The Occupational Safety and Health Administration (OSHA; /ˈoʊʃə/) is a regulatory agency of the United States Department of Labor that originally had federal visitorial powers to inspect and examine workplaces. The United States Congress established the agency under the Occupational Safety and Health Act (OSH Act), which President Richard M. Nixon
signed into law on December 29, 1970. OSHA's mission is to "assure safe
and healthy working conditions for working men and women by setting and
enforcing standards and by providing training, outreach, education, and
assistance." The agency is also charged with enforcing a variety of whistleblower
statutes and regulations. OSHA's workplace safety inspections have been
shown to reduce injury rates and injury costs without adverse effects
on employment, sales, credit ratings, or firm survival.
History
The Bureau of Labor Standards of the Department of Labor has worked on some work safety issues since its creation in 1934.
Economic boom and associated labor turnover during World War II
worsened work safety in nearly all areas of the United States economy,
but after 1945 accidents again declined as long-term forces reasserted
themselves. Additionally, new and powerful labor unions played an increasingly important role in worker safety post-World War II.
In the 1960s, increasing economic expansion again led to rising injury
rates, and the resulting political pressures led Congress to establish
the Occupational Safety and Health Administration (OSHA) on April 28,
1971, the date that the Occupational Health and Safety Act became
effective.
The new agency incorporated much of what had been the original Bureau
of Labor Standards. George Guenther was appointed by Labor Secretary James D. Hodgson as the agency's first director.
OSHA has run a number of training, compliance assistance, and
health and safety recognition programs throughout its history. The OSHA
Training Institute, which trains government and private sector health
and safety personnel, began in 1972.
In 1978, the agency began a grant-making program, now called the Susan
Harwood Training Grant Program, to train workers and employers in
reducing workplace hazards.
OSHA started the Voluntary Protection Programs in 1982, which allow
employers to apply as "model workplaces" to achieve special designation
if they meet certain requirements.
The OSH Act covers most private sector employers in all 50 states, the District of Columbia, and other U.S. jurisdictions—either directly through federal OSHA or through an OSHA-approved state plan.
State plans are OSHA-approved job safety and health programs
operated by individual states instead of federal OSHA. Federal OSHA
approves and monitors all state plans and provides as much as fifty
percent of the funding for each program. State-run safety and health
programs are required to be at least as effective as the federal OSHA
program.
Federal OSHA provides coverage to certain workplaces specifically
excluded from a state’s plan, such as work in maritime industries or on
military bases.
State and local governments
Workers
at state and local government agencies are not covered by federal OSHA
but have OSH Act protections if they work in those states that have an
OSHA-approved state program. OSH Act rules also permit states and
territories to develop plans that cover only public sector (state and
local government) workers. In these cases, private sector workers and
employers remain under federal OSHA jurisdiction. Five additional states
and one U.S. territory have OSHA-approved state plans that cover public
sector workers only: Connecticut, Illinois, Maine, New Jersey, New York, and the Virgin Islands.
Federal government agencies
OSHA’s
protection applies to all federal agencies. Section 19 of the OSH Act
makes federal agency heads responsible for providing safe and healthful
working conditions for their workers. OSHA conducts inspections of
federal facilities in response to workers' reports of hazards and under
programs that target high-hazard federal workplaces.
Federal agencies must have a safety and health program that meets
the same standards as private employers. OSHA issues “virtual fines” to
federal agencies – following an inspection where violations are found,
OSHA issues a press release stating the size of the fine would be if the
federal agency were a private sector employer. Under a 1998 amendment,
the OSH Act covers the U.S. Postal Service the same as any private sector employer.
Employers have the responsibility to provide a safe workplace.
By law, employers must provide their workers with a workplace
that does not have serious hazards, and they must follow all OSH Act
safety and health standards. Employers are obligated to identify and
rectify safety and health problems. The OSH Act further requires that
employers must first attempt to eliminate or reduce hazards by making
feasible changes in working conditions, rather than relying solely on
personal protective equipment such as masks, gloves, or earplugs.
Examples of effective ways to eliminate or reduce risks include
switching to safer chemicals, enclosing processes to trap harmful fumes,
or using ventilation systems to clean the air.
Employers must also:
Inform workers about chemical hazards through training, labels,
alarms, color-coded systems, chemical information sheets, and other
relevant methods..
Provide safety training to workers in a language and vocabulary they can understand.
Keep accurate records of work-related injuries and illnesses.
Perform tests in the workplace, such as air sampling, required by some OSH Act standards.
Provide the required personal protective equipment at no cost to workers, as employers must pay for most types of required personal protective equipment.
Provide hearing exams or other medical tests when required by OSH Act standards.
Post OSHA citations and annually post injury and illness summary data where workers can see them.
Notify OSHA within eight hours of a workplace fatality and within 24 hours of all work-related inpatient hospitalizations.
Prominently display the official OSHA Job Safety and Health – It’s the Law poster that describes rights and responsibilities under the OSH Act.
Not retaliate or discriminate against workers for using their rights under the law, including their right to report a work-related injury or illness.
Workers have the right to:
Working conditions that do not pose a risk of serious harm.
File a confidential complaint with OSHA to have their workplace inspected.
Receive information and training about hazards, methods to prevent
harm, and the OSH Act standards that apply to their workplace. The
training must be conducted in a language and vocabulary that workers can
understand.
Receive copies of records of work-related injuries and illnesses that occur in their workplace.
Receive copies of the results from tests and monitoring conducted to identify and measure hazards in their workplace.
Receive copies of their workplace medical records.
Participate in an OSHA inspection and speak in private with the inspector.
File a complaint with OSHA if they have faced retaliation or
discrimination from their employer as a result of requesting an
inspection or exercising any of their other rights under the OSH Act.
File a complaint if punished or retaliated against for acting as a
'whistleblower' under the 21 additional federal laws for which OSHA has
jurisdiction.
Temporary workers must be treated like permanent employees.
Staffing agencies and host employers share joint accountability for
temporary workers. Both entities are therefore obligated to comply with
workplace health and safety requirements and ensure worker safety and
health. OSHA could hold both the host and temporary employers
responsible for any violations.
Health and safety standards
The Occupational Safety and Health Act grants OSHA the authority to issue workplace health and safety regulations.
These regulations include limits on hazardous chemical exposure,
employee access to hazard information, requirements for the use of
personal protective equipment, and requirements to prevent falls and
hazards from operating dangerous equipment.
The OSH Act's current Construction, General Industry, Maritime, and Agriculture standards
are designed to protect workers from a wide range of serious hazards.
Examples of OSHA standards include requirements for employers to provide
fall protection such as a safety harness/line or guardrails; prevent
trenching cave-ins;
prevent exposure to some infectious diseases; ensure the safety of
workers who enter confined spaces; prevent exposure to harmful
chemicals; put guards on dangerous machines; provide respirators or
other safety equipment, and provide training for certain dangerous jobs
in a language and vocabulary workers can understand.
OSHA sets enforceable permissible exposure limits
(PELs) to protect workers against the health effects of exposure to
hazardous substances, including limits on the airborne concentrations of
hazardous chemicals in the air.
Most of OSHA’s PELs were issued shortly after the adoption of the OSH
Act in 1970. Attempts to issue more stringent PELs have been blocked by
litigation from the industry; thus, the vast majority of PELs have not
been updated since 1971. The agency has issued non-binding, alternate occupational exposure limits that may better protect workers.
Employers must also comply with the General Duty Clause of the
OSH Act. This clause requires employers to keep their workplaces free of
serious recognized hazards and is generally cited when no specific OSHA
standard applies to the hazard.
In its first year of operation, OSHA was permitted to adopt
regulations based on guidelines set by certain standards organizations,
such as the American Conference of Governmental Industrial Hygienists,
without going through all of the requirements of a typical rule-making.
OSHA is granted the authority to promulgate standards that prescribe the
methods employers are legally required to follow to protect their
workers from hazards. Before OSHA can issue a standard, it must go
through a very extensive and lengthy process that includes substantial
public engagement, notice, and comment. The agency must show that a
significant risk to workers exists and that there are feasible measures
employers can take to protect their workers.
In 2000, OSHA issued an ergonomics standard. In March 2001, Congress voted to repeal the standard through the Congressional Review Act. The repeal, one of the first major pieces of legislation signed by President George W. Bush, is the first instance that Congress has successfully used the Congressional Review Act to block regulation.
Since 2001, OSHA has issued the following standards:
2002: Exit Routes, Emergency Action Plans, and Fire Prevention Plans
2004: Commercial Diving Operations
2004: Fire Protection in Shipyards
2006: Occupational Exposure to Hexavalent Chromium
2006: Assigned Protection Factors for Respiratory Protection Equipment
2007: Personal Protective Equipment Payment (Clarification)
2008: Vertical Tandem Lifts
2010: Cranes and Derricks in Construction
2010: General Working Conditions in Shipyards
2012: GHS Update to the Hazard Communication Standard
2014: New Recordkeeping and Reporting Requirements for Employers
2014: Revision to Electric Power Generation, Transmission, and Distribution; Electrical Protective Equipment
2016: Occupational Exposure to Respirable Crystalline Silica
2016: Update General Industry Walking-Working Surfaces and Fall Protection Standards
Enforcement
OSHA
is responsible for enforcing its standards on regulated entities.
