Brain–computer interface
A brain–computer interface (BCI), sometimes called a brain–machine interface (BMI), is a direct communication link between the brain's electrical activity and an external device, most commonly a computer or robotic limb. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.[1] They are often conceptualized as a human–machine interface that skips the intermediary of moving body parts (hands...), although they also raise the possibility of erasing the distinction between brain and machine. BCI implementations range from non-invasive (EEG, MEG, MRI) and partially invasive (ECoG and endovascular) to invasive (microelectrode array), based on how physically close electrodes are to brain tissue.[2]
For direct brain control of prosthetic devices, see Neuroprosthetics.
Research on BCIs began in the 1970s by Jacques Vidal at the University of California, Los Angeles (UCLA) under a grant from the National Science Foundation, followed by a contract from DARPA.[3][4] Vidal's 1973 paper introduced the expression brain–computer interface into scientific literature.
Due to the cortical plasticity of the brain, signals from implanted prostheses can, after adaptation, be handled by the brain like natural sensor or effector channels.[5] Following years of animal experimentation, the first neuroprosthetic devices were implanted in humans in the mid-1990s.
Studies in human-computer interaction via the application of machine learning to statistical temporal features extracted from the frontal lobe (EEG brainwave) data has achieved success in classifying mental states (relaxed, neutral, concentrating),[6] mental emotional states (negative, neutral, positive),[7] and thalamocortical dysrhythmia.[8]
History[edit]
The history of brain-computer interfaces (BCIs) starts with Hans Berger's discovery of the brain's electrical activity and the development of electroencephalography (EEG). In 1924 Berger was the first to record human brain activity utilizing EEG. Berger was able to identify oscillatory activity, such as the alpha wave (8–13 Hz), by analyzing EEG traces.
Berger's first recording device was rudimentary. He inserted silver wires under the scalps of his patients. These were later replaced by silver foils attached to the patient's head by rubber bandages. Berger connected these sensors to a Lippmann capillary electrometer, with disappointing results. However, more sophisticated measuring devices, such as the Siemens double-coil recording galvanometer, which displayed voltages as small as 10-4 volt, led to success.
Berger analyzed the interrelation of alternations in his EEG wave diagrams with brain diseases. EEGs permitted completely new possibilities for brain research.
Although the term had not yet been coined, one of the earliest examples of a working brain-machine interface was the piece Music for Solo Performer (1965) by American composer Alvin Lucier. The piece makes use of EEG and analog signal processing hardware (filters, amplifiers, and a mixing board) to stimulate acoustic percussion instruments. Performing the piece requires producing alpha waves and thereby "playing" the various instruments via loudspeakers that are placed near or directly on the instruments.[9]
Vidal coined the term "BCI" and produced the first peer-reviewed publications on this topic.[3][4] He is widely recognized as the inventor of BCIs.[10][11][12] A review pointed out that Vidal's 1973 paper stated the "BCI challenge"[13] of controlling external objects using EEG signals, and especially use of Contingent Negative Variation (CNV) potential as a challenge for BCI control. Vidal's 1977 experiment was the first application of BCI after his 1973 BCI challenge. It was a noninvasive EEG (actually Visual Evoked Potentials (VEP)) control of a cursor-like graphical object on a computer screen. The demonstration was movement in a maze.[14]
1988 was the first demonstration of noninvasive EEG control of a physical object, a robot. The experiment demonstrated EEG control of multiple start-stop-restart cycles of movement, along an arbitrary trajectory defined by a line drawn on a floor. The line-following behavior was the default robot behavior, utilizing autonomous intelligence and an autonomous energy source.[15][16][17][18]
In 1990, a report was given on a closed loop, bidirectional, adaptive BCI controlling a computer buzzer by an anticipatory brain potential, the Contingent Negative Variation (CNV) potential.[19][20] The experiment described how an expectation state of the brain, manifested by CNV, used a feedback loop to control the S2 buzzer in the S1-S2-CNV paradigm. The resulting cognitive wave representing the expectation learning in the brain was termed Electroexpectogram (EXG). The CNV brain potential was part of Vidal's 1973 challenge.
Studies in the 2010s suggested neural stimulation's potential to restore functional connectivity and associated behaviors through modulation of molecular mechanisms.[21][22] This opened the door for the concept that BCI technologies may be able to restore function.
Beginning in 2013, DARPA funded BCI technology through the BRAIN initiative, which supported work out of teams including University of Pittsburgh Medical Center,[23] Paradromics,[24] Brown,[25] and Synchron.[26]
Human research[edit]
Invasive BCIs[edit]
Invasive BCI requires surgery to implant electrodes under the scalp for accessing brain signals. The main advantage is to increase accuracy. Downsides include side effects from the surgery, including scar tissue that can obstruct brain signals or the body may not accept the implanted electrodes.[56]
Collaborative BCIs[edit]
The idea of combining/integrating brain signals from multiple individuals was introduced at Humanity+ @Caltech, in December 2010, by Adrian Stoica, who referred to the concept as multi-brain aggregation.[170][171][172] A patent was applied for in 2012.[173][174][175] Stoica's first paper on the topic appeared in 2012, after the publication of his patent application.[176]
Ethical considerations[edit]
BCIs present significant ethical questions, including concerns about privacy, autonomy, consent, and the consequences of merging human cognition with external devices. Exploring these ethical considerations highlights the complex interplay between advancing technology and preserving fundamental human rights and values. The concerns can be broadly categorized into user-centric issues and legal and social issues.
Concerns center on the safety and long-term effects on users. These include obtaining informed consent from individuals with communication difficulties, the impact on patients' and families' quality of life, health-related side effects, misuse of therapeutic applications, safety risks, and the non-reversible nature of some BCI-induced changes. Additionally, questions arise about access to maintenance, repair, and spare parts, particularly in the event of a company's bankruptcy[177]
The legal and social aspects of BCIs complicate mainstream adoption. Concerns include issues of accountability and responsibility, such as claims that BCI influence overrides free will and control over actions, inaccurate translation of cognitive intentions, personality changes resulting from deep-brain stimulation, and the blurring of the line between human and machine.[178] Other concerns involve the use of BCIs in advanced interrogation techniques, unauthorized access ("brain hacking"),[179] social stratification through selective enhancement, privacy issues related to mind-reading, tracking and "tagging" systems, and the potential for mind, movement, and emotion control.[180] Researchers have also theorized that BCIs could exacerbate existing social inequalities.
In their current form, most BCIs are more akin to corrective therapies that engage few of such ethical issues. Bioethics is well-equipped to address the challenges posed by BCI technologies, with Clausen suggesting in 2009 that "BCIs pose ethical challenges, but these are conceptually similar to those that bioethicists have addressed for other realms of therapy."[181] Haselager and colleagues highlighted the importance of managing expectations and value.[182] Standard protocols can ensure ethically sound informed-consent procedures for locked-in patients.
The evolution of BCIs mirrors that of pharmaceutical science, which began as a means to address impairments and now enhances focus and reduces the need for sleep. As BCIs progress from therapies to enhancements, the BCI community is working to create consensus on ethical guidelines for research, development, and dissemination.[183][184] Ensuring equitable access to BCIs will be crucial in preventing generational inequalities that could hinder the right to human flourishing.
Various companies are developing inexpensive BCIs for research and entertainment. Toys such as the NeuroSky and Mattel MindFlex have seen some commercial success.