A brain–computer interface (BCI) is a direct communication pathway between the brain and an external device. BCIs are often directed at assisting, augmenting, or repairing human cognitive or sensory-motor functions.

The field of BCI research and development has since focused primarily on 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-1990s.

The history of brain–computer interfaces (BCIs) starts with Hans Berger's discovery of the electrical activity of the human brain and the development of electroencephalography (EEG). In 1924 Berger was the first to record human brain activity by means of EEG. By analyzing EEG traces, Berger was able to identify oscillatory activity in the brain, such as the alpha wave (8–12 Hz), also known as Berger's wave.

Berger's first recording device was very rudimentary. He inserted silver wires under the scalps of his patients. These were later replaced by silver foils attached to the patients' head by rubber bandages. Berger connected these sensors to a Lippmann capillary electrometer, with disappointing results. More sophisticated measuring devices, such as the Siemens double-coil recording galvanometer, which displayed electric voltages as small as one ten thousandth of a volt, led to success.

Berger analyzed the interrelation of alternations in his EEG wave diagrams with brain diseases. EEGs permitted completely new possibilities for the research of human brain activities.

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 organs. The most widely used neuroprosthetic device is the cochlear implant which, as of 2006, had been implanted in approximately 100,000 people worldwide. There are also several neuroprosthetic devices that aim to restore vision, including retinal implants.

The difference between BCIs and neuroprosthetics is mostly in how the terms are used: neuroprosthetics typically connect the nervous system to a device, whereas BCIs usually connect the brain (or nervous system) with a computer system. Practical neuroprosthetics can be linked to any part of the nervous system—for example, peripheral nerves—while the term "BCI" usually designates a narrower class of systems which interface with the central nervous system.

The terms are sometimes, however, 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.

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.

ECoG (Electrocorticography) has recently emerged as a promising recording technique for use in brain-computer interfaces (BCI). BCIs are direct neural interfaces that provide control of prosthetic, electronic, or communication devices via direct use of the individual’s brain signals. Brain signals may be recorded either invasively, with recording devices implanted directly into the cortex, or noninvasively, using EEG scalp electrodes. ECoG serves to provide a partially invasive compromise between the two modalities – while ECoG does not penetrate the blood–brain barrier like invasive recording devices, it features a higher spatial resolution and higher signal-to-noise ratio than EEG. A recent study by Shenoy et al. demonstrates the high movement classification accuracy potential of ECoG-based BCIs.

Brain-machine interfaces (BMIs) have been developed within the last 20 years. By recording single unit potentials, these devices can decode signals through a computer and output this signal for control of an external device such as a computer cursor or prosthetic limb. BMIs have the potential to restore function in patients with paralysis or neurological disease. This technology has potential to reach a wide variety of patients but is not yet available clinically due to lack of reliability in recording signals over time. The primary hypothesis regarding this failure is that the chronic inflammatory response around the electrode causes neurodegeneration that reduces the number of neurons it is able to record from (Nicolelis, 2001). In 2004, the BrainGate pilot clinical trial was initiated to "test the safety and feasibility of a neural interface system based on an intracortical 100-electrode silicon recording array." This initiative has been successful in advancement of BCIs and in 2011, published data showing long term computer control in a patient with tetraplegia (Simeral, 2011).

See also:
https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface
https://en.wikipedia.org/wiki/Single-unit_recording
https://en.wikipedia.org/wiki/Electrocorticography

Source: Wikipedia (All text is available under the terms of the GNU Free Documentation License and Creative Commons Attribution-ShareAlike License.)