Compliance Safety and Health Officers carry out inspections and assess
fines for regulatory violations. Inspections are planned for worksites
in particularly hazardous industries. Inspections can also be triggered
by a workplace fatality, multiple hospitalizations, worker complaints,
or referrals.
OSHA is a small agency, given the size of its mission: with its
state partners, OSHA has approximately 2,400 inspectors covering more
than 8 million workplaces where 130 million workers are employed. In
Fiscal Year 2012 (ending Sept. 30), OSHA and its state partners
conducted more than 83,000 inspections of workplaces across the United
States — just a fraction of the nation’s worksites. According to a report by AFL–CIO, it would take OSHA 129 years to inspect all workplaces under its jurisdiction.
Enforcement plays an important part in OSHA's efforts to reduce
workplace injuries, illnesses, and fatalities. Inspections are initiated
without advance notice, conducted using on-site or telephone and
facsimile investigations, performed by trained compliance officers and
scheduled based on the following priorities [highest to lowest]:
imminent danger; catastrophes – fatalities or hospitalizations; worker
complaints and referrals; targeted inspections – particular hazards,
high injury rates; and follow-up inspections.
Current workers or their representatives may file a complaint and
ask OSHA to inspect their workplace if they believe that there is a
serious hazard or that their employer is not following OSHA standards.
Workers and their representatives have the right to ask for an
inspection without OSHA telling their employer who filed the complaint.
It is a violation of the OSH Act for an employer to fire, demote,
transfer or in any way discriminate against a worker for filing a
complaint or using other OSHA rights.
When an inspector finds violations of OSHA standards or serious
hazards, OSHA may issue citations and fines. A citation includes methods
an employer may use to fix a problem and the date by which the
corrective actions must be completed.
OSHA’s fines are very low compared with other government
agencies. They were raised for the first time since 1990 on August 2,
2016, to comply with the 2015 Federal Civil Penalties Inflation
Adjustment Act Improvements Act passed by Congress to advance the
effectiveness of civil monetary penalties and to maintain their
deterrent effect. The new law directs agencies to adjust their penalties
for inflation each year. The maximum OSHA fine for a serious violation
is $13,653 (which can be assessed daily after a failure to "abate" the
violation) and the maximum fine for a repeat or willful violation is
$136,532.
In determining the amount of the proposed penalty, OSHA must take into
account the gravity of the alleged violation and the employer’s size of
business, good faith, and history of previous violations. Employers have the right to contest any part of the citation, including whether a violation actually exists.
Workers only have the right to challenge the deadline by which a
problem must be resolved. Appeals of citations are heard by the
independent Occupational Safety and Health Review Commission (OSHRC).
In 2020, the COVID-19 pandemic caused about 1,300 workers and their families to contract the virus, with four deaths, at the Smithfield Foods packing plant in Sioux Falls, South Dakota. The governor, Kristi Noem, resisted initiating and enforcing measures to protect workers and the community. The plant was fined $13,494 – the maximum allowed at the time – by OSHA for what was considered a single violation.
Tracking
and investigating workplace injuries and illnesses play an important
role in preventing future injuries and illnesses. Under OSHA’s
Recordkeeping regulation, certain covered employers in high-hazard
industries are required to prepare and maintain records of serious
occupational injuries and illnesses. This information is important for
employers, workers, and OSHA in evaluating the safety of a workplace,
understanding industry hazards, and implementing worker protections to
reduce and eliminate hazards.
Employers with more than ten employees and whose establishments
are not classified as a partially exempt industry must record serious
work-related injuries and illnesses using OSHA Forms 300, 300A and 301.
Recordkeeping forms, requirements, and exemption information are on
OSHA’s website.
Whistleblower Protection Program
OSHA’s
Whistleblower Protection Program (WPP) enforces the whistleblower
provisions of the Occupational Safety and Health Act and 24 other
statutes protecting workers who report violations of various airline,
commercial motor carrier, consumer product, environmental, financial
reform, food safety, health care reform, nuclear, pipeline, public
transportation agency, maritime and securities laws.
Unlike OSHA’s Safety Enforcement complaints (or referrals) being
completely anonymous, OSHA’s whistleblower investigations can not be
anonymous as a Respondent is required to address all allegations of
adverse actions taken against Complainant’s employment. Additionally,
these whistleblower investigations follow the McDonnell-Douglas burden
shifting framework. WPP’s Investigators conduct complex investigations
pertaining to complaints of retaliation by an employer (Respondent)
against an employee (Complainant) who reported a violation(s) covered
under one of the 25 statutes.
WPP Investigators act as neutral fact-finders; they do not work for either the Complainant or Respondent.
A WPP Investigator’s job is to impartially gather and analyze all
relevant evidence to determine whether unlawful whistleblower
retaliation has occurred.
Over the years, OSHA’s WPP has been responsible for enforcing these
laws that protect the rights of workers to speak up without fear of
retaliation, regardless of the relationship of these laws to
occupational safety and health matters.
Compliance assistance
Voluntary Protection Program (VPP) Star Demonstration banner
OSHA has developed several training, compliance assistance, and health and safety recognition programs throughout its history.
The OSHA Training Institute, which trains government and private sector health and safety personnel, began in 1972.
In 1978, the agency began a grant-making program, now called the Susan
Harwood Training Grant Program, to train workers and employers in
identifying and reducing workplace hazards.
The Voluntary Protection Program (VPP) recognizes employers and
workers in private industry and federal agencies who have implemented
effective safety and health management programs and maintain injury and
illness rates below the national average for their respective
industries. In VPP, management, labor, and OSHA work cooperatively and
proactively to prevent fatalities, injuries, and illnesses through a
system focused on: hazard prevention and control, worksite analysis,
training, and management commitment and worker involvement.
OSHA’s On-site Consultation Program
offers free and confidential advice to small and medium-sized
businesses in all states across the country, with priority given to
high-hazard worksites. Each year, responding to requests from small
employers looking to create or improve their safety and health
management programs, OSHA’s On-site Consultation Program conducts over
29,000 visits to small business worksites covering over 1.5 million
workers across the nation. On-site consultation services are separate
from enforcement and do not result in penalties or citations.
Consultants from state agencies or universities work with employers to
identify workplace hazards, provide advice on compliance with OSHA
standards, and assist in establishing safety and health management
programs.
Under the consultation program, certain exemplary employers may request participation in OSHA’s Safety and Health Achievement Recognition Program (SHARP).
Eligibility for participation includes, but is not limited to,
receiving a full-service, comprehensive consultation visit, correcting
all identified hazards, and developing an effective safety and health
management program. Worksites that receive SHARP recognition are exempt
from programmed inspections during the period that the SHARP
certification is valid.
OSHA also provides compliance assistance through its national and
area offices. Through hundreds of publications in a variety of
languages, website safety, and health topics pages, and through
compliance assistance staff, OSHA provides information to employers and
workers on specific hazards and OSHA rights and responsibilities.
Efficacy
A 2012 study in Science
found that OSHA's random workplace safety inspections caused a "9.4%
decline in injury rates" and a "26% reduction in injury cost" for the
inspected firms.
The study found "no evidence that these improvements came at the
expense of employment, sales, credit ratings, or firm survival." A 2020 study in the American Economic Review
found that the decision by the Obama administration to issue press
releases that named and shamed facilities that violated OSHA safety and
health regulations led other facilities to increase their compliance and
to experience fewer workplace injuries. The study estimated that each
press release had the same effect on compliance as 210 inspections.
Much of the debate about OSHA regulations and enforcement
policies revolve around the cost of regulations and enforcement, versus
the actual benefit in reduced worker injury, illness, and death. A 1995
study of several OSHA standards by the Office of Technology Assessment
(OTA) found that OSHA relies "generally on methods that provide a
credible basis for the determinations essential to rulemaking." Though
it found that OSHA's findings and estimates are "subject to vigorous
review and challenge", it stated that this is natural because
"interested parties and experts involved in rulemakings have differing
visions."
OSHA has come under considerable criticism for the
ineffectiveness of its penalties, particularly its criminal penalties.
The maximum penalty is a misdemeanor with a maximum of 6 months in jail.
In response to the criticism, OSHA, in conjunction with the Department
of Justice, has pursued several high-profile criminal prosecutions for
violations under the Act and has announced a joint enforcement
initiative between OSHA and the United States Environmental Protection Agency (EPA) which has the ability to issue much higher fines than OSHA. Meanwhile, Congressional Democrats, labor unions, and community safety and health advocates are attempting to revise the OSH Act
to make it a felony with much higher penalties to commit a willful
violation that results in the death of a worker. Some local prosecutors
are charging company executives with manslaughter and other felonies when criminal negligence leads to the death of a worker.
