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A brain-computer interface (BCI), sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a human or animal brain (or brain cell culture) and an external device. In one-way BCIs, computers either accept commands from the brain or send signals to it (for example, to restore vision) but not both. Two-way BCIs would allow brains and external devices to exchange information in both directions. In this definition, the word brain means the brain or nervous system of an organic life form rather than the mind. Computer means any processing or computational device, from simple circuits to silicon chips. Research on BCIs has been going on for more than 30 years, and from the mid-1990s there has been a dramatic increase in the knowledge gleaned from experiments. Years of animal experimentation have produced early working implants in humans designed to restore damaged hearing, sight and movement. The common thread throughout the research is the remarkable cortical plasticity of the brain, which often adapts to BCIs, treating prostheses controlled by implants as natural limbs. With recent advances in technology and knowledge, pioneering researchers could now conceivably attempt to produce BCIs that augment human functions rather than simply restoring them, previously only the realm of science fiction. BCI versus Neuroprosthetics Neuroprosthetics is an area of neuroscience concerned with neural prostheses — using artificial devices to replace the function of impaired nervous systems or sensory organs. The most widely used neuroprosthetic device is the cochlear implant, which was implanted in approximately 100,000 people worldwide as of 2006.• There are also several neuroprosthetic devices that aim to restore vision, including retinal implants, although this article only discusses implants directly into the brain. The differences between BCIs and neuroprosthetics are mostly in the ways the terms are used: "neuroprosthetics" typically refers to clinical devices, whereas many BCIs are still in the experimental realm. Practical neuroprosthetics can be linked to any part of nervous systems, for example peripheral nerves, while the term "BCI" often designates a narrower class of systems which interface with the brain directly. The terms are sometimes used interchangeably and for good reason. Neuroprosthetics and BCI seek to achieve the same aims, such as restoring sight, hearing, movement and even cognitive function. Both use similar experimental methods and surgical techniques. Animal BCI research
Early work Studies that developed algorithms to reconstruct movements from motor cortex neurons, which control movement, date back to the 1970s. Work by groups led by Schmidt, Fetz and Baker in the 1970s established that monkeys could quickly learn to voluntarily control the firing rate of individual neurons in the primary motor cortex after closed-loop operant conditioning, a training method using punishment and rewards. In the 1980s, Apostolos 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 that monkeys moved their arms (based on a cosine function). He also found that dispersed groups of neurons in different areas of the brain collectively controlled motor commands but was only able to record the firings of neurons in one area at a time because of technical limitations imposed by his equipment. There has been rapid development in BCIs since the mid-1990s. Several groups have been able to capture complex brain motor centre signals using recordings from neural ensembles (groups of neurons) and use these to control external devices, including research groups led by Richard Andersen, John Donoghue, Phillip Kennedy, Miguel Nicolelis and Andrew Schwartz. Prominent research successes
Invasive BCIs Invasive BCI research has targeted repairing damaged sight and providing new functionality to paralysed people. Invasive BCIs are implanted directly into the grey matter of the brain during neurosurgery. As they rest 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 lost 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 come up with 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 TV 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 and at a low frame-rate also requiring him to be hooked up to a two-ton mainframe. Shrinking electronics and faster computers made his artificial eye more portable and allowed him to perform simple tasks unassisted. 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 slowly around the parking area of the research institute. BCIs focusing on motor neuroprosthetics aim to either restore movement in paralysed individuals 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, suffered from ‘locked-in syndrome’ after suffering a brain-stem stroke. 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. Tetraplegic Matt 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 Neurotechnology’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.• Partially-invasive BCIs Partially invasive BCI devices are implanted inside the skull but rest outside the brain rather than among the grey matter. They produce better resolution signals than non-invasive BCIs where the bone tissue of the cranium deflects and deforms signals and have a lower risk of forming scar-tissue in the brain than fully-invasive BCIs. Electrocorticography (ECoG) uses the same technology as non-invasive electroencephalography (see below), but the electrodes are embedded in a thin plastic pad that is placed above the cortex, beneath the dura mater. ECoG technologies were first trialed 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 it is difficult to produce kinematic BCI devices with more than one dimension of control using ECoG. Light Reactive Imaging BCI devices are still in the realm of theory. These would involve implanting a laser inside the skull. The laser would be trained on a single neurons and the neuron's reflectance measured by a separate sensor. When the neuron fires, the laser light pattern and wavelengths it reflects would change slightly. This