The central nervous system is the processing center of the body, handling important functions like breathing, consciousness, movement, thinking, and speech. It facilitates communication with the world around you by interpreting sensory inputs, including sight, sound, and smell, and producing the corresponding motor responses. Through a system of neurons known as the peripheral nervous system, the central nervous system relays this data to the appropriate regions of the body. But what if this communication is disrupted because of a medical dysfunction?
Neurological disorders, damaging the peripheral or central nervous system, can disturb this communication, having repercussions on many different yet critically essential activities. A brain-computer interface provides a bridge across this communication gap by recording the CNS activity and translating it into an artificial output that replaces, restores, enhances, supplements, or improves natural CNS outputs.
Components of BCI Systems
A BCI system consists of several crucial components designed for a specific purpose. Each of these BCI components is being extensively researched in order to create a reliable and efficient BCI system.
Neurons communicate with each other through electrical signals, generated inside the brain, which can be recorded using electrodes. When the brain reacts to a stimulus, such as moving the hand away from a fire, electrical activity is produced in the brain that can be utilized to decode the final output. Neuroscientists have mastered several methods of signal acquisition over the years, each having its own merits and demerits.
These signals are extremely weak and feature a great deal of background noise. As a result, an instrumentation amplifier is used to boost the signal. You can remove unwanted signal artifacts from the signal with either analog filters or digital filters. In order to transfer the signal to a computer for further processing, the signal is first routed through an analog-to-digital converter, where it is converted into a digital signal.
The raw digital signal coming from the signal acquisition component still has several artifacts which can lead to faulty outputs, if not eliminated. Common sources of artifacts include signal acquisition equipment, electrical interference, participant blinking, moving, speaking, and other non-experimental behaviors.
The above noise is eliminated during the preprocessing phase. Several different methods of signal filtering have been experimented with to remove the maximum possible noise.
After acquiring the clean signal, the next step is to extract useful features from it that can be used to classify the output. Features are selected on the basis that they are uncorrelated to each other and contribute significantly to the classification process.
The design of a suitable set of features is a challenging task. It involves many variables to be experimented with to get the relevant set of features for a particular BCI system, for example, the number of features, feature type, and epoch size.
The most important aspect of a BCI system is the classification process, which entails determining to which category a given collection of features belongs. The desired result should be taken into account when designing the classification algorithm. Various machine learning and deep learning models are used to optimize the classification or decoding process. The classification process helps to decipher the mental task a user is performing.
Translation and Feedback
Once the feature set has been categorized, it can be translated into the intended result. When applied to a robotic arm, for instance, it determines the arm’s speed, direction, and angle of movement. The robotic arm, also known as the feedback device, is then programmed to provide the artificial output.
Types of BCI Systems
There are three distinct categories of BCI systems depending on the mode of recording brain activity.
Non-invasive BCI systems refer to any method that does not involve performing open-brain surgery. The neural activity is captured from the scalp without the need for it to be opened. Despite the low quality of the recorded signal (which is caused by the long distance the signal must travel from the brain to the skull), the method has several useful applications due to the convenience of signal acquisition.
EEG is the most common and widely used method of recording brain signals for non-invasive BCI. In this technique, the electrical activity of the neurons is recorded by attaching electrodes to the scalp of the participant. The signals are generated due to the activity of thousands of neurons firing together. Despite its limitations in terms of signal quality and the regions of the brain that can be captured, EEG has found widespread use in research and clinical settings.
fMRI (functional Magnetic Resonance Imaging)
Whenever we use a part of the brain, neurons in that part become active and start firing. Doing so necessitates the delivery of oxygen-rich blood to the relevant area of the brain, which provides the energy necessary for the process. In the functional magnetic resonance imaging (fMRI) method, we record this fluctuation in blood oxygenation as images to determine which regions of the brain were engaged during a certain task. Clinical doctors rely heavily on this method for assessing brain function and tying certain areas of the brain to specific types of activity.
fNIRS (functional Near Infrared Spectroscopy)
While functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) both aim to record changes in blood oxygenation, fNIRS employs a distinct method. Infrared light is used in fNIRS instead of a magnetic field to measure blood flow to the brain.
Magnetometers monitor the brain’s electrical activity because, as we all remember from our high school physics lecture, the electric current creates a magnetic field. Again, this is a form of neuroimaging employed in pathology with the purpose of identifying brain abnormalities and pinpointing their precise locations in the brain.
PET (Positron Emission Tomography)
This method of neuroimaging involves injecting a tiny dose of a radioactive isotope termed “radiotracer” into a vein. It travels to the brain, where it is concentrated in the regions of active processing and depleted in the regions of rest.
For practical reasons related to the expense and bulk of the equipment needed to conduct these neuroimaging studies, they are often reserved for clinical settings.
Neurosurgery is required for invasive BCI systems, which include implanting electrodes in the brain. This setup is useful for recording high-quality single-neuronal activity, but it comes with significant health hazards. Inflammation of brain tissue and/or seizures have been linked to the implant. As a result, it is reserved for the most severely disabled individuals, such as those with paralysis or other neurological problems. Extensive research has been going on to improve these brain implants for an effective and safe BCI system.
To learn more about brain implants check out Evolution of Brain Implants.
In semi-invasive or partially-invasive BCI systems, electrodes are placed on the surface of the brain instead of in the brain. It gives higher signal quality than non-invasive systems due to the recording of brain activity from inside the skull and poses lesser health issues than invasive systems.
This technique involves recording brain activity from electrodes injected into the vascular system, i.e., blood vessels. Although this technique of recording activity dates back to the 1960s, it has recently gained more recognition due to the development of an FDA-approved brain implant that can be injected into the blood vessel without needing a craniotomy, thus maximizing its clinical utility.
Read more about endovascular technique and the new brain implant Stentrode here: A Peek Inside Synchron’s Stentrode.
ECoG is a technique similar to EEG but performed inside the skull. The electrodes are placed on the exposed surface of the brain in the form of a grid. Although it doesn’t require open-brain surgery, it still requires opening the skull and hence is only done on patients suffering from neurological disorders. This technique has been widely used in research for building efficient BCI devices.
Applications of BCI Systems
Rehabilitation and Restoration
The potential of brain-computer interface technology to recover functions lost to neurological illnesses or accidents has prompted extensive research and clinical application. People now are able to move robotic limbs, operate computer systems, type their ideas out, and even paint or sing, just by controlling their minds.
BCIs have been making their way to smart homes and offices wherein people can control appliances and other devices just by thinking about it. All of these BCI systems rely primarily on non-invasive methods, especially EEG, to record brain activity. They may also assess a person’s mental health at any given time, picking up on changes in your emotional or mental condition and giving you tips on how to improve. As a result, one’s productivity in the workplace skyrockets.
People are developing various games, especially in virtual reality, where you can control the character without having to press any keys. Many BCI enthusiasts have also developed techniques to create paintings and music with their thoughts.
BCIs have also been employed in biometric authentication. Like fingerprints, our individual patterns of brain activity can be used to verify our identity. It can also be used by people with disabilities who lack the physical traits for other biometric authentication.
Brain-computer interface technology has advanced significantly in recent decades and is now a thriving field, involving many scientists, engineers, and clinicians from around the world in an increasingly interconnected community addressing key issues and pursuing the high potential of BCI technology.
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