With technology today, the line between humans and machines is blurred. Our thoughts, actions and daily lives are being increasingly shaped, supported and substantiated by machines. “Neural interfacing,” a term for technology aimed at bridging the workings of machines and the human brain.
Brain-computer interface (BCI) is a connection between a brain and a device that enables signals from the brain to direct some external activity in a connected device. A challenges in developing BCI technology has been the development of electrode devices and/or surgical methods that are minimally invasive. The interface enables a direct communications between the brain and the object to be controlled by reading signals from an array of neurons and using technology to translate the signals into action. Brain-machine interfaces promise to aid paralyzed patients by re-routing movement-related signals around damaged parts of the nervous system.
HBMIs – “hybrid brain-machine interfaces” or HBMIs – will allow human brains to control artificial devices designed to restore lost sensory and motor functions. Paralysis sufferers, for example, might gain control over a motorized wheelchair or a prosthetic arm-perhaps even regain control over their own limbs.
The field of BCI research and development has since focused primarily on neuroprosthetics applications that aim at restoring damaged hearing, sight and movement. Thanks to the remarkable cortical plasticity of the brain, signals from implanted prostheses can, after adaptation, be handled by the brain like natural sensor or effector channels.
Numerous stumbling blocks remain to be overcome before human brains can interface reliably and comfortably with artificial devices, making mind-controlled prosthetic limbs or computers more than just lab curiosities. Among the key challenges are developing electrode devices and surgical methods that will allow safe, long-term recording of neuronal activities. Among the many challenges tied to developing commercially viable devices for use in patients are the bulky size of the equipment, the limited durability of the implanted electrodes, and the difficulty of developing prosthetics that can relay sensory feedback to the brain.
Important ethical, legal and societal issues related to brain-computer interfacing are:
conceptual issues (researchers disagree over what is and what is not a brain-computer interface)
obtaining informed consent from people who have difficulty communicating
shared responsibility of BCI teams (e.g. how to ensure that responsible group decisions can be made)
the consequences of BCI technology for the quality of life of patients and their families
personal responsibility and its possible constraints (e.g. who is responsible for erroneous actions with a neuroprosthesis)
issues concerning personality and personhood and its possible alteration,
therapeutic applications and their possible exceedance
questions of research ethics that arise when progressing from animal experimentation to application in human subjects
mind-reading and privacy
use of the technology in advanced interrogation techniques by governmental authorities
selective enhancement and social stratification
communication to the media
Researchers are well aware that sound ethical guidelines, appropriately moderated enthusiasm in media coverage and education about BCI systems will be of utmost importance for the societal acceptance of this technology. Thus, recently more effort is made inside the BCI community to create consensus on ethical guidelines for BCI research, development and dissemination
A brain–computer interface (BCI), sometimes called a mind-machine interface (MMI), direct neural interface (DNI), or brain–machine interface (BMI), is a direct communication pathway between the brain and an external device. Research on BCIs began in the 1970s at the University of California, Los Angeles (UCLA) under a grant from the National Science Foundation, followed by a contract from DARPA. The papers published after this research also mark the first appearance of the expression brain–computer interface in scientific literature.
Invasive BCI research has targeted repairing damaged sight and providing new functionality for people with paralysis. Invasive BCIs are implanted directly into the grey matter of the brain during neurosurgery. Because they lie in the grey matter, invasive devices produce the highest quality signals but are prone to scar tissue build up, as the body reacts to a foreign object in the brain. BCIs focusing on motor neuroprosthetics aim to either restore movement in individuals with paralysis or provide devices to assist them, such as interfaces with computers or robot arms.
Partially invasive BCIs
Partially invasive BCI devices are implanted inside the skull but rest outside the brain rather than within the grey matter. They produce better resolution signals than non-invasive BCIs where the bone tissue of the cranium deflects and deforms signals and have a lower risk of forming scar-tissue in the brain than fully invasive BCIs.
Electrocorticography (ECoG) measures the electrical activity of the brain taken from beneath the skull in a similar way to non-invasive electroencephalography but the electrodes are embedded in a thin plastic pad that is placed above the cortex, beneath the dura mater. Light reactive imaging BCI devices are still in the realm of theory. These would involve implanting a laser inside the skull. The laser would be trained on a single neuron and the neuron’s reflectance measured by a separate sensor. When the neuron fires, the laser light pattern and wavelengths it reflects would change slightly. This would allow researchers to monitor single neurons but require less contact with tissue and reduce the risk of scar-tissue build-up.