would allow researchers to monitor single neurons but require less contact with tissue and reduce the risk of scar-tissue build-up. Non-invasive BCIs As well as invasive experiments, there have also been experiments in humans using non-invasive neuroimaging technologies as interfaces. Signals recorded in this way have been used to power muscle implants and restore partial movement in an experimental volunteer. Although they are easy to wear, non-invasive implants produce poor signal resolution because the skull dampens signals, dispersing and blurring the electromagnetic waves created by the neurons. Although the waves can still be detected it is more difficult to determine the area of the brain that created them or the actions of individual neurons. Electroencephalography (EEG) is the most studied potential non-invasive interface, mainly due to its fine temporal resolution, ease of use, portability and low set-up cost. But as well as the technology's susceptibility to noise, another substantial barrier to using EEG as a brain-computer interface is the extensive training required before users can work the technology. For example, in experiments beginning in the mid-1990s, Niels Birbaumer of the University of Tübingen in Germany used EEG recordings of slow cortical potential to give paralysed patients limited control over 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. Another research parameter is the type of waves measured. Birbaumer's later research with Jonathan Wolpaw at New York State University has focused on developing technology that would allow users to choose the brain signals they found easiest to operate a BCI, including mu and beta waves. 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 recognise 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 2000, for example, research by Jessica Bayliss at the University of Rochester showed that volunteers wearing virtual reality helmets could control elements in a virtual world using their P300 EEG readings, including turning lights on and off and bringing a mock-up car to a stop. In 1999, researchers at Case Western Reserve University 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. Electronic neural networks have been deployed shift the learning phase from the user to the computer. Experiments by scientists at the Fraunhofer Society in 2004 using neural networks led to noticeable improvements within 30 minutes of training. Experiments by Eduardo Miranda aim to use EEG recordings of mental activity associated with music to allow the disabled to express themselves musically through an encephalophone. Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) have both been used successfully as non-invasive BCIs. In a widely reported experiment, fMRI allowed two users being scanned to play Pong in real-time by altering their haemodynamic response or brain blood flow through biofeedback techniques. 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. Commercialization and companies John Donoghue and fellow researchers founded Cyberkinetics. Now listed on a US stock exchange and known as Cyberkinetic Neurotechnology Inc, the company markets its electrode arrays under the BrainGate product name and has set the development of practical BCIs for humans as its major goal. The BrainGate is based on the Utah Array developed by Dick Normann. Philip Kennedy founded Neural Signals in 1987 to develop BCIs that would allow paralysed patients to communicate with the outside world and control external devices. As well as an invasive BCI, the company also sells an implant to restore speech. Neural Signals' Brain Communicator BCI device uses glass cones containing microelectrodes coated with proteins to encourage the electrodes to bind to neurons. Although 16 paying patients were treated using William Dobelle's vision BCI, new implants ceased within a year of Dobelle's death in 2004. A company controlled by Dobelle, Avery Biomedical Devices, and Stony Brook University are continuing development of the implant, which has not yet received FDA approval for human implantation. Cell-culture BCIs Researchers have also 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. 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 is 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. 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 begin to reconnect themselves to form a living neural network. The cells were arranged over a grid of 60 electrodes and trained 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. Ethical considerations Discussions about the ethical implications of BCIs has been relatively muted. This may be because the research holds great promise in the fight against disability, BCI researchers have yet to attract the attention of animal rights groups and because BCIs are being used to acquire signals to control devices rather than the other way round. Vision research is the exception to this. This ethical debate is likely to intensify as BCIs become technologically advanced and it becomes apparent that they may not just be used therapeutically but to enhance human function. Today's brain pacemakers, which are already used to treat neurological conditions such as depression could become a type of BCI and be used to modify other behaviours which society considers undesireable. Neurochips could also develop further, for example the artificial hippocampus, raising issues about what it actually means to be human. Some of the ethical considerations that BCIs would raise under these circumstances are already being debated in relation to brain implants and the broader area of mind control. Theme in fiction The prospect of BCIs and brain implants of all kinds have been important themes in science fiction, manga and anime. See brain implants in fiction and philosophy for a review of this literature. See also Organisations (for a list of universites see Neural Engineering - Neural Engineering Labs) Researchers listed in above text Portals and articles | |||||||||||
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