Brain-computer interface - Revision history

Xinreality at 06:44, 29 April 2025

2025-04-29T06:44:21Z

← Older revision		Revision as of 06:44, 29 April 2025
Line 1:		Line 1:
	==Introduction==		==Introduction==

	A Brain-computer interface (BCI) is a technological system of communication that is based on neural activity generated by the brain <ref name=”1”> Vallabhaneni, A., Wang, T. and He, B. (2005). Brain-Computer Interface. Neural Engineering, Springer US, pp. 85-121</ref>. It’s comprised of four main parts: a means for acquiring neural signals from the brain, a method for isolating the desired specific features in that signal, an algorithm to decode the signals obtained, and a method for transforming the decoding into an action (Figure 1) <ref name=”2”> Sajda, P., Müller, KR. and Shenoy, K. V. (2008). Brain-Computer Interfaces. IEEE Signal Processing Magazine, 25(1): 16-17</ref> <ref name=”3”> He, B., Gao, S., Yuan, H. and Wolpaw, J. R. (2013). Brain-Computer Interfaces. Neural Engineering, Springer US, pp 87-151</ref>. This method of communication is independent of the normal output pathways of peripheral nerves and muscles, and the signal can be acquired by using invasive or non-invasive techniques <ref name=”1”></ref>. This technology can help to provide a means of communication for people disabled by neurological diseases or injuries, giving them a new channel of output for the brain. It can also enhance functions in healthy individuals <ref name=”1”></ref> <ref name=”2”></ref> <ref name=”3”></ref>. BCIs are also named brain-machine interfaces (BMIs) <ref name=”4”> McFarland, D. J. and Wolpaw, J. R. (2011). Brain-Computer Interfaces for Communication and Control. Commun ACM, 54(5): ~~60–66~~</ref>.		A Brain-computer interface (BCI) is a technological system of communication that is based on neural activity generated by the brain <ref name=”1”> Vallabhaneni, A., Wang, T. and He, B. (2005). Brain-Computer Interface. Neural Engineering, Springer US, pp. 85-121</ref>. It’s comprised of four main parts: a means for acquiring neural signals from the brain, a method for isolating the desired specific features in that signal, an algorithm to decode the signals obtained, and a method for transforming the decoding into an action (Figure 1) <ref name=”2”> Sajda, P., Müller, KR. and Shenoy, K. V. (2008). Brain-Computer Interfaces. IEEE Signal Processing Magazine, 25(1): 16-17</ref> <ref name=”3”> He, B., Gao, S., Yuan, H. and Wolpaw, J. R. (2013). Brain-Computer Interfaces. Neural Engineering, Springer US, pp 87-151</ref>. This method of communication is independent of the normal output pathways of peripheral nerves and muscles, and the signal can be acquired by using invasive or non-invasive techniques <ref name=”1”></ref>. This technology can help to provide a means of communication for people disabled by neurological diseases or injuries, giving them a new channel of output for the brain. It can also enhance functions in healthy individuals <ref name=”1”></ref> <ref name=”2”></ref> <ref name=”3”></ref>. BCIs are also named brain-machine interfaces (BMIs) <ref name=”4”> McFarland, D. J. and Wolpaw, J. R. (2011). Brain-Computer Interfaces for Communication and Control. Commun ACM, 54(5): 60-66</ref>.

	[[File:Figure 1. Basic design of a BCI system. (Image taken from Wolpaw et al., 2002).png\|thumb\|Figure 1 Basic design of a BCI system. (Image taken from Wolpaw et al., 2002)]]		[[File:Figure 1. Basic design of a BCI system. (Image taken from Wolpaw et al., 2002).png\|thumb\|Figure 1 Basic design of a BCI system. (Image taken from Wolpaw et al., 2002)]]

