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Force Trainer

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The Force Trainer is a Star Wars -themed toy which creates the illusion of performing Force -powered telekinesis .

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70-405: The brain–computer interface toy, released was Uncle Milton Industries ' Star Wars Science line in 2009, comes with a headset that claims to sense the brain's electric fields (similar to an EEG ) and relays the signals to a tube that uses a fan to blow a ball into the air. The harder the user concentrates, the harder the fan blows, and the higher the ball is suspended. The voice of Yoda instructs

140-460: 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

210-556: A mu wave can be found over the primary motor cortex . Human alpha rhythm has generators in the pulvinar and lateral geniculate nucleus (LGN) and the visual cortex. Several analyses suggest that cortical alpha leads pulvinar (thalamic) alpha, complicating prevailing theories of a thalamic pacemaker. Halgren, M et al. discovered that alpha acts within the nervous system by propagating from cortex to thalamus and higher-order to lower-order cortex. The experimental and computational models explored by Traub RD et al. suggested cortical-

280-426: A string galvanometer to create a photograph of the electrical activity of a dog's brain. Using similar techniques, Berger confirmed the existence of electrical activity in the human brain. He first did this by presenting a stimulus to hospital patients with skull damage and measuring the electrical activity in their brains. Later he ceased the stimulus method and began measuring the natural rhythmic electrical cycles in

350-546: A BCI with sensory feedback with rhesus monkeys. The monkey controlled 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 that have developed BCIs and algorithms that decode neuron signals include John Donoghue at the Carney Institute for Brain Science at Brown University , Andrew Schwartz at

420-516: 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

490-566: A first, second, and third-place winner, who receive awards of $ 3,000, $ 2,000, and $ 1,000, respectively. Invasive BCI requires surgery to implant electrodes under the scalp for accessing brain signals. The main advantage is to increase accuracy. Downsides include side effects from the surgery, including scar tissue that can obstruct brain signals or the body may not accept the implanted electrodes. Invasive BCI research has targeted repairing damaged sight and providing new functionality for people with paralysis. Invasive BCIs are implanted directly into

560-605: A grant from the National Science Foundation , followed by a contract from the Defence Advanced Research Projects Agency ( 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,

630-687: A healthy adult's. That's clearly a stretch, but the Jell-O EEG readings do look pretty similar to a normal human alpha rhythm. Alpha waves are observed when a patient is awake and resting with eyes closed, and in some kinds of sleep and reversible coma. True, the Jell-O waves are a little slower and of much lower amplitude, barely within normal human limits, but that doesn't tell you much by itself. Hypoxia, encephalitis, and other medical conditions can cause reduced frequency and amplitude, as can drug use. Alpha waves were discovered by German neurologist Hans Berger ,

700-419: A human brain implant that produced signals of high enough quality to simulate movement. Their patient, Johnny Ray (1944–2002), developed ' locked-in syndrome ' after 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 . Tetraplegic Matt Nagle became

770-460: A lamina- and principal neuron subtype specific origin for the visual alpha rhythm. On the basis of examination of patients with congenital visual defects, it was established that the existence of an efficient and complete visual pathway is necessary for the development of a correct EEG activity pattern. This wave begins appearing at around four months, and is initially a frequency of 4 waves per second. The mature alpha wave, at 10 waves per second,

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840-475: 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

910-487: A mound of Jell-O in Upton's experiments) to cause signals to appear on an EEG readout, causing false signals to be interpreted as healthy alpha waves. This finding suggests that it is possible that a non-flat EEG could lead to the interpretation that a patient is still living when in fact he or she is long dead. Cecil Adams from The Straight Dope discusses this scenario: Sometimes it's claimed Jell-O brainwaves are identical to

980-541: A one-Hertz reduction in alpha wave frequency relative to controls. Alpha wave intrusion occurs when the alpha waves appear with non-REM sleep when delta activity is expected. It is hypothesized to be associated with fibromyalgia with increased phasic alpha sleep activity correlated with clinical manifestations of fibromyalgia, such as longer pain duration. Despite this, alpha wave intrusion has not been significantly linked to any major sleep disorder , including chronic fatigue syndrome , and major depression . However, it

1050-407: A patient's brain and used deep learning to synthesize speech. In 2021, those researchers reported 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 is the lack of a sensor modality that provides safe, accurate and robust access to brain signals. The use of a better sensor expands

1120-417: A person is doing something automatically, or "on auto-pilot", and not paying attention to the task they are performing. After the mistake was noticed by the subject, there was a decrease in alpha waves as the subject began paying more attention. This study hopes to promote the use of wireless EEG technology on employees in high-risk fields, such as air traffic controlling, to monitor alpha wave activity and gauge

1190-526: A robot arm. Their deeply cleft and furrowed brains made them 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 and learned to control it by viewing its movements. The BCI used velocity predictions to control reaching movements and simultaneously predicted gripping force . In 2011 O'Doherty and colleagues showed

