer may better interpret the user’s brainwaves, and the user may in turn learn the unique characteristics of the BCI system. For longtime BCI users, this learning process has been compared to the process that people without disabilities use to learn the capabilities of their own muscles, joints, and so on.

Most BCI research is in medical fields that intend to help people bypass the limitations of physical disabilities. However, other research involves professional applications of BCI, such as measuring driver fatigue or testing the emotional reactions of test audiences. BCI may also be used to create highly immersive video games and other entertainment experiences. Uses for BCI are likely to increase in the future as technology continues to advance.

Bibliography

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