	The central nervous system (CNS) responds to stimuli in the environment or in the body by producing an appropriate output that can be in the form of a neuromuscular or hormonal response. A BCI provides a new output for the CNS that is different from the typical neuromuscular and hormonal ones. It changes the electrophysiological signals from reflections of the CNS activity (such as an electroencephalography – or EEG - rhythm or a neuronal firing rate) into the intended products of that activity, such as messages and commands that act on the world and accomplish the person’s intent <ref name=”5”> Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G. and Vaughan, T. M. (2002). Brain-Computer Interfaces for Communication and Control. Clinical Neurophysiology 113: ~~767–791~~</ref>. Since it measures CNS activity, converting it into an artificial output, it can replace, restore, or enhance the natural CNS output, changing the interactions between the CNS and its internal or external environment <ref name=”3”></ref>.		The central nervous system (CNS) responds to stimuli in the environment or in the body by producing an appropriate output that can be in the form of a neuromuscular or hormonal response. A BCI provides a new output for the CNS that is different from the typical neuromuscular and hormonal ones. It changes the electrophysiological signals from reflections of the CNS activity (such as an electroencephalography, or EEG, rhythm or a neuronal firing rate) into the intended products of that activity, such as messages and commands that act on the world and accomplish the person’s intent <ref name=”5”> Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G. and Vaughan, T. M. (2002). Brain-Computer Interfaces for Communication and Control. Clinical Neurophysiology 113: 767-791</ref>. Since it measures CNS activity, converting it into an artificial output, it can replace, restore, or enhance the natural CNS output, changing the interactions between the CNS and its internal or external environment <ref name=”3”></ref>.

	The electrical signals produced by brain activity can be detected on the scalp, on the cortical surface, or within the brain. As mentioned previously, the BCI has the function of translating these electrical signals into outputs that allow the user to communicate without the peripheral nerves and muscles. This becomes relevant because, since the BCI does not depend on neuromuscular control, it can provide another way of communication for people with disorders such as amyotrophic lateral sclerosis (ALS), brainstem stroke, cerebral palsy and spinal cord injury <ref name=”4”></ref>. It needs to be mentioned that a BCI also depends on feedback and on the adaptation of brain activity based on that feedback. According to McFarland and Wolpaw (2011), “communication and control applications are interactive processes that require the user to observe the results of their efforts in order to maintain good performance and to correct mistakes <ref name=”4”></ref>.” The BCI system needs to provide feedback and interact with the adaptations the brain makes in response. The general BCI operation, therefore, depends on the interaction between the user’s brain (where the signals produced are measured by the BCI), and the BCI itself (that translates the signals into specific commands) <ref name=”5”></ref>. One of the most difficult challenges in BCI research is the management of the complex interactions between the concurrent adaptations of the CNS and the BCI <ref name=”3”></ref>.		The electrical signals produced by brain activity can be detected on the scalp, on the cortical surface, or within the brain. As mentioned previously, the BCI has the function of translating these electrical signals into outputs that allow the user to communicate without the peripheral nerves and muscles. This becomes relevant because, since the BCI does not depend on neuromuscular control, it can provide another way of communication for people with disorders such as amyotrophic lateral sclerosis (ALS), brainstem stroke, cerebral palsy and spinal cord injury <ref name=”4”></ref>. It needs to be mentioned that a BCI also depends on feedback and on the adaptation of brain activity based on that feedback. According to McFarland and Wolpaw (2011), “communication and control applications are interactive processes that require the user to observe the results of their efforts in order to maintain good performance and to correct mistakes <ref name=”4”></ref>.” The BCI system needs to provide feedback and interact with the adaptations the brain makes in response. The general BCI operation, therefore, depends on the interaction between the user’s brain (where the signals produced are measured by the BCI), and the BCI itself (that translates the signals into specific commands) <ref name=”5”></ref>. One of the most difficult challenges in BCI research is the management of the complex interactions between the concurrent adaptations of the CNS and the BCI <ref name=”3”></ref>.
Line 33:		Line 33:
	==Brief overview of the development of Brain-Computer Interfaces==		==Brief overview of the development of Brain-Computer Interfaces==