1260-505: A robotic arm. The same group demonstrated that a monkey could feed itself pieces of fruit and marshmallows using a robotic arm controlled by the animal's brain signals. Andersen's group used recordings of premovement activity from the posterior parietal cortex , including signals created when experimental animals anticipated receiving a reward. In addition to predicting kinematic and kinetic parameters of limb movements, BCIs that predict electromyographic or electrical activity of

1330-403: 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, a study reported 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

1400-471: A series of 16 paying patients to receive Dobelle's second generation implant, 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

1470-508: A subject. Two researchers in the United States explored this concept through unrelated experiments. Joe Kamiya, of the University of Chicago, discovered that some individuals had the conscious ability to recognize when they were creating alpha waves, and could increase their alpha activity. These individuals were motivated through a reward system from Kamiya. The second progenitor of biofeedback

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1540-554: A wakeful period during sleep. This has been attributed to studies where subjects report non-refreshing sleep and have EEG records reporting high levels of alpha intrusion into sleep. This occurrence is known as alpha wave intrusion. However, it is possible that these explanations may be misleading, as they only focus on alpha waves being generated from the occipital lobe. Mindfulness meditation has been shown to increase alpha wave power in both healthy subjects and patients. Practitioners of Transcendental Meditation have demonstrated

1610-469: Is Barry Sterman, from the University of California, Los Angeles. He was working with monitoring brain waves in cats and found that, when the cats were trained to withhold motor movement, they released SMR, or mu, waves , a wave similar to alpha waves. Using a reward system, he further trained these cats to enter this state more easily. Later, he was approached by the United States Air Force to test

1680-415: Is common in chronic fatigued patients, and may amplify the effects of other sleep disorders. Following this lapse-of-attention line of thought, a recent study indicates that alpha waves may be used to predict mistakes. In it, MEGs measured increases of up to 25% in alpha brain wave activity before mistakes occurred. This study used common sense: alpha waves indicate idleness, and mistakes are often made when

1750-453: Is firmly established by age 3. Other research finds an increase in alpha frequency from about 9 Hz at the age of five to about 12 Hz in 21 year olds. This shift has been linked to changes in the optic radiation and correlates with improvement in visual perception. Some researchers posit that there are at least two forms of alpha waves, which may have different functions in the wake-sleep cycle. Alpha waves are present at different stages of

1820-422: Is located in a frontal-central location in the brain. The purpose of alpha activity during REM sleep has yet to be fully understood. Currently, there are arguments that alpha patterns are a normal part of REM sleep, and for the notion that it indicates a semi-arousal period. It has been suggested that this alpha activity is inversely related to REM sleep pressure. It has long been believed that alpha waves indicate

1890-718: The Altran Foundation for Innovation prize for developing a Brain Computer Interface with electrodes located on the surface of the skull, instead of directly in the brain. Research teams led by the BrainGate group and another at University of Pittsburgh Medical Center , both in collaborations with the United States Department of Veterans Affairs (VA), demonstrated control of prosthetic limbs with many degrees of freedom using direct connections to arrays of neurons in

1960-633: The EEG in 1924. Alpha waves are one type of brain waves detected by electrophysiological and closely related methods, such as by electroencephalography (EEG) or magnetoencephalography (MEG), and can be quantified using quantitative electroencephalography (qEEG). They can be predominantly recorded from the occipital lobes during wakeful relaxation with closed eyes and were the earliest brain rhythm recorded in humans. Alpha waves are reduced with open eyes and sleep, while they are enhanced during drowsiness. Occipital alpha waves during periods of eyes closed are

2030-525: The University of Pittsburgh , and Richard Andersen at Caltech . These researchers produced working BCIs using recorded signals from far fewer neurons than Nicolelis (15–30 neurons versus 50–200 neurons). 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 a joystick. The group created a BCI for three-dimensional tracking in virtual reality and reproduced BCI control in

2100-401: 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 weaken, or disappear, as the body reacts to the foreign object. In vision science , direct brain implants have been used to treat non- congenital (acquired) blindness. One of

2170-493: The retina . Neuron firings were recorded from watching eight short movies. Using mathematical filters, the researchers decoded the signals to reconstruct recognizable scenes and moving objects. Duke University professor Miguel Nicolelis advocates using multiple electrodes spread over a greater area of the brain to obtain neuronal signals. After initial studies in rats during the 1990s, Nicolelis and colleagues developed BCIs that decoded brain activity in owl monkeys and used

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2240-481: 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 cortex neurons , 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

2310-544: The appearance of the alpha rhythm with open eyes may indicate a temporary shutdown of visual information processing in the primary visual cortex at the moments when the subject analyzes the image in visual memory. At these moments, information is processed in the association areas of the visual cortex (hV4, V3v, VO1, VO2 areas). One study suggests that a "visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency)" can result in substantially faster perceptual visual learning , maintained

