Difference between revisions of "Brain-computer interfaces"

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A '''Brain-computer interface''' or '''(BCI)''' is a direct communications link between a brain and a computer. BCIs have been proposed as a means by which a [[superintelligence]] could be created. Present developments of BCIs consists only of aiding those with disabilities, developing prostheses such as robotic arms, cochlear and retinal implants. There is no significant technical difference between restoring normal functionality and enhanced functionality, however. Developing BCIs is a task which is aided enormously by the [[wikipedia:Neuroplasticity| neuroplasticity]] of the brain.
 
  
Although many previously foreseen uses of BCIs are provided today by indirect computer links, many innovative possibilities remain, a short list of which follows: new sensory modules, direct communication including perfect coordination, knowledge and memory transfer, computer aided calculation, planning, research, debate, memory, neurochemical control, and even possibly neuronal editing. It is also possible that the development of BCIs could lead to a dystopia with actual mind control. A BCI might also permit the transfer of a human mind onto a digital substrate, permitting immortality and all the possibilities [[whole brain emulation]] implies.  
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A '''Brain Computer Interface (BCI)''' is the generic term used to describe any kind of system that serves as a communication bridge between the brain (human or not) and an artificial module. It’s a field of research in which wide investment has been made since the 1970’s, especially in the clinical fields and ergonomics.
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Generally speaking, any kind of brain activity that can be recorded can be used as a means of communicating with another system. Through the use of statistical classification techniques it’s possible to associate certain states or characteristics of the recorded signal – which the experiment subject learns to control - to any procedure, usually mediated by a computer.
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Many techniques have been developed to help us look and better understand the way the brain works. They range from imaging techniques (like MRI, fMRI, fNIRS or PET), to electrophysiological ones (like EEG, EcG or MEG). While the first category is usually used to obtain high resolution images of brain structures and the second one to register and analyze the electrical activity produced by the brain, with a high temporal resolution – which is why they are the ones mainly used in the field of BCI’s. In pair with such methods, although a different area in itself, includes brain implants capable of communicating directly with the neuronal tissue - [http://en.wikipedia.org/wiki/Neuroprosthetics neuroprosthetics].
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== EEG BCIs ==
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Of all the different means avaliable, the registering of the [http://en.wikipedia.org/wiki/Electroencephalography electroencephalographic (EEG)] activity is the most developed and extensively researched of this fields. It allows us, in a non-invasive way, to peak the brain functioning with a high temporal resolution – furthermore, it is now well established that different brain states produce distinct observable activity. With the help of electrodes placed on the scalp, it is possible to feed this activity and their respective variations and patterns to any system capable of classifying and detecting them in real time and act accordingly (making this a field highly interconnected to that of machine learning).
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The field of BCIs has followed closely the developments in signal processing and classification, along with the increasing computational power available. It was firstly researched as a communication means (for people unable to move, for instance) through the detection of ERPs – event related potentials, small variations of amplitude associated to the presentation of certain stimuli - as well as a way of automatically detecting epileptic seizures. Also, much owing to the first and major financers of such research, the [http://en.wikipedia.org/wiki/DARPA DARPA], the use of BCIs has been always closed associated to the military field. This has allowed insights regarding the detection of mental states of fatigue and attention variations, which has led to the development of informatics systems capable of adapting to the mental state of the user.
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Currently we have available a considerable range of both research and commercial applications of EEG based BCI systems with a wide list of applications. It has shown to be a field due to receive increased attention in the next years, especially through the developing of increasingly efficient classification algorithms and computer power, and the fascination with the cognitive augmentation it might bring.
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== Potential applications ==
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Although the EEG has been the main technique used for the development of such systems, it has been shown to be possible to integrate electronic controllers directly in the functioning of single cells or even networks. The [http://www.wired.com/wired/archive/10.09/vision.html permanent implant of devices for interpretation] and regulation of cortical activity has also been demonstrated.
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This has led to a renewed interest in the field and the exploration of new hypothesis, like drug rehabilitation through the detection of relevant cues and stimulation of the brain reward system, rehabilitation after strokes or lesion and even direct transmission of patterns of thought between subjects.
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Other attractive future application includes the [http://www.sim.me.uk/neural/JournalArticles/Bamford2012IJMC.pdf upload of the whole content of the brain], and thus the mind, to a computer. Although still speculative, it seems [http://intelligence.org/files/CoalescingMinds.pdf theoretically possible].
  
 
==External Links==
 
==External Links==
  
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*[http://intelligence.org/files/CoalescingMinds.pdf Brain content uploading]
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*[http://intelligence.org/brain-computer-interfaces/ Tech Summary: Brain-Computer Interfaces]
 
*[http://thinktechuk.wordpress.com/ ThinkTech] A blog dedicated to BCI developements
 
*[http://thinktechuk.wordpress.com/ ThinkTech] A blog dedicated to BCI developements
 
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*[http://www.emotiv.com Commercial EEG BCI System example]
 
*[http://www.kurzweilai.net/people-with-paralysis-control-robotic-arms-using-brain-computer-interface Paralyzed patient controls robot arm using BCI] Article from KurzweilAI
 
*[http://www.kurzweilai.net/people-with-paralysis-control-robotic-arms-using-brain-computer-interface Paralyzed patient controls robot arm using BCI] Article from KurzweilAI
 
 
*[http://www.youtube.com/watch?v=ogBX18maUiM Demonstration of paralyzed patient using robot arm] from Nature Magazine YouTube
 
*[http://www.youtube.com/watch?v=ogBX18maUiM Demonstration of paralyzed patient using robot arm] from Nature Magazine YouTube
 