A New York Times investigation in 2003 showed that over
the 20-year period from 1982 to 2002, 2,197 workers died in 1,242
incidents in which OSHA investigators concluded that employers had
willfully violated workplace safety laws. In 93% of these fatality cases
arising from wilful violation, OSHA made no referral to the U.S. Department of Justice for criminal prosecution. The Times
investigation found that OSHA had failed to pursue prosecution "even
when employers had been cited before for the very same safety violation"
and even in cases where multiple workers died. In interviews, current
and former OSHA officials said that the low rates of criminal
enforcement were the result of "a bureaucracy that works at every level
to thwart criminal referrals. ... that fails to reward, and sometimes
penalizes, those who push too hard for prosecution" and that "
aggressive enforcement [was] suffocated by endless layers of review.
OSHA has also been criticized for taking too long to develop new regulations. For instance, speaking about OSHA under the George W. Bush presidency on the specific issue of combustible dust explosions, Chemical Safety Board
appointee Carolyn Merritt said: "The basic disappointment has been this
attitude of no new regulation. They don't want the industry to be
pestered. In some instances, the industry has to be pestered in order to
comply."
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. 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.
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. 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. Following years of animal experimentation, the first neuroprosthetic devices were implanted in humans in the mid-1990s.
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 by means of 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
producoing alpha waves and thereby "playing" the various instruments via loudspeakers that are placed near or directly on the instruments.
Vidal coined the term "BCI" and produced the first peer-reviewed publications on this topic. He is widely recognized as the inventor of BCIs. A review pointed out that Vidal's 1973 paper stated the "BCI challenge" 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.
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.
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.
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 the 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. 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, Paradromics, Brown, and Synchron.
Neuroprosthetics is an area of neuroscience
concerned with neural prostheses, that is, using artificial devices to
replace the function of impaired nervous systems and brain-related
problems, or of sensory or other organs (bladder, diaphragm, etc.). As
of December 2010, cochlear implants had been implanted as neuroprosthetic devices in some 736,900 people worldwide. Other neuroprosthetic devices aim to restore vision, including retinal implants. The first neuroprosthetic device, however, was the pacemaker.
The terms are sometimes used interchangeably. Neuroprosthetics
and BCIs seek to achieve the same aims, such as restoring sight,
hearing, movement, ability to communicate, and even cognitive function. Both use similar experimental methods and surgical techniques.
Several laboratories have managed to read signals from monkey and rat cerebral cortices to operate BCIs to produce movement. Monkeys have moved computer cursors
and commanded robotic arms to perform simple tasks simply by thinking
about the task and seeing the results, without motor output. In May 2008 photographs that showed a monkey at the University of Pittsburgh Medical Center operating a robotic arm by thinking were published in multiple studies. Sheep have also been used to evaluate BCI technology including Synchron's Stentrode.
In 2020, Elon Musk's Neuralink was successfully implanted in a pig. In 2021, Musk announced that the company had successfully enabled a monkey to play video games using Neuralink's device.
Early work
Monkey operating a robotic arm with brain–computer interfacing (Schwartz lab, University of Pittsburgh)
In 1969 operant conditioning studies by Fetz et.al. at the Regional Primate Research Center and Department of Physiology and Biophysics, University of Washington School of Medicine showed that monkeys could learn to control the deflection of a biofeedback arm with neural activity.
Similar work in the 1970s established that monkeys could learn to
control the firing rates of individual and multiple neurons in the
primary motor cortex if they were rewarded accordingly.
Algorithms to reconstruct movements from motor cortexneurons, which control movement, date back to the 1970s. In the 1980s, Georgopoulos at Johns Hopkins University found a mathematical relationship between the electrical responses of single motor cortex neurons in rhesus macaque monkeys
and the direction in which they moved their arms. He also found that
dispersed groups of neurons, in different areas of the monkey's brains,
collectively controlled motor commands. He was able to record the
firings of neurons in only one area at a time, due to equipment
limitations.
Several groups have been able to capture complex brain motor cortex signals by recording from neural ensembles (groups of neurons) and using these to control external devices.
Prominent research successes
Kennedy and Yang Dan
Phillip
Kennedy (who later founded Neural Signals in 1987) and colleagues built
the first intracortical brain–computer interface by implanting
neurotrophic-cone electrodes into monkeys.
Yang Dan and colleagues' recordings of cat vision using a BCI implanted in the lateral geniculate nucleus (top row: original image; bottom row: recording)
In 1999, researchers led by Yang Dan at the University of California, Berkeley decoded neuronal firings to reproduce images seen by cats. The team used an array of electrodes embedded in the thalamus (which integrates all of the brain's sensory input) of sharp-eyed cats. Researchers targeted 177 brain cells in the thalamus lateral geniculate nucleus area, which decodes signals from the retina.
The cats were shown eight short movies, and their neuron firings were
recorded. Using mathematical filters, the researchers decoded the
signals to generate movies of what the cats saw and were able to
reconstruct recognizable scenes and moving objects. Similar results in humans have since been achieved by researchers in Japan (see below).
Miguel Nicolelis, a professor at Duke University, in Durham, North Carolina,
has been a prominent proponent of using multiple electrodes spread over
a greater area of the brain to obtain neuronal signals to drive a BCI.
After conducting initial studies in rats during the 1990s,
Nicolelis and his colleagues developed BCIs that decoded brain activity
in owl monkeys
and used the devices to reproduce monkey movements in robotic arms.
Monkeys have advanced reaching and grasping abilities and good hand
manipulation skills, making them ideal test subjects for this kind of
work.
By 2000, the group succeeded in building a BCI that reproduced owl monkey movements while the monkey operated a joystick or reached for food. The BCI operated in real time and could also control a separate robot remotely over Internet Protocol. But the monkeys could not see the arm moving and did not receive any feedback, a so-called open-loop BCI.
Diagram of the BCI developed by Miguel Nicolelis and colleagues for use on rhesus monkeys
Later experiments by Nicolelis using rhesus monkeys succeeded in closing the feedback loop
and reproduced monkey reaching and grasping movements in a robot arm.
With their deeply cleft and furrowed brains, rhesus monkeys are
considered to be better models for human neurophysiology
than owl monkeys. The monkeys were trained to reach and grasp objects
on a computer screen by manipulating a joystick while corresponding
movements by a robot arm were hidden.
The monkeys were later shown the robot directly and learned to control
it by viewing its movements. The BCI used velocity predictions to
control reaching movements and simultaneously predicted handgripping force.
In 2011 O'Doherty and colleagues showed a BCI with sensory feedback
with rhesus monkeys. The monkey was brain controlling the position of an
avatar arm while receiving sensory feedback through direct intracortical stimulation (ICMS) in the arm representation area of the sensory cortex.
Other laboratories which have developed BCIs and algorithms that decode neuron signals include the Carney Institute for Brain Science at Brown University and the labs of Andrew Schwartz at the University of Pittsburgh and Richard Andersen at Caltech.
These researchers have been able to produce working BCIs, even using
recorded signals from far fewer neurons than did Nicolelis (15–30
neurons versus 50–200 neurons).
John Donoghue's
lab at the Carney Institute reported training rhesus monkeys to use a
BCI to track visual targets on a computer screen (closed-loop BCI) with
or without assistance of a joystick.
Schwartz's group created a BCI for three-dimensional tracking in
virtual reality and also reproduced BCI control in a robotic arm.
The same group also created headlines when they demonstrated that a
monkey could feed itself pieces of fruit and marshmallows using a
robotic arm controlled by the animal's own brain signals.
Andersen's group used recordings of premovement activity from the posterior parietal cortex in their BCI, including signals created when experimental animals anticipated receiving a reward.
Other research
In addition to predicting kinematic and kinetic parameters of limb movements, BCIs that predict electromyographic or electrical activity of the muscles of primates are being developed. Such BCIs could be used to restore mobility in paralyzed limbs by electrically stimulating muscles.
Miguel Nicolelis and colleagues demonstrated that the activity of
large neural ensembles can predict arm position. This work made
possible creation of BCIs that read arm movement intentions and
translate them into movements of artificial actuators. Carmena and
colleaguesrammed the neural coding in a BCI that allowed a monkey to control reaching and grasping movements by a robotic arm. Lebedev and colleagues
argued that brain networks reorganize to create a new representation of
the robotic appendage in addition to the representation of the animal's
own limbs.
In 2019, researchers from UCSF
published a study where they demonstrated a BCI that had the potential
to help patients with speech impairment caused by neurological
disorders. Their BCI used high-density electrocorticography to tap
neural activity from a patient's brain and used deep learning methods to synthesize speech.
In 2021, researchers from the same group published a study showing the
potential of a BCI to decode words and sentences in an anarthric patient
who had been unable to speak for over 15 years.