2380-406: The attention level of the employee. A study has shown that the appearance of an alpha rhythm with open eyes can be a predictor of visual information processing in working memory. It was shown that the moment of appearance of alpha activity depends on the type of stimulus in memory and the number of visual characteristics (color, shape, etc.) that it needs to keep in memory. The authors suggest that

2450-445: The brain's electrical activity and the development of electroencephalography (EEG). In 1924 Berger was the first to record human brain activity utilizing EEG. Berger was able to identify oscillatory activity , such as the alpha wave (8–13 Hz), by analyzing EEG traces. Berger's first recording device was rudimentary. He inserted silver wires under the scalps of his patients. These were later replaced by silver foils attached to

2520-558: The brain, manifested by CNV, used a feedback loop to control the S2 buzzer in the S1-S2-CNV paradigm. The resulting cognitive wave representing the expectation learning in the brain was termed Electroexpectogram (EXG). The CNV brain potential was part of Vidal's 1973 challenge. Studies in the 2010s suggested neural stimulation's potential to restore functional connectivity and associated behaviors through modulation of molecular mechanisms. This opened

2590-569: The brain. The first natural rhythm he documented was what would become known as the alpha wave. Berger was very thorough and meticulous in his data-gathering, but despite his brilliance, he did not feel confident enough to publish his discoveries until at least five years after he had made them. In 1929, he published his first findings on alpha waves in the journal Archiv für Psychiatrie . He was originally met with derision for his EEG technique and his subsequent alpha and beta wave discoveries. His technique and findings did not gain widespread acceptance in

2660-474: The company had successfully enabled a monkey to play video games using Neuralink's device. 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

2730-405: The context of a simple learning task, illumination of transfected cells in the somatosensory cortex influenced decision-making in mice. BCIs led to a deeper understanding of neural networks and the central nervous system . Research has reported that despite neuroscientists' inclination to believe that neurons have the most effect when working together, single neurons can be conditioned through

2800-437: The day following training. In particular, the entrainment substantially accelerated learning in a discrimination task to detect targets embedded in background clutter or to identify radial vs. concentric Glass patterns embedded in noise compared to entrainment that does not match an individual's alpha frequency. As demonstrated by Dr. Adrian R. M. Upton, it is possible for extraneous sources (ambient fluctuations detected with

2870-563: The devices to reproduce monkey movements in robotic arms. Monkeys' advanced reaching and grasping abilities and hand manipulation skills, made them good test subjects. 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 remotely control a separate robot. But the monkeys received no feedback ( open-loop BCI). Later experiments on rhesus monkeys included feedback and reproduced monkey reaching and grasping movements in

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2940-532: 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. Phillip Kennedy (Neural Signals founder (1987) and colleagues built

3010-460: 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

3080-442: The effects of a jet fuel that was known to cause seizures in humans. Sterman tested the effects of this fuel on the previously-trained cats, and discovered that they had a higher resistance to seizures than non-trained cats. Alpha wave biofeedback has gained interest for having some successes in humans for seizure suppression and for treatment of depression. Alpha waves again gained interest in regards to an engineering approach to

3150-472: The electrodes are connected directly to each other instead of being worn by the player, the game will proceed to play itself and pass all of the training exercises without any user input. This Star Wars -related article is a stub . You can help Misplaced Pages by expanding it . This toy -related article is a stub . You can help Misplaced Pages by expanding it . Brain%E2%80%93computer interface A brain–computer interface ( BCI ), sometimes called

3220-523: The first neuroprosthetic devices were implanted in humans in the mid-1990s. Studies in human-computer interaction via the application of machine learning to statistical temporal features extracted from the frontal lobe ( EEG brainwave ) data has achieved success in classifying mental states (relaxed, neutral, concentrating), mental emotional states (negative, neutral, positive), and thalamocortical dysrhythmia . The history of brain-computer interfaces (BCIs) starts with Hans Berger 's discovery of

3290-457: The first intracortical brain–computer interface by implanting neurotrophic-cone electrodes into monkeys. In 1999, Yang Dan et al. at University of California, Berkeley decoded neuronal firings to reproduce images from cats. The team used an array of electrodes embedded in the thalamus (which integrates the brain's sensory input). Researchers targeted 177 brain cells in the thalamus lateral geniculate nucleus area, which decodes signals from

3360-481: 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 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, Jonathan Wolpaw received

3430-432: 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

3500-485: 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

3570-400: 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. In 2002, Jens Naumann, also blinded in adulthood, became the first in

