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The World's First Commercial Brain-Computer Interface + history of BCI

aa011A brain–computer interface (BCI), sometimes called a direct neural interface or a brain–machine interface, is a direct communication pathway between a brain and an external device. BCIs are often aimed at assisting, augmenting or repairing human cognitive or sensory-motor functions. Research on BCIs began in the 1970s at the University of California Los Angeles (UCLA) under a grant from the National Science Foundation, followed by a contract from DARPA. The papers published after this research also mark the first appearance of the expression brain–computer interface in scientific literature.



The field of BCI has since blossomed spectacularly, mostly toward neuroprosthetics applications that aim at restoring damaged hearing, sight and movement. Thanks to the remarkable cortical plasticity of the brain, signals from implanted prostheses can, after adaptation, be handled by the brain like natural sensor or effector channels. Following years of animal experimentation, the first neuroprosthetic devices implanted in humans appeared in the mid-nineties.

Animal BCI research



Several laboratories have managed to record signals from monkey and rat cerebral cortices in order to operate BCIs to carry out movement. Monkeys have navigated computer cursors on screen and commanded robotic arms to perform simple tasks simply by thinking about the task and without any motor output. In May 2008 photographs that showed a monkey operating a robotic arm with its mind at the Pittsburgh University Medical Center were published in a number of well known science journals and magazines. Other research on cats has decoded visual signals.

Experiments with monkeys in Neural Prosthetic Systems Laboratory at Stanford University.



Early work

The operant conditioning studies of Fetz and colleagues first demonstrated that monkeys could learn to control the deflection of a biofeedback meter arm with neural activity. Such work in the 1970s established that monkeys could quickly learn to voluntarily control the firing rates of individual and multiple neurons in the primary motor cortex if they were rewarded for generating appropriate patterns of neural activity.
Studies that developed algorithms to reconstruct movements from motor cortex neurons, which control movement, date back to the 1970s. 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.


April 9, 2008 lecture by Randy Breen for the Stanford University Computer Systems Colloquium (EE380). The Emotiv EPOC (www.emotiv.com) now makes it possible for games to be controlled and influenced by the player's mind. Engaging, immersive, and nuanced, Emotiv-inspired game-play will be like nothing ever seen before. Based on the latest developments in neuro-technology, Emotiv has developed a new personal interface for human computer interaction. EE380 | Computer Systems Colloquium: http://www.stanford.edu/class/ee380/

 

 

Today

New research from the University of Southampton has demonstrated that it is possible for communication from person to person through the power of thought -- with the help of electrodes, a computer and Internet connection.

Brain-Computer Interfacing (BCI) can be used for capturing brain signals and translating them into commands that allow humans to control (just by thinking) devices such as computers, robots, rehabilitation technology and virtual reality environments.

This experiment goes a step further and was conducted by Dr Christopher James from the University's Institute of Sound and Vibration Research. The aim was to expand the current limits of this technology and show that brain-to-brain (B2B) communication is possible.


Live demonstration of a brain-controlled Adams Family pinball machine by imagined movements at the CeBit IT fair 2010 in Hannover. While the player imagines left and right hand movements, algorithms decode his brain activity signals in realtime into control signals for the pinball machine. The demonstration shows the cutting edge performance of a brain-computer interface system with regard of timing precision of the control signal. Other (slower) applications are developed for communication needs of e.g. paralized patients. Involved partners of this project: Technische Universität Berlin (Machine Learning Lab); Charité University Hospital Berlin, Dept. Neurology. Pinball machine was kindly sponsored by BrainProducts GmbH.



A brain-computer interface based on EEG signals, developed by MMSPG. It allows to type a text without using one's fingers



Dr James comments: "Whilst BCI is no longer a new thing and person to person communication via the nervous system was shown previously in work by Professor Kevin Warwick from the University of Reading, here we show, for the first time, true brain to brain interfacing. We have yet to grasp the full implications of this but there are various scenarios where B2B could be of benefit such as helping people with severe debilitating muscle wasting diseases, or with the so-called 'locked-in' syndrome, to communicate and it also has applications for gaming."

His experiment had one person using BCI to transmit thoughts, translated as a series of binary digits, over the internet to another person whose computer receives the digits and transmits them to the second user's brain through flashing an LED lamp.