Non-invasive BCI’s are easy to wear and do not require surgery. One problem with non-invasive BCIs are they have relatively poor spatial resolution and cannot effectively use higher-frequency signals because the skull dampens signals, dispersing and blurring the electromagnetic waves created by the neurons. Noninvasive BCIs also require some time and effort prior to each usage session.
(EEG) is the most studied non-invasive interface, mainly due to its fine temporal resolution, ease of use, portability and low set-up cost. The technology is somewhat susceptible to noise however. Non-invasive BCIs have also been applied to enable brain-control of prosthetic upper and lower extremity devices in people with paralysis.
- Electronic neural networks have been deployed which shift the learning phase from the user to the computer.
- Experiments have aimed to use EEG recordings of mental activity associated with music to allow the disabled to express themselves musically through an encephalophone.
- BCI for use in biometrics to identify/authenticate a person.
- Researchers have been conducting research on using BCIs for non-disabled individuals, proposing that BCIs could improve error handling, task performance, and user experience. One area of military research is user-to-user communication through analysis of neural signals. The project “Silent Talk” aims to detect and analyze the word-specific neural signals, using EEG.
- Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) have both been used successfully as non-invasive BCIs. fMRI measurements of haemodynamic responses in real time have also been used to control robot arms with a seven-second delay between thought and movement.
Currently, there is a new field of gaming called Neurogaming, which uses non-invasive BCI in order to improve game play so that users can interact with a console without the use of a traditional controller. Some Neurogaming software use a player’s brain waves, heart rate, expressions, pupil dilation, and even emotions to complete tasks or affect the mood of the game.
Synthetic telepathy/silent communication
In a $6.3 million Army initiative to invent devices for telepathic communication, , Research into synthetic telepathy using subvocalization is taking place at the University of California, Irvine.
Researchers have built devices to interface with neural cells and entire neural networks in cultures outside animals. As well as furthering research on animal implantable devices, experiments on cultured neural tissue have focused on building problem-solving networks, constructing basic computers and manipulating robotic devices. Research into techniques for stimulating and recording from individual neurons grown on semiconductor chips is sometimes referred to as neuroelectronics or neurochips. .
Clinical and research-grade BCI-based interfaces
Some companies have been producing high-end systems that have been widely used in established BCI labs for several years. These systems typically entail more channels than the low-cost systems below, with much higher signal quality and robustness in real-world settings. Some systems from new companies have been gaining attention for new BCI applications for new user groups, such as persons with stroke or coma.
Future directions for BCIs
A consortium consisting of 12 European partners has completed a roadmap to support the European Commission in their funding decisions for the new framework program Horizon 2020. The project, which was funded by the European Commission. The road-map is now complete, and can be downloaded on the project’s webpage. A 2015 publication describes some of the analyses and achievements of this project, as well as the emerging Brain-Computer Interface Society.
Some of the directions include:
There are a couple of state-of-the-art methods, such as a functional electrical stimulation (FES) system or virtual representation of a hand.
Disorders of consciousness (DOC)
This state is defined to include research directions called RecoveriX and MoreGrasp. There are groups exploring BCI technology related to stroke recovery. The approach typically uses conventional tools for gait rehabilitation, such as an exoskeleton and EMG sensors, along with EEG-based tools to evaluate motor signals. The BCI-based approach leverages the concept of paired associative stimulation (PAS) – system’s activities are paired with the user’s movement imagery. This approach also combines BCI methods and systems de persons with coma, as well as persons in a vegetative state (VS) or minimally conscious state (MCS). BCI research seeks to help with DOC in different ways. A key initial goal is to identify patients who are able to perform basic cognitive tasks, which would of course lead to a change in their diagnosis.
In addition, these patients could then be provided with BCI-based communication tools that could help them convey basic needs, adjust bed position and HVAC (heating, ventilation, and air conditioning), and otherwise empower them to make major life decisions and communicate.
BCI research experts and medical doctors have collaborated to explore new ways to use BCI technology to improve neurosurgical mapping. This work focuses largely on
This research effort was supported in part by different EU-funded projects, such as the DECODER. This project contributed to the first BCI system developed for DOC assessment and communication, called mindBeagle. ComAlert will conduct further research and development to improve DOC prediction, assessment, rehabilitation, and communication, called “PARC” in that project.
Functional brain mapping high gamma activity, which is difficult to detect with non-invasive means. Results have led to improved methods for identifying key areas for movement, language, and other functions. A recent article addressed advances in functional brain mapping and summarizes a workshop.
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