The biggest impediment to BCI technology at present is the lack
of a sensor modality that provides safe, accurate and robust access to
brain signals. It is conceivable or even likely, however, that such a
sensor will be developed within the next twenty years. The use of such a
sensor should greatly expand the range of communication functions that
can be provided using a BCI.
Development and implementation of a BCI system is complex and
time-consuming. In response to this problem, Gerwin Schalk has been
developing a general-purpose system for BCI research, called BCI2000. BCI2000 has been in development since 2000 in a project led by the Brain–Computer Interface R&D Program at the Wadsworth Center of the New York State Department of Health in Albany, New York, United States.
The use of BMIs has also led to a deeper understanding of neural
networks and the central nervous system. Research has shown that despite
the inclination of neuroscientists to believe that neurons have the
most effect when working together, single neurons can be conditioned
through the use of BMIs to fire at a pattern that allows primates to
control motor outputs. The use of BMIs has led to development of the
single neuron insufficiency principle which states that even with a well
tuned firing rate single neurons can only carry a narrow amount of
information and therefore the highest level of accuracy is achieved by
recording firings of the collective ensemble. Other principles
discovered with the use of BMIs include the neuronal multitasking
principle, the neuronal mass principle, the neural degeneracy principle,
and the plasticity principle.
BCIs are also proposed to be applied by users without disabilities. A user-centered categorization of BCI approaches by Thorsten O. Zander and Christian Kothe introduces the term passive BCI.
Next to active and reactive BCI that are used for directed control,
passive BCIs allow for assessing and interpreting changes in the user
state during Human-Computer Interaction (HCI). In a secondary, implicit control loop the computer system adapts to its user improving its usability in general.
Beyond BCI systems that decode neural activity to drive external
effectors, BCI systems may be used to encode signals from the periphery.
These sensory BCI devices enable real-time, behaviorally-relevant
decisions based upon closed-loop neural stimulation.
The BCI Award
The Annual BCI Research Award
is awarded in recognition of outstanding and innovative research in the
field of Brain-Computer Interfaces. Each year, a renowned research
laboratory is asked to judge the submitted projects. The jury consists
of world-leading BCI experts recruited by the awarding laboratory. The
jury selects twelve nominees, then chooses a first, second, and
third-place winner, who receive awards of $3,000, $2,000, and $1,000,
respectively.
Human BCI research
Invasive BCIs
Invasive
BCI requires surgery to implant electrodes under the scalp for
communicating brain signals. The main advantage is to provide more
accurate reading; however, its downside includes side effects from the
surgery including scar tissue, which can make brain signals weaker. In
addition, according to the research of Abdulkader et al., (2015), the body may not accept the implanted electrodes and this can cause a medical condition.
Vision
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 of BCI devices but
are prone to scar-tissue build-up, causing the signal to become weaker, or even non-existent, as the body reacts to a foreign object in the brain.
In vision science, direct brain implants have been used to treat non-congenital (acquired) blindness. One of the first scientists to produce a working brain interface to restore sight was private researcher William Dobelle.
Dobelle's first prototype was implanted into "Jerry", a man
blinded in adulthood, in 1978. A single-array BCI containing 68
electrodes was implanted onto Jerry's visual cortex and succeeded in producing phosphenes,
the sensation of seeing light. The system included cameras mounted on
glasses to send signals to the implant. Initially, the implant allowed
Jerry to see shades of grey in a limited field of vision at a low
frame-rate. This also required him to be hooked up to a mainframe computer,
but shrinking electronics and faster computers made his artificial eye
more portable and now enable him to perform simple tasks unassisted.
Dummy unit illustrating the design of a BrainGate interface
In 2002, Jens Naumann, also blinded in adulthood, became the first in
a series of 16 paying patients to receive Dobelle's second generation
implant, marking one of the earliest commercial uses of BCIs. The second
generation device used a more sophisticated implant enabling better
mapping of phosphenes into coherent vision. Phosphenes are spread out
across the visual field in what researchers call "the starry-night
effect". Immediately after his implant, Jens was able to use his
imperfectly restored vision to drive an automobile slowly around the parking area of the research institute. Unfortunately, Dobelle died in 2004
before his processes and developments were documented. Subsequently,
when Mr. Naumann and the other patients in the program began having
problems with their vision, there was no relief and they eventually lost
their "sight" again. Naumann wrote about his experience with Dobelle's
work in Search for Paradise: A Patient's Account of the Artificial Vision Experiment and has returned to his farm in Southeast Ontario, Canada, to resume his normal activities.
Movement
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.
Researchers at Emory University in Atlanta,
led by Philip Kennedy and Roy Bakay, were first to install a brain
implant in a human that produced signals of high enough quality to
simulate movement. Their patient, Johnny Ray (1944–2002), developed 'locked-in syndrome' after having a brain-stem stroke
in 1997. Ray's implant was installed in 1998 and he lived long enough
to start working with the implant, eventually learning to control a
computer cursor; he died in 2002 of a brain aneurysm.
TetraplegicMatt Nagle became the first person to control an artificial hand using a BCI in 2005 as part of the first nine-month human trial of Cyberkinetics's BrainGate chip-implant. Implanted in Nagle's right precentral gyrus
(area of the motor cortex for arm movement), the 96-electrode BrainGate
implant allowed Nagle to control a robotic arm by thinking about moving
his hand as well as a computer cursor, lights and TV. One year later, professor Jonathan Wolpaw received the prize of the Altran Foundation for Innovation to develop a Brain Computer Interface with electrodes located on the surface of the skull, instead of directly in the brain.
More recently, research teams led by the BrainGate group at Brown University and a group led by University of Pittsburgh Medical Center, both in collaborations with the United States Department of Veterans Affairs,
have demonstrated further success in direct control of robotic
prosthetic limbs with many degrees of freedom using direct connections
to arrays of neurons in the motor cortex of patients with tetraplegia.
Communication
In
May 2021, a Stanford University team reported a successful
proof-of-concept test that enabled a quadraplegic participant to input
English sentences at about 86 characters per minute and 18 words per
minute. The participant imagined moving his hand to write letters, and
the system performed handwriting recognition on electrical signals
detected in the motor cortex, utilizing hidden Markov models and
recurrent neural networks for decoding. A report published in July 2021 reported a paralyzed patient was
able to communicate 15 words per minute using a brain implant that
analyzed motor neurons that previously controlled the vocal tract.
In a recent review article, researchers raised an open question
of whether human information transfer rates can surpass that of language
with BCIs. Given that recent language research has demonstrated that
human information transfer rates are relatively constant across many
languages, there may exist a limit at the level of information
processing in the brain. On the contrary, this "upper limit" of
information transfer rate may be intrinsic to language itself, as a
modality for information transfer.
In 2023 two studies used BCIs with recurrent neural network to
decode speech at a record rate of 62 words per minute and 78 words per
minute.
Technical challenges
There exist a number of technical challenges to recording brain activity with invasive BCIs. Advances in CMOS
technology are pushing and enabling integrated, invasive BCI designs
with smaller size, lower power requirements, and higher signal
acquisition capabilities. Invasive BCIs involve electrodes that penetrate brain tissue in an attempt to record action potential
signals (also known as spikes) from individual, or small groups of,
neurons near the electrode. The interface between a recording electrode
and the electrolytic solution surrounding neurons has been modelled
using the Hodgkin-Huxley model.
Electronic limitations to invasive BCIs have been an active area of research in recent decades. While intracellular recordings
of neurons reveal action potential voltages on the scale of hundreds of
millivolts, chronic invasive BCIs rely on recording extracellular
voltages which typically are three orders of magnitude smaller, existing
at hundreds of microvolts.
Further adding to the challenge of detecting signals on the scale of
microvolts is the fact that the electrode-tissue interface has a high capacitance
at small voltages. Due to the nature of these small signals, for BCI
systems that incorporate functionality onto an integrated circuit, each
electrode requires its own amplifier and ADC, which convert analog extracellular voltages into digital signals.
Because a typical neuron action potential lasts for one millisecond,
BCIs measuring spikes must have sampling rates ranging from 300 Hz to
5 kHz. Yet another concern is that invasive BCIs must be low-power, so
as to dissipate less heat to surrounding tissue; at the most basic level
more power is traditionally needed to optimize signal-to-noise ratio. Optimal battery design is an active area of research in BCIs.
Illustration
of invasive and partially invasive BCIs: electrocorticography (ECoG),
endovascular, and intracortical microelectrode.
Challenges existing in the area of material science
are central to the design of invasive BCIs. Variations in signal
quality over time have been commonly observed with implantable
microelectrodes.Optimal material and mechanical characteristics for long term signal
stability in invasive BCIs has been an active area of research. It has been proposed that the formation of glial scarring,
secondary to damage at the electrode-tissue interface, is likely
responsible for electrode failure and reduced recording performance. Research has suggested that blood-brain barrier
leakage, either at the time of insertion or over time, may be
responsible for the inflammatory and glial reaction to chronic
microelectrodes implanted in the brain. As a result, flexible and tissue-like designs have been researched and developed to minimize foreign-body reaction by means of matching the Young's modulus of the electrode closer to that of brain tissue.