	For a long time, there was speculation that a device such as an electroencephalogram, which can record electrical potentials generated by brain activity, could be used to control devices by taking advantage of the signals obtained by it <ref name=”1”></ref>. In the 1960s there where the first demonstrations of BCIs technology. These were made in 1964 by Grey Walter, which used a signal recorded on the scalp by EEG to control a slide projector. Ebenhard Fetz also helped advance the development of BCIs teaching monkeys to control a meter needle by changing the firing rate of a single cortical neuron. Moving forward to the 1970s, Jacques Vidal developed a system that determined the eye-gaze direction using the scalp-recorded visual evoked potential over the visual cortex to determine the direction in which the user wanted to move a computer cursor. The term brain-computer interface can be traced to Vidal <ref name=”4”></ref>. During 1980, Elbert T. and colleagues demonstrated that people could learn to control slow cortical potentials (SCPs) in scalp-recorded RRG activity. This was used to adjust the vertical position of a rocket image moving on a TV screen. Still in the 1980s, more specifically in 1988, Farwell and Donchin proved that people could use the P300 event-related potentials to spell words on a computer screen. Another major development was when Wolpaw and colleagues trained people to control the amplitude of mu and beta rhythms – sensorimotor rhythms – using the EEG recorded over the sensorimotor cortex. They demonstrated that users could use the mu and beta rhythms to move a computer cursor in one or two dimensions <ref name=”3”></ref>.		For a long time, there was speculation that a device such as an electroencephalogram, which can record electrical potentials generated by brain activity, could be used to control devices by taking advantage of the signals obtained by it <ref name=”1”></ref>. In the 1960s there where the first demonstrations of BCIs technology. These were made in 1964 by Grey Walter, which used a signal recorded on the scalp by EEG to control a slide projector. Ebenhard Fetz also helped advance the development of BCIs teaching monkeys to control a meter needle by changing the firing rate of a single cortical neuron. Moving forward to the 1970s, Jacques Vidal developed a system that determined the eye-gaze direction using the scalp-recorded visual evoked potential over the visual cortex to determine the direction in which the user wanted to move a computer cursor. The term brain-computer interface can be traced to Vidal <ref name=”4”></ref>. During 1980, Elbert T. and colleagues demonstrated that people could learn to control slow cortical potentials (SCPs) in scalp-recorded RRG activity. This was used to adjust the vertical position of a rocket image moving on a TV screen. Still in the 1980s, more specifically in 1988, Farwell and Donchin proved that people could use the P300 event-related potentials to spell words on a computer screen. Another major development was when Wolpaw and colleagues trained people to control the amplitude of mu and beta rhythms, sensorimotor rhythms, using the EEG recorded over the sensorimotor cortex. They demonstrated that users could use the mu and beta rhythms to move a computer cursor in one or two dimensions <ref name=”3”></ref>.

	The research of BCIs increased rapidly in the mid-1990s, continuing to grow into the present years. During the past 20 years, the research has covered a broad range of areas that are relevant to the development of BCI technology, such as basic and applied neuroscience, biomedical engineering, materials engineering, electrical engineering, signal processing, computer science, assistive technology, and clinical rehabilitation <ref name=”3”></ref>.		The research of BCIs increased rapidly in the mid-1990s, continuing to grow into the present years. During the past 20 years, the research has covered a broad range of areas that are relevant to the development of BCI technology, such as basic and applied neuroscience, biomedical engineering, materials engineering, electrical engineering, signal processing, computer science, assistive technology, and clinical rehabilitation <ref name=”3”></ref>.
Line 51:		Line 51:
	==BCI signals==		==BCI signals==

	As mentioned above, brain signals acquired by different methods can be used as BCI inputs. But not all signals are the same: they can differ substantially in regards to topographical resolution, frequency content, area of origin, and technical needs. For example, their resolution can range from EEG – that has millimeter resolution – to electrocorticogram (ECoG), with its millimeter resolution, to neuronal action potentials that have tens-of-microns resolution. The main issue when considering signals for BCI usage is what signals can best indicate the user’s intent <ref name=”3”></ref> <ref name=”5”></ref>.		As mentioned above, brain signals acquired by different methods can be used as BCI inputs. But not all signals are the same: they can differ substantially in regards to topographical resolution, frequency content, area of origin, and technical needs. For example, their resolution can range from EEG, that has millimeter resolution, to electrocorticogram (ECoG), with its millimeter resolution, to neuronal action potentials that have tens-of-microns resolution. The main issue when considering signals for BCI usage is what signals can best indicate the user’s intent <ref name=”3”></ref> <ref name=”5”></ref>.