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3640-481: The inventor of the EEG itself. Alpha waves were among the first waves documented by Berger, along with beta waves , and he displayed an interest in "alpha blockage", the process by which alpha waves decrease and beta waves increase upon a subject opening their eyes. This distinction earned the alpha wave the alternate title of "Berger's Wave". Berger took a cue from Ukrainian physiologist Vladimir Pravdich-Neminsky , who used

3710-399: The motor cortex of tetraplegia patients. In May 2021, a Stanford University team reported a successful proof-of-concept test that enabled a quadraplegic participant to produce 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

3780-469: The motor cortex, utilizing Hidden Markov models and recurrent neural networks . Alpha wave Alpha waves , or the alpha rhythm , are neural oscillations in the frequency range of 8–12 Hz likely originating from the synchronous and coherent ( in phase or constructive) electrical activity of thalamic pacemaker cells in humans. Historically, they are also called "Berger's waves" after Hans Berger , who first described them when he invented

3850-431: The muscles of primates are in process. Such BCIs could restore mobility in paralyzed limbs by electrically stimulating muscles. Nicolelis and colleagues demonstrated that large neural ensembles can predict arm position. This work allowed BCIs to read arm movement intentions and translate them into actuator movements. Carmena and colleagues programmed a BCI that allowed a monkey to control reaching and grasping movements by

3920-435: The neuronal mass principle, the neural degeneracy principle, and the plasticity principle. BCIs are proposed to be applied by users without disabilities. Passive BCIs allow for assessing and interpreting changes in the user state during Human-Computer Interaction ( HCI ). In a secondary, implicit control loop, the system adapts to its user, improving its usability . BCI systems can potentially be used to encode signals from

3990-524: The parking area of the research institute. Dobelle died in 2004 before his processes and developments were documented, leaving no one to continue his work. Subsequently, Naumann and the other patients in the program began having problems with their vision, and eventually lost their "sight" again. BCIs focusing on motor neuroprosthetics aim to restore movement in individuals with paralysis or provide devices to assist them, such as interfaces with computers or robot arms. Kennedy and Bakay were first to install

4060-533: 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 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

4130-400: The periphery. These sensory BCI devices enable real-time, behaviorally-relevant decisions based upon closed-loop neural stimulation. The BCI Research Award is awarded annually in recognition of innovative research. Each year, a renowned research laboratory is asked to judge projects. The jury consists of BCI experts recruited by that laboratory. The jury selects twelve nominees, then chooses

4200-402: 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

4270-442: The psychological community until 1937, when he gained the approval of the famous physiologist Lord Adrian , who took a particular interest in alpha waves. Alpha waves again gained recognition in the early 1960s and 1970s with the creation of a biofeedback theory relating to brain waves (see below). Such biofeedback, referred to as a kind of neurofeedback , relating to alpha waves is the conscious elicitation of alpha brainwaves by

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4340-498: 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 BCI2000 , a general-purpose system for BCI research, since 2000. A new 'wireless' approach uses light-gated ion channels such as channelrhodopsin to control the activity of genetically defined subsets of neurons in vivo . In

4410-420: 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

4480-563: The strongest EEG brain signals. Historically, alpha waves were thought to represent the activity of the visual cortex in an idle state. More recently, research suggests that they inhibit areas of the cortex not in use, or alternatively that they play an active role in network coordination and communication. Whether they are inhibitory or play an active role in attention links to their direction of propagation, with top-down rearward waves being inhibitory, and forward bottom-up ones aiding visual attentional processes. An alpha-like variant called

4550-411: 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

4620-464: The term had not yet been coined, one of the earliest examples of a working brain-machine interface was the piece Music for Solo Performer (1965) by American composer Alvin Lucier . The piece makes use of EEG and analog signal processing hardware (filters, amplifiers, and a mixing board) to stimulate acoustic percussion instruments. Performing the piece requires producing alpha waves and thereby "playing"

4690-425: The use of BCIs to fire in a pattern that allows primates to control motor outputs. BCIs led to development of the single neuron insufficiency principle that states that even with a well-tuned firing rate, single neurons can only carry limited information and therefore the highest level of accuracy is achieved by recording ensemble firings. Other principles discovered with BCIs include the neuronal multitasking principle,

4760-624: The user on developing their skills. In a 2010 episode of the College Humor series Bleep Bloop , the hosts Jeff Rubin and Pat Cassels tested out the toy, even having a co-worker, Brian Murphy, play Brain Age , a video game advertised as making you use your brain more, while he had the Force Trainer headset on. One user of the toy argues that the brainwave effect of the Force Trainer II is fake; if

4830-440: 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

4900-417: The wake-sleep cycle. The most widely researched is during the relaxed mental state, where the subject is at rest with eyes closed, but is not tired or asleep. This alpha activity is centered in the occipital lobe , although there has been speculation that it has a thalamic origin. The second occurrence of alpha wave activity is during REM sleep . As opposed to the awake form of alpha activity, this form

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