 
*[http://www.youtube.com/watch?v=g0rRvBd7Dew&feature=endscreen&NR=1 Demonstration of a blind patient with a Retinal Implant reading] from Discovery Magazine YouTube
 
*[http://www.youtube.com/watch?v=g0rRvBd7Dew&feature=endscreen&NR=1 Demonstration of a blind patient with a Retinal Implant reading] from Discovery Magazine YouTube
  
*[http://mindstalk.net/vinge/vinge-sing.html Achieving the Singularity with Brain-computer interfaces] by Vernor Vinge
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== Further Reading & References==
 
 
*[http://www.amazon.co.uk/Beyond-Boundaries-Neuroscience-Connecting-Machines---And/dp/0805090525/ref=sr_1_1?ie=UTF8&qid=1339423006&sr=8-1 Beyond Boundaries] by Miguel Nicolelis on Amazon.
 
  
*[http://www.sim.me.uk/neural/JournalArticles/Bamford2012IJMC.pdf A Framework for approaches to transfer the Mind's Substrate] by Sim Bamford
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*Anderson, J. (1980). Neurocomputing. Cambridge: The MIT Press
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*Muller, D. (1995). Towards brain–computer interfacing. MIT Press, Cambridge, MA, 409–422.
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*Niedermeyer, E., & Lopes da Silva, F. (2004). Electroencephalography: Basic Principles. Clinical Applications and Related Fields. London
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*Vidal, J. (1977). Real-Time Detection of Brain Events in EEG. IEEE Proceedings,  65 (5), 633–641
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*Parasuraman, R. (2003). Neuroergonomics: Research and practice. Theoretical Issues in Ergonomics Science, 4, 5–20.
  
 
==See Also==
 
==See Also==
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*[[Biological Cognitive Enhancement]]
 
*[[Biological Cognitive Enhancement]]
 
*[[Whole brain emulation]]
 
*[[Whole brain emulation]]
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*[[Wireheading]]

Latest revision as of 02:13, 14 September 2012

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Wikipedia has an article about


A Brain Computer Interface (BCI) is the generic term used to describe any kind of system that serves as a communication bridge between the brain (human or not) and an artificial module. It’s a field of research in which wide investment has been made since the 1970’s, especially in the clinical fields and ergonomics. Generally speaking, any kind of brain activity that can be recorded can be used as a means of communicating with another system. Through the use of statistical classification techniques it’s possible to associate certain states or characteristics of the recorded signal – which the experiment subject learns to control - to any procedure, usually mediated by a computer.

Many techniques have been developed to help us look and better understand the way the brain works. They range from imaging techniques (like MRI, fMRI, fNIRS or PET), to electrophysiological ones (like EEG, EcG or MEG). While the first category is usually used to obtain high resolution images of brain structures and the second one to register and analyze the electrical activity produced by the brain, with a high temporal resolution – which is why they are the ones mainly used in the field of BCI’s. In pair with such methods, although a different area in itself, includes brain implants capable of communicating directly with the neuronal tissue - neuroprosthetics.

EEG BCIs

Of all the different means avaliable, the registering of the electroencephalographic (EEG) activity is the most developed and extensively researched of this fields. It allows us, in a non-invasive way, to peak the brain functioning with a high temporal resolution – furthermore, it is now well established that different brain states produce distinct observable activity. With the help of electrodes placed on the scalp, it is possible to feed this activity and their respective variations and patterns to any system capable of classifying and detecting them in real time and act accordingly (making this a field highly interconnected to that of machine learning).

The field of BCIs has followed closely the developments in signal processing and classification, along with the increasing computational power available. It was firstly researched as a communication means (for people unable to move, for instance) through the detection of ERPs – event related potentials, small variations of amplitude associated to the presentation of certain stimuli - as well as a way of automatically detecting epileptic seizures. Also, much owing to the first and major financers of such research, the DARPA, the use of BCIs has been always closed associated to the military field. This has allowed insights regarding the detection of mental states of fatigue and attention variations, which has led to the development of informatics systems capable of adapting to the mental state of the user.

Currently we have available a considerable range of both research and commercial applications of EEG based BCI systems with a wide list of applications. It has shown to be a field due to receive increased attention in the next years, especially through the developing of increasingly efficient classification algorithms and computer power, and the fascination with the cognitive augmentation it might bring.

Potential applications

Although the EEG has been the main technique used for the development of such systems, it has been shown to be possible to integrate electronic controllers directly in the functioning of single cells or even networks. The permanent implant of devices for interpretation and regulation of cortical activity has also been demonstrated.

This has led to a renewed interest in the field and the exploration of new hypothesis, like drug rehabilitation through the detection of relevant cues and stimulation of the brain reward system, rehabilitation after strokes or lesion and even direct transmission of patterns of thought between subjects.

Other attractive future application includes the upload of the whole content of the brain, and thus the mind, to a computer. Although still speculative, it seems theoretically possible.

External Links

Further Reading & References

  • Anderson, J. (1980). Neurocomputing. Cambridge: The MIT Press
  • Muller, D. (1995). Towards brain–computer interfacing. MIT Press, Cambridge, MA, 409–422.
  • Niedermeyer, E., & Lopes da Silva, F. (2004). Electroencephalography: Basic Principles. Clinical Applications and Related Fields. London
  • Vidal, J. (1977). Real-Time Detection of Brain Events in EEG. IEEE Proceedings, 65 (5), 633–641
  • Parasuraman, R. (2003). Neuroergonomics: Research and practice. Theoretical Issues in Ergonomics Science, 4, 5–20.

See Also