	Sensorimotor rhythms were first reported by Wolpaw et al. (1991) for cursor control. These are EEG rhythms that vary according to movement or the imagination of movement and are spontaneous, not requiring specific stimuli for their occurrence <ref name=”3”></ref> <ref name=”5”></ref>. The P300 type of signal is an endogenous event-related potential component in the EEG <ref name=”3”></ref>. It is a positive potential that occurs around 300 msec after an event that has significance to the user. The BCIs based on the P300 potential do not depend on muscle control, such as eye movement since it reflects attention rather than simply gaze direction. Both sensorimotor rhythms and the P300 have demonstrated that the noninvasive acquiring of these brain signals can be used for communication and control of devices <ref name=”4”></ref>.		Sensorimotor rhythms were first reported by Wolpaw et al. (1991) for cursor control. These are EEG rhythms that vary according to movement or the imagination of movement and are spontaneous, not requiring specific stimuli for their occurrence <ref name=”3”></ref> <ref name=”5”></ref>. The P300 type of signal is an endogenous event-related potential component in the EEG <ref name=”3”></ref>. It is a positive potential that occurs around 300 msec after an event that has significance to the user. The BCIs based on the P300 potential do not depend on muscle control, such as eye movement since it reflects attention rather than simply gaze direction. Both sensorimotor rhythms and the P300 have demonstrated that the noninvasive acquiring of these brain signals can be used for communication and control of devices <ref name=”4”></ref>.
Line 84:		Line 84:
	[[Neurable]] - Building BCI for [[VR]] and [[AR]]		[[Neurable]] - Building BCI for [[VR]] and [[AR]]

	[[Neuralink]] - [[Elon Musk]]'s company to develop [[implantable]] [[~~brain–computer~~ interface]]		[[Neuralink]] - [[Elon Musk]]'s company to develop [[implantable]] [[brain-computer interface]]

	==References==		==References==

Paulo Pacheco at 17:17, 13 December 2017

2017-12-13T17:17:10Z

← Older revision		Revision as of 17:17, 13 December 2017
Line 19:		Line 19:
	'''Dependent and independent BCIs'''		'''Dependent and independent BCIs'''

	The commands that the user sends to the external world through the BCI system do not follow the same output pathways of peripheral nerves and muscles. Instead, a BCI provides the user with an alternative method for acting on the world. The BCIs can be in two different classes: dependent and independent <ref name=”5”></ref>. These terms appeared in 2002, and both are used to describe BCIs that use brain signals for the control of applications. The difference between them is in how they depend on natural CNS output <ref name=”3”></ref>.		The commands that the user sends to the external world through the BCI system do not follow the same output pathways of peripheral nerves and muscles. Instead, a BCI provides the user with an alternative method for acting on the world. The BCIs can be placed in two different classes: dependent and independent <ref name=”5”></ref>. These terms appeared in 2002, and both are used to describe BCIs that use brain signals for the control of applications. The difference between them is in how they depend on natural CNS output <ref name=”3”></ref>.

	A dependent BCI uses brains signals that depend on muscle activity <ref name=”3”></ref>, such as in the case of a BCI that present the user with a matrix of letters. Each letter flashes one at a time, and it is the objective of the user to select a specific letter by looking directly at it. This initiates a visual evoked potential (VEP) that is recorded from the scalp. The VEP produced when the right intended letter flashes is greater than the VEPs produced when other letters flash. In this example, the brain’s output channel is EEG, but the generation of the signal that is detected is dependent on the direction of the gaze which, in turn, depends on extraocular muscles and the cranial nerves that activate them <ref name=”5”></ref>.		A dependent BCI uses brains signals that depend on muscle activity <ref name=”3”></ref>, such as in the case of a BCI that present the user with a matrix of letters. Each letter flashes one at a time, and it is the objective of the user to select a specific letter by looking directly at it. This initiates a visual evoked potential (VEP) that is recorded from the scalp. The VEP produced when the right intended letter flashes is greater than the VEPs produced when other letters flash. In this example, the brain’s output channel is EEG, but the generation of the signal that is detected is dependent on the direction of the gaze which, in turn, depends on extraocular muscles and the cranial nerves that activate them <ref name=”5”></ref>.