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. There has been
preclinical demonstration of intracortical BCIs from the stroke
perilesional cortex.
Endovascular
A
systematic review published in 2020 detailed multiple studies, both
clinical and non-clinical, dating back decades investigating the
feasibility of endovascular BCIs.
In recent years, the biggest advance in partially invasive BCIs has emerged in the area of interventional neurology.
In 2010, researchers affiliated with University of Melbourne had begun
developing a BCI that could be inserted via the vascular system. The
Australian neurologist Thomas Oxley (Mount Sinai Hospital)
conceived the idea for this BCI, called Stentrode, which has received
funding from DARPA. Preclinical studies evaluated the technology in
sheep.
The Stentrode, a monolithic stent electrode array, is designed to be delivered via an intravenous catheter under image-guidance to the superior sagittal sinus, in the region which lies adjacent to motor cortex. This proximity to motor cortex
underlies the Stentrode's ability to measure neural activity. The
procedure is most similar to how venous sinus stents are placed for the
treatment of idiopathic intracranial hypertension.
The Stentrode communicates neural activity to a battery-less telemetry
unit implanted in the chest, which communicates wirelessly with an
external telemetry unit capable of power and data transfer. While an
endovascular BCI benefits from avoiding craniotomy for insertion, risks
such as clotting and venous thrombosis are possible.
First-in-human trials with the Stentrode are underway. In November 2020, two participants with amyotrophic lateral sclerosis
were able to wirelessly control an operating system to text, email,
shop, and bank using direct thought through the Stentrode brain-computer
interface,
marking the first time a brain-computer interface was implanted via the
patient's blood vessels, eliminating the need for open brain surgery.
In January 2023, researchers reported no serious adverse events during
the first year for all four patients who could use it to operate
computers.
ECoG
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. ECoG technologies were first trialled in humans in 2004 by Eric Leuthardt and Daniel Moran from Washington University in St. Louis. In a later trial, the researchers enabled a teenage boy to play Space Invaders using his ECoG implant.
This research indicates that control is rapid, requires minimal
training, and may be an ideal tradeoff with regards to signal fidelity
and level of invasiveness.
Signals can be either subdural or epidural, but are not taken from within the brain parenchyma
itself. It has not been studied extensively until recently due to the
limited access of subjects. Currently, the only manner to acquire the
signal for study is through the use of patients requiring invasive
monitoring for localization and resection of an epileptogenic focus.
ECoG is a very promising intermediate BCI modality because it has
higher spatial resolution, better signal-to-noise ratio, wider
frequency range, and less training requirements than scalp-recorded EEG,
and at the same time has lower technical difficulty, lower clinical
risk, and may have superior long-term stability than intracortical
single-neuron recording.
This feature profile and recent evidence of the high level of control
with minimal training requirements shows potential for real world
application for people with motor disabilities. Light reactive imaging BCI devices are still in the realm of theory.
Recent work published by Edward Chang and Joseph Makin from UCSF
revealed that ECoG signals could be used to decode speech from epilepsy
patients implanted with high-density ECoG arrays over the peri-Sylvian
cortices. Their study achieved word error rates of 3% (a marked improvement from prior publications) utilizing an encoder-decoder neural network, which translated ECoG data into one of fifty sentences composed of 250 unique words.
Non-invasive BCIs
There have also been experiments in humans using non-invasiveneuroimaging
technologies as interfaces. The substantial majority of published BCI
work involves noninvasive EEG-based BCIs. Noninvasive EEG-based
technologies and interfaces have been used for a much broader variety of
applications. Although EEG-based interfaces are easy to wear and do not
require surgery, 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. EEG-based interfaces also require some time and
effort prior to each usage session, whereas non-EEG-based ones, as well
as invasive ones require no prior-usage training. Overall, the best BCI
for each user depends on numerous factors.
After the BCI challenge was stated by Vidal in 1973, the initial
reports on non-invasive approach included control of a cursor in 2D
using VEP (Vidal 1977), control of a buzzer using CNV (Bozinovska et al.
1988, 1990), control of a physical object, a robot, using a brain
rhythm (alpha) (Bozinovski et al. 1988), control of a text written on a
screen using P300 (Farwell and Donchin, 1988).
In the early days of BCI research, another substantial barrier to using electroencephalography
(EEG) as a brain–computer interface was the extensive training required
before users can work the technology. For example, in experiments
beginning in the mid-1990s, Niels Birbaumer at the University of Tübingen in Germany trained severely paralysed people to self-regulate the slow cortical potentials in their EEG to such an extent that these signals could be used as a binary signal to control a computer cursor. (Birbaumer had earlier trained epileptics
to prevent impending fits by controlling this low voltage wave.) The
experiment saw ten patients trained to move a computer cursor by
controlling their brainwaves. The process was slow, requiring more than
an hour for patients to write 100 characters with the cursor, while
training often took many months. However, the slow cortical potential
approach to BCIs has not been used in several years, since other
approaches require little or no training, are faster and more accurate,
and work for a greater proportion of users.
Another research parameter is the type of oscillatory activity
that is measured. Gert Pfurtscheller founded the BCI Lab 1991 and fed
his research results on motor imagery in the first online BCI based on
oscillatory features and classifiers. Together with Birbaumer and
Jonathan Wolpaw at New York State University
they focused on developing technology that would allow users to choose
the brain signals they found easiest to operate a BCI, including mu and beta rhythms.
A further parameter is the method of feedback used and this is shown in studies of P300 signals. Patterns of P300 waves are generated involuntarily (stimulus-feedback)
when people see something they recognize and may allow BCIs to decode
categories of thoughts without training patients first. By contrast, the
biofeedback methods described above require learning to control brainwaves so the resulting brain activity can be detected.
In 2005 it was reported research on EEG emulation of digital control circuits for BCI, with example of a CNV flip-flop. In 2009 it was reported noninvasive EEG control of a robotic arm using a CNV flip-flop. In 2011 it was reported control of two robotic arms solving Tower of Hanoi task with three disks using a CNV flip-flop. In 2015 it was described EEG-emulation of a Schmitt trigger, flip-flop, demultiplexer, and modem.
While an EEG based brain-computer interface has been pursued
extensively by a number of research labs, recent advancements made by Bin He and his team at the University of Minnesota
suggest the potential of an EEG based brain-computer interface to
accomplish tasks close to invasive brain-computer interface. Using
advanced functional neuroimaging including BOLD functional MRI and EEG
source imaging, Bin He and co-workers identified the co-variation and
co-localization of electrophysiological and hemodynamic signals induced
by motor imagination.
Refined by a neuroimaging approach and by a training protocol, Bin He
and co-workers demonstrated the ability of a non-invasive EEG based
brain-computer interface to control the flight of a virtual helicopter
in 3-dimensional space, based upon motor imagination.
In June 2013 it was announced that Bin He had developed the technique
to enable a remote-control helicopter to be guided through an obstacle
course.
In addition to a brain-computer interface based on brain waves,
as recorded from scalp EEG electrodes, Bin He and co-workers explored a
virtual EEG signal-based brain-computer interface by first solving the
EEG inverse problem
and then used the resulting virtual EEG for brain-computer interface
tasks. Well-controlled studies suggested the merits of such a source
analysis based brain-computer interface.
A 2014 study found that severely motor-impaired patients could
communicate faster and more reliably with non-invasive EEG BCI, than
with any muscle-based communication channel.
A 2016 study found that the Emotiv EPOC device may be more
suitable for control tasks using the attention/meditation level or eye
blinking than the Neurosky MindWave device.
A 2019 study found that the application of evolutionary
algorithms could improve EEG mental state classification with a
non-invasive Muse device, enabling high quality classification of data acquired by a cheap consumer-grade EEG sensing device.
In a 2021 systematic review of randomized controlled trials using
BCI for upper-limb rehabilitation after stroke, EEG-based BCI was found
to have significant efficacy in improving upper-limb motor function
compared to control therapies. More specifically, BCI studies that
utilized band power features, motor imagery, and functional electrical
stimulation in their design were found to be more efficacious than
alternatives.
Another 2021 systematic review focused on robotic-assisted EEG-based
BCI for hand rehabilitation after stroke. Improvement in motor
assessment scores was observed in three of eleven studies included in
the systematic review.
Dry active electrode arrays
In the early 1990s Babak Taheri, at University of California, Davis
demonstrated the first single and also multichannel dry active
electrode arrays using micro-machining. The single channel dry EEG
electrode construction and results were published in 1994. The arrayed electrode was also demonstrated to perform well compared to silver/silver chloride electrodes. The device consisted of four sites of sensors with integrated electronics to reduce noise by impedance matching.
