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