Paulo Pacheco at 17:12, 13 December 2017

2017-12-13T17:12:49Z

← Older revision		Revision as of 17:12, 13 December 2017
Line 13:		Line 13:
	'''The biology of BCIs'''		'''The biology of BCIs'''

	Since the BCI includes both a biological and technological ~~components~~, without specific characteristics of the biological factor that can be used, the system would not work. The technology works because of the way our brains function <ref name=”6”> Grabianowski, E. How Brain-Computer Interfaces Work. Retrieved from computer.howstuffworks.com/brain-computer-interface.htm</ref>. The human brain (arguably the most complex signal processing machine in existence) is capable of transducing a variety of environmental signals and to extract information from them in order to produce behavior, cognition, and action <ref name=”2”></ref> <ref name=”3”></ref>. The ~~brains have~~ a myriad of neurons ~~that are~~ individual nerve cells ~~that are~~ connected to one another by dendrites and axons. The actions of the brain are carried out by small electric signals ~~that are~~ generated by differences in electric potential carried by ions on the membranes of the neurons Even though the signal pathways are insulated by myelin, there is a residual electric signal that escapes and that can be detected, interpreted and used, such as in the case of BCIs. This also allows for the development of technologies that send signals into specific regions of the brain~~, such as in the case of the optic nerve~~. By connecting a camera that could send the same signals as the eye (or close enough) to the brain, a blind person could regain some measure of vision <ref name=”6”></ref>.		Since the BCI includes both a biological and technological component, without specific characteristics of the biological factor that can be used, the system would not work. The technology works because of the way our brains function <ref name=”6”> Grabianowski, E. How Brain-Computer Interfaces Work. Retrieved from computer.howstuffworks.com/brain-computer-interface.htm</ref>. The human brain (arguably the most complex signal processing machine in existence) is capable of transducing a variety of environmental signals and to extract information from them in order to produce behavior, cognition, and action <ref name=”2”></ref> <ref name=”3”></ref>. The brain has a myriad of neurons - individual nerve cells connected to one another by dendrites and axons. The actions of the brain are carried out by small electric signals generated by differences in electric potential carried by ions on the membranes of the neurons. Even though the signal pathways are insulated by myelin, there is a residual electric signal that escapes and that can be detected, interpreted, and used, such as in the case of BCIs. This also allows for the development of technologies that send signals into specific regions of the brain. By connecting a camera that could send the same signals as the eye (or close enough) to the brain, a blind person could regain some measure of vision <ref name=”6”></ref>.

	The non-~~invasively~~ recording of the electrical brain activity by electrodes on the surface of the scalp has been known for over 80 years ~~ago~~, due to the work of Hans Berger. His observations demonstrated that the electroencephalogram (EEG) could be used as “an index of the gross state of the brain.” Besides the detection of electrical signals of the brain, ~~the~~ neural activity can also be monitored by measuring magnetic fields or hemoglobin oxygenation~~, by~~ using sensors on the scalp, the surface of the brain, or within the brain <ref name=”4”></ref>.		The non-invasive recording of the electrical brain activity by electrodes on the surface of the scalp has been known for over 80 years, due to the work of Hans Berger. His observations demonstrated that the electroencephalogram (EEG) could be used as “an index of the gross state of the brain.” Besides the detection of electrical signals from the brain, neural activity can also be monitored by measuring magnetic fields or hemoglobin oxygenation using sensors on the scalp, the surface of the brain, or within the brain <ref name=”4”></ref>.

	'''Dependent and independent BCIs'''		'''Dependent and independent BCIs'''

Paulo Pacheco at 16:52, 13 December 2017

2017-12-13T16:52:25Z

← Older revision		Revision as of 16:52, 13 December 2017
Line 1:		Line 1:
	==Introduction==		==Introduction==