The advantages of such electrodes are: (1) no electrolyte used, (2) no
skin preparation, (3) significantly reduced sensor size, and (4)
compatibility with EEG monitoring systems. The active electrode array is
an integrated system made of an array of capacitive sensors with local
integrated circuitry housed in a package with batteries to power the
circuitry. This level of integration was required to achieve the
functional performance obtained by the electrode.
The electrode was tested on an electrical test bench and on human
subjects in four modalities of EEG activity, namely: (1) spontaneous
EEG, (2) sensory event-related potentials, (3) brain stem potentials,
and (4) cognitive event-related potentials. The performance of the dry
electrode compared favorably with that of the standard wet electrodes in
terms of skin preparation, no gel requirements (dry), and higher
signal-to-noise ratio.
In 1999 researchers at Case Western Reserve University, in Cleveland, Ohio, led by Hunter Peckham, used 64-electrode EEG skullcap to return limited hand movements to quadriplegic
Jim Jatich. As Jatich concentrated on simple but opposite concepts like
up and down, his beta-rhythm EEG output was analysed using software to
identify patterns in the noise. A basic pattern was identified and used
to control a switch: Above average activity was set to on, below average
off. As well as enabling Jatich to control a computer cursor the
signals were also used to drive the nerve controllers embedded in his
hands, restoring some movement.
SSVEP mobile EEG BCIs
In
2009, the NCTU Brain-Computer-Interface-headband was reported. The
researchers who developed this BCI-headband also engineered
silicon-based microelectro-mechanical system (MEMS) dry electrodes designed for application in non-hairy sites of the body. These electrodes were secured to the DAQ board in the headband with snap-on electrode holders. The signal processing module measured alpha
activity and the Bluetooth enabled phone assessed the patients'
alertness and capacity for cognitive performance. When the subject
became drowsy, the phone sent arousing feedback to the operator to rouse
them. This research was supported by the National Science Council,
Taiwan, R.O.C., NSC, National Chiao-Tung University, Taiwan's Ministry
of Education, and the U.S. Army Research Laboratory.
In 2011, researchers reported a cellular based BCI with the
capability of taking EEG data and converting it into a command to cause
the phone to ring. This research was supported in part by Abraxis Bioscience
LLP, the U.S. Army Research Laboratory, and the Army Research Office.
The developed technology was a wearable system composed of a four
channel bio-signal acquisition/amplification module,
a wireless transmission module, and a Bluetooth enabled cell phone.
The electrodes were placed so that they pick up steady state visual
evoked potentials (SSVEPs). SSVEPs are electrical responses to flickering visual stimuli with repetition rates over 6 Hz that are best found in the parietal and occipital scalp regions of the visual cortex.
It was reported that with this BCI setup, all study participants were
able to initiate the phone call with minimal practice in natural
environments.
The scientists claim that their studies using a single channel fast Fourier transform (FFT) and multiple channel system canonical correlation analysis (CCA) algorithm support the capacity of mobile BCIs.
The CCA algorithm has been applied in other experiments investigating
BCIs with claimed high performance in accuracy as well as speed.
While the cellular based BCI technology was developed to initiate a
phone call from SSVEPs, the researchers said that it can be translated
for other applications, such as picking up sensorimotor mu/beta rhythms to function as a motor-imagery based BCI.
In 2013, comparative tests were performed on android cell phone, tablet, and computer based BCIs, analyzing the power spectrum density
of resultant EEG SSVEPs. The stated goals of this study, which involved
scientists supported in part by the U.S. Army Research Laboratory, were
to "increase the practicability, portability, and ubiquity of an
SSVEP-based BCI, for daily use". Citation It was reported that the
stimulation frequency on all mediums was accurate, although the cell
phone's signal demonstrated some instability. The amplitudes of the
SSVEPs for the laptop and tablet were also reported to be larger than
those of the cell phone. These two qualitative characterizations were
suggested as indicators of the feasibility of using a mobile stimulus
BCI.
Limitations
In
2011, researchers stated that continued work should address ease of
use, performance robustness, reducing hardware and software costs.
One of the difficulties with EEG readings is the large susceptibility to motion artifacts.
In most of the previously described research projects, the participants
were asked to sit still, reducing head and eye movements as much as
possible, and measurements were taken in a laboratory setting. However,
since the emphasized application of these initiatives had been in
creating a mobile device for daily use, the technology had to be tested in motion.
In 2013, researchers tested mobile EEG-based BCI technology,
measuring SSVEPs from participants as they walked on a treadmill at
varying speeds. This research was supported by the Office of Naval Research,
Army Research Office, and the U.S. Army Research Laboratory. Stated
results were that as speed increased the SSVEP detectability using CCA
decreased. As independent component analysis (ICA) had been shown to be efficient in separating EEG signals from noise,
the scientists applied ICA to CCA extracted EEG data. They stated that
the CCA data with and without ICA processing were similar. Thus, they
concluded that CCA independently demonstrated a robustness to motion
artifacts that indicates it may be a beneficial algorithm to apply to
BCIs used in real world conditions.
One of the major problems in EEG-based BCI applications is the low
spatial resolution. Several solutions have been suggested to address
this issue since 2019, which include: EEG source connectivity based on
graph theory, EEG pattern recognition based on Topomap, EEG-fMRI fusion,
and so on.
Prosthesis and environment control
Non-invasive
BCIs have also been applied to enable brain-control of prosthetic upper
and lower extremity devices in people with paralysis. For example, Gert
Pfurtscheller of Graz University of Technology and colleagues demonstrated a BCI-controlled functional electrical stimulation system to restore upper extremity movements in a person with tetraplegia due to spinal cord injury. Between 2012 and 2013, researchers at the University of California, Irvine
demonstrated for the first time that it is possible to use BCI
technology to restore brain-controlled walking after spinal cord injury.
In their spinal cord injury research study, a person with paraplegia was able to operate a BCI-robotic gait orthosis to regain basic brain-controlled ambulation.
In 2009 Alex Blainey, an independent researcher based in the UK, successfully used the Emotiv EPOC to control a 5 axis robot arm. He then went on to make several demonstration mind controlled wheelchairs and home automation that could be operated by people with limited or no motor control such as those with paraplegia and cerebral palsy.
Research into military use of BCIs funded by DARPA has been ongoing since the 1970s. The current focus of research is user-to-user communication through analysis of neural signals.
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.
In 2008 research developed in the Advanced Telecommunications Research (ATR) Computational Neuroscience Laboratories in Kyoto,
Japan, allowed the scientists to reconstruct images directly from the
brain and display them on a computer in black and white at a resolution of 10x10 pixels. The article announcing these achievements was the cover story of the journal Neuron of 10 December 2008.
In 2011 researchers from UC Berkeley published
a study reporting second-by-second reconstruction of videos watched by
the study's subjects, from fMRI data. This was achieved by creating a
statistical model relating visual patterns in videos shown to the
subjects, to the brain activity caused by watching the videos. This
model was then used to look up the 100 one-second video segments, in a
database of 18 million seconds of random YouTube
videos, whose visual patterns most closely matched the brain activity
recorded when subjects watched a new video. These 100 one-second video
extracts were then combined into a mashed-up image that resembled the
video being watched.
Motor imagery involves the imagination of the movement of various body parts resulting in sensorimotor cortex
activation, which modulates sensorimotor oscillations in the EEG. This
can be detected by the BCI to infer a user's intent. Motor imagery
typically requires a number of sessions of training before acceptable
control of the BCI is acquired. These training sessions may take a
number of hours over several days before users can consistently employ
the technique with acceptable levels of precision. Regardless of the
duration of the training session, users are unable to master the control
scheme. This results in very slow pace of the gameplay.
Advanced machine learning methods were recently developed to compute a
subject-specific model for detecting the performance of motor imagery.
The top performing algorithm from BCI Competition IV dataset 2 for motor imagery is the Filter Bank Common Spatial Pattern, developed by Ang et al. from A*STAR, Singapore.
Bio/neurofeedback for passive BCI designs
Biofeedback
is used to monitor a subject's mental relaxation. In some cases,
biofeedback does not monitor electroencephalography (EEG), but instead
bodily parameters such as electromyography (EMG), galvanic skin resistance (GSR), and heart rate variability (HRV). Many biofeedback systems are used to treat certain disorders such as attention deficit hyperactivity disorder (ADHD),
sleep problems in children, teeth grinding, and chronic pain. EEG
biofeedback systems typically monitor four different bands (theta:
4–7 Hz, alpha:8–12 Hz, SMR: 12–15 Hz, beta: 15–18 Hz) and challenge the
subject to control them. Passive BCI
involves using BCI to enrich human–machine interaction with implicit
information on the actual user's state, for example, simulations to
detect when users intend to push brakes during an emergency car stopping
procedure. Game developers using passive BCIs need to acknowledge that
through repetition of game levels the user's cognitive state will change
or adapt. Within the first play
of a level, the user will react to things differently from during the
second play: for example, the user will be less surprised at an event in
the game if they are expecting it.