Two persons playing PONG. No mouse, no joystick just thought. Amazing. PLEASE* - you can link the video, embedd it on your blog - no problem. *BUT* do mention me as the author and put a link to my weblog at http://www.andreas.de/wordpress





While attached to an EEG amplifier, the first person would generate and transmit a series of binary digits, imagining moving their left arm for zero and their right arm for one. The second person was also attached to an EEG amplifier and their PC would pick up the stream of binary digits and flash an LED lamp at two different frequencies, one for zero and the other one for one. The pattern of the flashing LEDs is too subtle to be picked by the second person, but it is picked up by electrodes measuring the visual cortex of the recipient.

The encoded information is then extracted from the brain activity of the second user and the PC can decipher whether a zero or a one was transmitted. This shows true brain-to-brain activity.

You can watch Dr James' BCI experiment at:


Dr James is part of the University of Southampton's Brain-Computer Interfacing Research Programme, which brings together biomedical engineering and the clinical sciences and provides a cohesive scientific basis for rehabilitation research and management. Projects are driven by clinical problems, using cutting-edge signal processing research to produce an investigative tool for advancing knowledge of neurophysiological mechanisms, as well as providing a practical therapeutic system to be used outside a specialised BCI laboratory.

Dr James also appeared on BBC2's 'James May's Big Ideas' last year, talking about thought controlled wheelchairs and introducing the field of BCI. You can view the segment here:

 

 

How Brain-computer Interfaces Work

As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't about convenience -- for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades. In this article, we'll learn all about how BCIs work, their limitations and where they could be headed in the future.



The Electric Brain

The reason a BCI works at all is because of the way our brains function. Our brains are filled with neurons, individual nerve cells connected to one another by dendrites and axons. Every time we think, move, feel or remember something, our neurons are at work. That work is carried out by small electric signals that zip from neuron to neuron as fast as 250 mph [source: Walker]. The signals are generated by differences in electric potential carried by ions on the membrane of each neuron.
Although the paths the signals take are insulated by something called myelin, some of the electric signal escapes. Scientists can detect those signals, interpret what they mean and use them to direct a device of some kind. It can also work the other way around. For example, researchers could figure out what signals are sent to the brain by the optic nerve when someone sees the color red. They could rig a camera that would send those exact signals into someone's brain whenever the camera saw red, allowing a blind person to "see" without eyes.

 

BCI Drawbacks and Innovators

Although we already understand the basic principles behind BCIs, they don't work perfectly. There are several reasons for this.

1. The brain is incredibly complex. To say that all thoughts or actions are the result of simple electric signals in the brain is a gross understatement. There are about 100 billion neurons in a human brain [source: Greenfield]. Each neuron is constantly sending and receiving signals through a complex web of connections. There are chemical processes involved as well, which EEGs can't pick up on.
2. The signal is weak and prone to interference. EEGs measure tiny voltage potentials. Something as simple as the blinking eyelids of the subject can generate much stronger signals. Refinements in EEGs and implants will probably overcome this problem to some extent in the future, but for now, reading brain signals is like listening to a bad phone connection. There's lots of static.
3. The equipment is less than portable. It's far better than it used to be -- early systems were hardwired to massive mainframe computers. But some BCIs still require a wired connection to the equipment, and those that are wireless require the subject to carry a computer that can weigh around 10 pounds. Like all technology, this will surely become lighter and more wireless in the future.



 

BCI Innovators

A few companies are pioneers in the field of BCI. Most of them are still in the research stages, though a few products are offered commercially.

Neural Signals is developing technology to restore speech to disabled people. An implant in an area of the brain associated with speech (Broca's area) would transmit signals to a computer and then to a speaker. With training, the subject could learn to think each of the 39 phonemes in the English language and reconstruct speech through the computer and speaker [source: Neural Signals].
NASA has researched a similar system, although it reads electric signals from the nerves in the mouth and throat area, rather than directly from the brain. They succeeded in performing a Web search by mentally "typing" the term "NASA" into Google [source: New Scientist].
Cyberkinetics Neurotechnology Systems is marketing the BrainGate, a neural interface system that allows disabled people to control a wheelchair, robotic prosthesis or computer cursor [source: Cyberkinetics].
Japanese researchers have developed a preliminary BCI that allows the user to control their avatar in the online world Second Life [source: Ars Technica].


This is a headset with brain computer interface. It's exterior looks is designed by Tommi P. Laiho and functions by Sami Leino and Tommi P. Laiho.



Sources:
http://computer.howstuffworks.com
http://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface
http://www.sciencedaily.com
http://www.bbci.de/

 

 

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