	A Brain-computer interface (BCI) is a technological system of communication that is based on neural activity generated by the brain <ref name=”1”> Vallabhaneni, A., Wang, T. and He, B. (2005). Brain-Computer Interface. Neural Engineering, Springer US, pp. 85-121</ref>. It’s comprised of four main parts: a means for acquiring neural signals from the brain, a method for isolating the desired specific features in that signal, an algorithm to decode the signals obtained and a method for transforming the decoding into an action (Figure 1) <ref name=”2”> Sajda, P., Müller, KR. and Shenoy, K. V. (2008). Brain-Computer Interfaces. IEEE Signal Processing Magazine, 25(1): 16-17</ref> <ref name=”3”> He, B., Gao, S., Yuan, H. and Wolpaw, J. R. (2013). Brain-Computer Interfaces. Neural Engineering, Springer US, pp 87-151</ref>. This method of communication is independent of the normal output pathways of peripheral nerves and muscles~~. The~~ signal can be acquired by using invasive or non-invasive techniques <ref name=”1”></ref>. This technology can help to provide a means of communication for people disabled by neurological diseases or injuries, ~~providing~~ a new channel of output for the brain ~~to the user~~. It can also enhance functions in healthy individuals <ref name=”1”></ref> <ref name=”2”></ref> <ref name=”3”></ref>. BCIs are also named brain-machine interfaces (BMIs) <ref name=”4”> McFarland, D. J. and Wolpaw, J. R. (2011). Brain-Computer Interfaces for Communication and Control. Commun ACM, 54(5): 60–66</ref>.		A Brain-computer interface (BCI) is a technological system of communication that is based on neural activity generated by the brain <ref name=”1”> Vallabhaneni, A., Wang, T. and He, B. (2005). Brain-Computer Interface. Neural Engineering, Springer US, pp. 85-121</ref>. It’s comprised of four main parts: a means for acquiring neural signals from the brain, a method for isolating the desired specific features in that signal, an algorithm to decode the signals obtained, and a method for transforming the decoding into an action (Figure 1) <ref name=”2”> Sajda, P., Müller, KR. and Shenoy, K. V. (2008). Brain-Computer Interfaces. IEEE Signal Processing Magazine, 25(1): 16-17</ref> <ref name=”3”> He, B., Gao, S., Yuan, H. and Wolpaw, J. R. (2013). Brain-Computer Interfaces. Neural Engineering, Springer US, pp 87-151</ref>. This method of communication is independent of the normal output pathways of peripheral nerves and muscles, and the signal can be acquired by using invasive or non-invasive techniques <ref name=”1”></ref>. This technology can help to provide a means of communication for people disabled by neurological diseases or injuries, giving them a new channel of output for the brain. It can also enhance functions in healthy individuals <ref name=”1”></ref> <ref name=”2”></ref> <ref name=”3”></ref>. BCIs are also named brain-machine interfaces (BMIs) <ref name=”4”> McFarland, D. J. and Wolpaw, J. R. (2011). Brain-Computer Interfaces for Communication and Control. Commun ACM, 54(5): 60–66</ref>.

	[[File:Figure 1. Basic design of a BCI system. (Image taken from Wolpaw et al., 2002).png\|thumb\|Figure 1 Basic design of a BCI system. (Image taken from Wolpaw et al., 2002)]]		[[File:Figure 1. Basic design of a BCI system. (Image taken from Wolpaw et al., 2002).png\|thumb\|Figure 1 Basic design of a BCI system. (Image taken from Wolpaw et al., 2002)]]

	The central nervous system (CNS) responds to stimuli in the environment or in the body by producing an appropriate output that can be in the form of a neuromuscular or hormonal response. A BCI provides a new output for the CNS that is different from the typical neuromuscular and hormonal ones. It changes the electrophysiological signals from reflections of the CNS activity (such as an electroencephalography – or EEG - rhythm or a neuronal firing rate) into the intended products of that activity, such as messages and commands that act on the world and accomplish the person’s intent <ref name=”5”> Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G. and Vaughan, T. M. (2002). Brain-Computer Interfaces for Communication and Control. Clinical Neurophysiology 113: 767–791</ref>. Since it measures CNS activity, converting it into an artificial output, it can replace, restore, or enhance the natural CNS output, changing the interactions between the CNS and its internal or external environment <ref name=”3”></ref>. The electrical signals produced by the brain activity can be detected on the scalp, on the cortical surface, or within the brain. As mentioned previously, the BCI has the function of translating these electrical signals into outputs that allow the user to communicate without the peripheral nerves and muscles. This becomes relevant because, since the BCI does not depend on neuromuscular control, it can provide another way of communication for people with disorders such as amyotrophic lateral sclerosis (ALS), brainstem stroke, cerebral palsy and spinal cord injury <ref name=”4”></ref>. It needs to be mentioned that a BCI also depends on feedback and on adaptation of brain activity based on that feedback. According to McFarland and Wolpaw (2011), “communication and control applications are interactive processes that require the user to observe the results of their efforts in order to maintain good performance and to correct mistakes <ref name=”4”></ref>.” The BCI system needs to provide feedback and interact with the adaptations the brains makes in response. The general BCI operation therefore depends on the interaction of the user’s brain (where the signals are produced that are measured by the BCI), and the BCI itself (that translates the signals into specific commands) <ref name=”5”></ref>. One of the most difficult challenges in BCI research is the management of the complex interactions between the concurrent adaptations of the CNS and the BCI <ref name=”3”></ref>.		The central nervous system (CNS) responds to stimuli in the environment or in the body by producing an appropriate output that can be in the form of a neuromuscular or hormonal response. A BCI provides a new output for the CNS that is different from the typical neuromuscular and hormonal ones. It changes the electrophysiological signals from reflections of the CNS activity (such as an electroencephalography – or EEG - rhythm or a neuronal firing rate) into the intended products of that activity, such as messages and commands that act on the world and accomplish the person’s intent <ref name=”5”> Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G. and Vaughan, T. M. (2002). Brain-Computer Interfaces for Communication and Control. Clinical Neurophysiology 113: 767–791</ref>. Since it measures CNS activity, converting it into an artificial output, it can replace, restore, or enhance the natural CNS output, changing the interactions between the CNS and its internal or external environment <ref name=”3”></ref>.