Visual evoked potential (VEP)
A
VEP is an electrical potential recorded after a subject is presented
with a type of visual stimuli. There are several types of VEPs.
Steady-state visually evoked potentials (SSVEPs) use potentials generated by exciting the retina,
using visual stimuli modulated at certain frequencies. SSVEP's stimuli
are often formed from alternating checkerboard patterns and at times
simply use flashing images. The frequency of the phase reversal of the
stimulus used can be clearly distinguished in the spectrum of an EEG;
this makes detection of SSVEP stimuli relatively easy. SSVEP has proved
to be successful within many BCI systems. This is due to several
factors, the signal elicited is measurable in as large a population as
the transient VEP and blink movement and electrocardiographic artefacts
do not affect the frequencies monitored. In addition, the SSVEP signal
is exceptionally robust; the topographic organization of the primary
visual cortex is such that a broader area obtains afferents from the
central or fovial region of the visual field. SSVEP does have several
problems however. As SSVEPs use flashing stimuli to infer a user's
intent, the user must gaze at one of the flashing or iterating symbols
in order to interact with the system. It is, therefore, likely that the
symbols could become irritating and uncomfortable to use during longer
play sessions, which can often last more than an hour which may not be
an ideal gameplay.
Another type of VEP used with applications is the P300 potential.
The P300 event-related potential is a positive peak in the EEG that
occurs at roughly 300 ms after the appearance of a target stimulus (a
stimulus for which the user is waiting or seeking) or oddball stimuli.
The P300 amplitude decreases as the target stimuli and the ignored
stimuli grow more similar.The P300 is thought to be related to a higher
level attention process or an orienting response using P300 as a control
scheme has the advantage of the participant only having to attend
limited training sessions. The first application to use the P300 model
was the P300 matrix. Within this system, a subject would choose a letter
from a grid of 6 by 6 letters and numbers. The rows and columns of the
grid flashed sequentially and every time the selected "choice letter"
was illuminated the user's P300 was (potentially) elicited. However, the
communication process, at approximately 17 characters per minute, was
quite slow. The P300 is a BCI that offers a discrete selection rather
than a continuous control mechanism. The advantage of P300 use within
games is that the player does not have to teach himself/herself how to
use a completely new control system and so only has to undertake short
training instances, to learn the gameplay mechanics and basic use of the
BCI paradigm.
Human-computer
interaction can benefit from other recording modalities, such as EOG
and eye-tracking. However, these modalities do not record brain activity
and therefore do not fall within the exact scope of BCIs, but rather
can be grouped under the wider field of physiological computing.
Electro-oculography (EOG)
In 1989, a report was given on control of a mobile robot by eye movement using electrooculography
(EOG) signals. A mobile robot was driven from a start to a goal point
using five EOG commands, interpreted as forward, backward, left, right,
and stop.
Pupil-size oscillation
A 2016 article described an entirely new communication device and non-EEG-based human-computer interface, which requires no visual fixation, or ability to move the eyes at all. The interface is based on covert interest;
directing one's attention to a chosen letter on a virtual keyboard,
without the need to move one's eyes to look directly at the letter. Each
letter has its own (background) circle which micro-oscillates in
brightness differently from all of the other letters. The letter
selection is based on best fit between unintentional pupil-size
oscillation and the background circle's brightness oscillation pattern.
Accuracy is additionally improved by the user's mental rehearsing of the
words 'bright' and 'dark' in synchrony with the brightness transitions
of the letter's circle.
Synthetic telepathy
In a $6.3 million US Army initiative to invent devices for telepathic communication, Gerwin Schalk,
underwritten in a $2.2 million grant, found the use of ECoG signals can
discriminate the vowels and consonants embedded in spoken and imagined
words, shedding light on the distinct mechanisms associated with
production of vowels and consonants, and could provide the basis for
brain-based communication using imagined speech.
In 2002 Kevin Warwick
had an array of 100 electrodes fired into his nervous system in order
to link his nervous system into the Internet to investigate enhancement
possibilities. With this in place Warwick successfully carried out a
series of experiments. With electrodes also implanted into his wife's
nervous system, they conducted the first direct electronic communication
experiment between the nervous systems of two humans.
Another group of researchers was able to achieve conscious
brain-to-brain communication between two people separated by a distance
using non-invasive technology that was in contact with the scalp of the
participants. The words were encoded by binary streams using the
sequences of 0's and 1's by the imaginary motor input of the person
"emitting" the information. As the result of this experiment,
pseudo-random bits of the information carried encoded words "hola" ("hi"
in Spanish) and "ciao" ("goodbye" in Italian) and were transmitted
mind-to-mind between humans separated by a distance, with blocked motor
and sensory systems, which has low to no probability of this happening
by chance.
In the 1960s a researcher was successful after some training in
using EEG to create Morse code using their brain alpha waves. Research
funded by the US army is being conducted with the goal of allowing users
to compose a message in their head, then transfer that message with
just the power of thought to a particular individual. On 27 February 2013 the group with Miguel Nicolelis at Duke University
and IINN-ELS successfully connected the brains of two rats with
electronic interfaces that allowed them to directly share information,
in the first-ever direct brain-to-brain interface.
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.
The world's first neurochip, developed by Caltech researchers Jerome Pine and Michael Maher
Development of the first working neurochip was claimed by a Caltech team led by Jerome Pine and Michael Maher in 1997. The Caltech chip had room for 16 neurons.
In 2003 a team led by Theodore Berger, at the University of Southern California, started work on a neurochip designed to function as an artificial or prosthetic hippocampus.
The neurochip was designed to function in rat brains and was intended
as a prototype for the eventual development of higher-brain prosthesis.
The hippocampus was chosen because it is thought to be the most ordered
and structured part of the brain and is the most studied area. Its
function is to encode experiences for storage as long-term memories
elsewhere in the brain.
In 2004 Thomas DeMarse at the University of Florida used a culture of 25,000 neurons taken from a rat's brain to fly a F-22 fighter jet aircraft simulator. After collection, the cortical neurons were cultured in a petri dish
and rapidly began to reconnect themselves to form a living neural
network. The cells were arranged over a grid of 60 electrodes and used
to control the pitch and yaw
functions of the simulator. The study's focus was on understanding how
the human brain performs and learns computational tasks at a cellular
level.
Collaborative BCIs
The
idea of combining/integrating brain signals from multiple individuals
was introduced at Humanity+ @Caltech, in December 2010, by a Caltech researcher at JPL, Adrian Stoica, who referred to the concept as multi-brain aggregation. A provisional patent application was filed on January 19, 2011, with the non-provisional patent following one year later. In May 2011, Yijun Wang and Tzyy-Ping Jung published, "A Collaborative Brain-Computer Interface for Improving Human Performance", and in January 2012 Miguel Eckstein published, "Neural decoding of collective wisdom with multi-brain computing". Stoica's first paper on the topic appeared in 2012, after the publication of his patent application.
Given the timing of the publications between the patent and papers,
Stoica, Wang & Jung, and Eckstein independently pioneered the
concept, and are all considered as founders of the field. Later, Stoica
would collaborate with University of Essex researchers, Riccardo Poli and Caterina Cinel. The work was continued by Poli and Cinel, and their students: Ana Matran-Fernandez, Davide Valeriani, and Saugat Bhattacharyya.
Ethical considerations
As
technology continually blurs the line between science fiction and
reality, the advent of brain-computer interfaces (BCIs) poses a profound
ethical quandary. These neural interfaces, heralded as marvels of
innovation, facilitate direct communication between the human brain and
external devices. However, the ethical landscape surrounding BCIs is
intricate and multifaceted, encompassing concerns of privacy invasion,
autonomy, consent, and the potential societal implications of merging
human cognition with machine interfaces. Delving into the ethical
considerations of BCIs illuminates the intricate balance between
technological advancement and safeguarding fundamental human rights and
values. Many of the concerns raised can be divided into two groups, user
centric issues and legal and social issues.
Ethical concerns in the user centric sphere tend to revolve
around the safety of the user and the effects that this technology will
have on them over a period of time. These can include but are not
limited to: long-term effects to the user remain largely unknown,
obtaining informed consent from people who have difficulty
communicating, the consequences of BCI technology for the quality of
life of patients and their families, health-related side-effects (e.g.
neurofeedback of sensorimotor rhythm training is reported to affect
sleep quality), therapeutic applications and their potential misuse,
safety risks, non-convertibility of some of the changes made to the
brain, lack of access to maintenance, repair and spare parts in case of
company bankruptcy, etc.
