Brain-computer interfaces sound like the stuff of science fiction. There are as many as 85bn neurons in an adult human brain, and a Interactions between brains and machines have changed lives in other ways, too. Me, myself and AI studded with small gold bars that sits halfway up his left forearm. Brain-computer interfacing is a hot topic in the tech world, with Elon and machines as a remedy to the pesky problem of human mortality. Brain computer interfaces (BCI) would enable it. This could enhance the abilities of the entire human race and put us to the same pace This has been happening for years, but it's the scope of their reach that scares the heck out of me. We're just emotional machines, doing irrational things all the time.
Challenges are inherent in translating any new technology to practical and useful clinical applications, and BCIs are no exception. We discuss the potential uses and users of BCI systems and address some of the limitations and challenges facing the field.
We also consider the advances that may be possible in the next several years. A detailed presentation of the basic principles, current state, and future prospects of BCI technology was recently published.
A BCI is a computer-based system that acquires brain signals, analyzes them, and translates them into commands that are relayed to an output device to carry out a desired action. Thus, BCIs do not use the brain's normal output pathways of peripheral nerves and muscles.
This definition strictly limits the term BCI to systems that measure and use signals produced by the central nervous system CNS. Thus, for example, a voice-activated or muscle-activated communication system is not a BCI. Furthermore, an electroencephalogram EEG machine alone is not a BCI because it only records brain signals but does not generate an output that acts on the user's environment.
Brain-Computer Interfaces in Medicine
It is a misconception that BCIs are mind-reading devices. Brain-computer interfaces do not read minds in the sense of extracting information from unsuspecting or unwilling users but enable users to act on the world by using brain signals rather than muscles.
The user and the BCI work together. The user, often after a period of training, generates brain signals that encode intention, and the BCI, also after training, decodes the signals and translates them into commands to an output device that accomplishes the user's intention.
Milestones in BCI Development Can observable electrical brain signals be put to work as carriers of information in person-computer communication or for the purpose of controlling devices such as prostheses? That was the question posed by Vidal in Although work with monkeys in the late s showed that signals from single cortical neurons can be used to control a meter needle, 3 systematic investigations with humans really began in the s.
Initial progress in human BCI research was slow and limited by computer capabilities and our own knowledge of brain physiology. ByElbert et al 4 demonstrated that persons given biofeedback sessions of slow cortical potentials in EEG activity can change those potentials to control the vertical movements of a rocket image traveling across a television screen.
InFarwell and Donchin 5 showed how the P event-related potential could be used to allow normal volunteers to spell words on a computer screen.
Since the s, the mu and beta rhythms ie, sensorimotor rhythms recorded over the sensorimotor cortex were known to be associated with movement or movement imagery. Starting from this information, Wolpaw et al trained volunteers to control sensorimotor rhythm amplitudes and use them to move a cursor on a computer screen accurately in 1 or 2 dimensions.
Bya microelectrode array was implanted in the primary motor cortex of a young man with complete tetraplegia after a C3-C4 cervical injury. How close are we really to successfully connecting our brains to our technologies?
Melding mind and machine: How close are we?
And what might the implications be when our minds are plugged in? How do brain-computer interfaces work and what can they do? Inbefore there were even personal computers, he showed that monkeys can amplify their brain signals to control a needle that moved on a dial. Much of the recent work on BCIs aims to improve the quality of life of people who are paralyzed or have severe motor disabilities.
You may have seen some recent accomplishments in the news: University of Pittsburgh researchers use signals recorded inside the brain to control a robotic arm. Stanford researchers can extract the movement intentions of paralyzed patients from their brain signals, allowing them to use a tablet wirelessly.
Similarly, some limited virtual sensations can be sent back to the brain, by delivering electrical current inside the brain or to the brain surface.
Brain-Computer Interfaces in Medicine
What about our main senses of sight and sound? Very early versions of bionic eyes for people with severe vision impairment have been deployed commercially, and improved versions are undergoing human trials right now.
Cochlear implants, on the other hand, have become one of the most successful and most prevalent bionic implants — overusers around the world use the implants to hear. A bidirectional brain-computer interface BBCI can both record signals from the brain and send information back to the brain through stimulation. With all these successes to date, you might think a brain-computer interface is poised to be the next must-have consumer gadget.
Still early days An electrocorticography grid, used for detecting electrical changes on the surface of the brain, is being tested for electrical characteristics. When BCIs produce movements, they are much slower, less precise and less complex than what able-bodied people do easily every day with their limbs. Bionic eyes offer very low-resolution vision; cochlear implants can electronically carry limited speech information, but distort the experience of music.
Not all BCIs, however, are invasive.
Even with implanted electrodes, another problem with trying to read minds arises from how our brains are structured. We know that each neuron and their thousands of connected neighbors form an unimaginably large and ever-changing network. What might this mean for neuroengineers?