The legal and social aspect of BCIs is a metaphorical minefield
for any entity attempting to make BCIs mainstream. Some of these
concerns would be issues of accountability and responsibility: claims
that the influence of BCIs overrides free will and control over
sensory-motor actions, claims that cognitive intention was inaccurately
translated due to a BCI malfunction, personality changes involved caused
by deep-brain stimulation, concerns regarding the state of becoming a
"cyborg" - having parts of the body that are living and parts that are
mechanical, questions about personality: what does it mean to be a
human, blurring of the division between human and machine and inability
to distinguish between human vs. machine-controlled actions,
use of the technology in advanced interrogation techniques by
governmental authorities, “brain hacking” or the unauthorized access of
someones BCI, selective enhancement and social stratification, mind reading and privacy, tracking and "tagging system", mind control, movement control, and emotion control. In addition many researchers have theorized that BCIs would only worsen social inequalities seen today.
In their current form, most BCIs are far removed from the ethical
issues considered above. They are actually similar to corrective
therapies in function. Clausen stated in 2009 that "BCIs pose ethical
challenges, but these are conceptually similar to those that
bioethicists have addressed for other realms of therapy".
Moreover, he suggests that bioethics is well-prepared to deal with the
issues that arise with BCI technologies. Haselager and colleagues
pointed out that expectations of BCI efficacy and value play a great
role in ethical analysis and the way BCI scientists should approach
media. Furthermore, standard protocols can be implemented to ensure
ethically sound informed-consent procedures with locked-in patients.
The case of BCIs today has parallels in medicine, as will its
evolution. Similar to how pharmaceutical science began as a balance for
impairments and is now used to increase focus and reduce need for sleep,
BCIs will likely transform gradually from therapies to enhancements.
Efforts are made inside the BCI community to create consensus on
ethical guidelines for BCI research, development and dissemination.
As innovation continues, ensuring equitable access to BCIs will be
crucial, failing which generational inequalities can arise which can
adversely affect the right to human flourishing.
Recently a number of companies have scaled back medical grade EEG
technology to create inexpensive BCIs for research as well as
entertainment purposes. For example, toys such as the NeuroSky and
Mattel MindFlex have seen some commercial success.
In 2006 Sony patented a neural interface system allowing radio waves to affect signals in the neural cortex.
In 2007 NeuroSky
released the first affordable consumer based EEG along with the game
NeuroBoy. This was also the first large scale EEG device to use dry
sensor technology.
In 2008 Final Fantasy developer Square Enix announced that it was partnering with NeuroSky to create a game, Judecca.
In 2009 Mattel partnered with NeuroSky to release the Mindflex, a game that used an EEG to steer a ball through an obstacle course. It is by far the best selling consumer based EEG to date.
In 2009 Emotiv
released the EPOC, a 14 channel EEG device that can read 4 mental
states, 13 conscious states, facial expressions, and head movements. The
EPOC is the first commercial BCI to use dry sensor technology, which
can be dampened with a saline solution for a better connection.
In November 2011 Time magazine selected "necomimi" produced by Neurowear
as one of the best inventions of the year. The company announced that
it expected to launch a consumer version of the garment, consisting of
catlike ears controlled by a brain-wave reader produced by NeuroSky, in spring 2012.
In February 2014 They Shall Walk (a nonprofit organization fixed on
constructing exoskeletons, dubbed LIFESUITs, for paraplegics and
quadriplegics) began a partnership with James W. Shakarji on the
development of a wireless BCI.
In 2016, a group of hobbyists developed an open-source BCI board
that sends neural signals to the audio jack of a smartphone, dropping
the cost of entry-level BCI to £20. Basic diagnostic software is available for Android devices, as well as a text entry app for Unity.
In 2020, NextMind released a dev kit including an EEG headset with dry electrodes at $399.
The device can be played with some demo applications or developers can
create their own use cases using the provided Software Development Kit.
Future directions
Brain-computer interface
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, started in November 2013 and published a roadmap in April 2015.
A 2015 publication led by Clemens Brunner describes some of the
analyses and achievements of this project, as well as the emerging
Brain-Computer Interface Society.
For example, this article reviewed work within this project that
further defined BCIs and applications, explored recent trends, discussed
ethical issues, and evaluated different directions for new BCIs.
Other recent publications too have explored future BCI directions for new groups of disabled users (e.g.,)
Disorders of consciousness (DOC)
Some people have a disorder of consciousness (DOC). This state is defined to include people in a coma and those in a vegetative state (VS) or minimally conscious state
(MCS). New BCI research seeks to help people with DOC in different
ways. A key initial goal is to identify patients who can perform basic
cognitive tasks, which would of course lead to a change in their
diagnosis. That is, some people who are diagnosed with DOC may in fact
be able to process information and make important life decisions (such
as whether to seek therapy, where to live, and their views on
end-of-life decisions regarding them). Some who are diagnosed with DOC
die as a result of end-of-life decisions, which may be made by family
members who sincerely feel this is in the patient's best interests.
Given the new prospect of allowing these patients to provide their views
on this decision, there would seem to be a strong ethical pressure to
develop this research direction to guarantee that DOC patients are given
an opportunity to decide whether they want to live.
These and other articles describe new challenges and solutions to
use BCI technology to help persons with DOC. One major challenge is
that these patients cannot use BCIs based on vision. Hence, new tools
rely on auditory and/or vibrotactile stimuli. Patients may wear
headphones and/or vibrotactile stimulators placed on the wrists, neck,
leg, and/or other locations. Another challenge is that patients may fade
in and out of consciousness and can only communicate at certain times.
This may indeed be a cause of mistaken diagnosis. Some patients may only
be able to respond to physicians' requests for a few hours per day
(which might not be predictable ahead of time) and thus may have been
unresponsive during diagnosis. Therefore, new methods rely on tools that
are easy to use in field settings, even without expert help, so family
members and other people without any medical or technical background can
still use them. This reduces the cost, time, need for expertise, and
other burdens with DOC assessment. Automated tools can ask simple
questions that patients can easily answer, such as "Is your father named
George?" or "Were you born in the USA?" Automated instructions inform
patients that they may convey yes or no by (for example) focusing their
attention on stimuli on the right vs. left wrist. This focused attention
produces reliable changes in EEG patterns
that can help determine whether the patient is able to communicate. The
results could be presented to physicians and therapists, which could
lead to a revised diagnosis and therapy. 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.
Motor recovery
People
may lose some of their ability to move due to many causes, such as
stroke or injury. Research in recent years has demonstrated the utility
of EEG-based BCI systems in aiding motor recovery and
neurorehabilitation in patients who have had a stroke. Several groups have explored systems and methods for motor recovery that include BCIs.
In this approach, a BCI measures motor activity while the patient
imagines or attempts movements as directed by a therapist. The BCI may
provide two benefits: (1) if the BCI indicates that a patient is not
imagining a movement correctly (non-compliance), then the BCI could
inform the patient and therapist; and (2) rewarding feedback such as
functional stimulation or the movement of a virtual avatar also depends
on the patient's correct movement imagery.
So far, BCIs for motor recovery have relied on the EEG to measure
the patient's motor imagery. However, studies have also used fMRI to
study different changes in the brain as persons undergo BCI-based stroke
rehab training.
Imaging studies combined with EEG-based BCI systems hold promise for
investigating neuroplasticity during motor recovery post-stroke.
Future systems might include the fMRI and other measures for real-time
control, such as functional near-infrared, probably in tandem with EEGs.
Non-invasive brain stimulation has also been explored in combination
with BCIs for motor recovery. In 2016, scientists out of the University of Melbourne
published preclinical proof-of-concept data related to a potential
brain-computer interface technology platform being developed for
patients with paralysis to facilitate control of external devices such
as robotic limbs, computers and exoskeletons by translating brain
activity. Clinical trials are currently underway.
Functional brain mapping
Each year, about 400,000 people undergo brain mapping during neurosurgery. This procedure is often required for people with tumors or epilepsy that do not respond to medication.
During this procedure, electrodes are placed on the brain to precisely
identify the locations of structures and functional areas. Patients may
be awake during neurosurgery and asked to perform certain tasks, such as
moving fingers or repeating words. This is necessary so that surgeons
can remove only the desired tissue while sparing other regions, such as
critical movement or language regions. Removing too much brain tissue
can cause permanent damage, while removing too little tissue can leave
the underlying condition untreated and require additional neurosurgery. Thus, there is a strong need to improve both methods and systems to map the brain as effectively as possible.
In several recent publications, 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 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.
Flexible neural interfaces have been extensively tested in recent
years in an effort to minimize brain tissue trauma related to
mechanical mismatch between electrode and tissue. Minimizing tissue trauma could, in theory, extend the lifespan of BCIs relying on flexible electrode-tissue interfaces.
Neural dust is a term used to refer to millimeter-sized devices operated as wirelessly powered nerve sensors that were proposed in a 2011 paper from the University of California, Berkeley Wireless Research Center, which described both the challenges and outstanding benefits of creating a long lasting wireless BCI. In one proposed model of the neural dust sensor, the transistor model allowed for a method of separating between local field potentials and action potential "spikes", which would allow for a greatly diversified wealth of data acquirable from the recordings.
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