	Even though the main objective of BCI research and development is the creation of assistive communication and control technology for disabled people with different ailments, BCIs also have potential as a new type of interface for interacting with a computer or machine for people with normal neurological function. This could be applied to the general population in gaming, for example, or in high-stress situations like air traffic control. There could also be systems that enhance or supplement human performance such as image analysis, and systems that expand the media access or artistic expression. There has been some research into another possible application for the BCI technology: assistance in the rehabilitation of people disabled by a stroke and other acute events <ref name=”2”></ref> <ref name=”3”></ref>.		The electrical signals produced by brain activity can be detected on the scalp, on the cortical surface, or within the brain. As mentioned previously, the BCI has the function of translating these electrical signals into outputs that allow the user to communicate without the peripheral nerves and muscles. This becomes relevant because, since the BCI does not depend on neuromuscular control, it can provide another way of communication for people with disorders such as amyotrophic lateral sclerosis (ALS), brainstem stroke, cerebral palsy and spinal cord injury <ref name=”4”></ref>. It needs to be mentioned that a BCI also depends on feedback and on the adaptation of brain activity based on that feedback. According to McFarland and Wolpaw (2011), “communication and control applications are interactive processes that require the user to observe the results of their efforts in order to maintain good performance and to correct mistakes <ref name=”4”></ref>.” The BCI system needs to provide feedback and interact with the adaptations the brain makes in response. The general BCI operation, therefore, depends on the interaction between the user’s brain (where the signals produced are measured by the BCI), and the BCI itself (that translates the signals into specific commands) <ref name=”5”></ref>. One of the most difficult challenges in BCI research is the management of the complex interactions between the concurrent adaptations of the CNS and the BCI <ref name=”3”></ref>.

			Even though the main objective of BCI research and development is the creation of assistive communication and control technology for disabled people with different ailments, BCIs also have potential as a new type of interface for interacting with a computer or machine for people with normal neurological function. This could be applied to the general population in areas such as gaming, for example, or in high-stress situations like air traffic control. There could also be systems that enhance or supplement human performance such as image analysis, and systems that expand the media access or artistic expression. There has been some research into another possible application for the BCI technology: assistance in the rehabilitation of people disabled by a stroke and other acute events <ref name=”2”></ref> <ref name=”3”></ref>.

	'''The biology of BCIs'''		'''The biology of BCIs'''

Paulo Pacheco at 12:58, 13 December 2017

2017-12-13T12:58:22Z

Show changes

Neo222 at 02:19, 29 August 2017

2017-08-29T02:19:37Z

← Older revision		Revision as of 02:19, 29 August 2017
Line 81:		Line 81:

	[[Neurable]] - Building BCI for [[VR]] and [[AR]]		[[Neurable]] - Building BCI for [[VR]] and [[AR]]

			[[Neuralink]] - [[Elon Musk]]'s company to develop [[implantable]] [[brain–computer interface]]

	==References==		==References==

Neo222: /* See Also */

2017-08-03T22:38:06Z

Xinreality at 00:27, 17 April 2017

2017-04-17T00:27:37Z

← Older revision		Revision as of 00:27, 17 April 2017
Line 76:		Line 76:

	A BCI output could enhance natural CNS output. For example, as a method to prevent the loss of attention when someone is engaged in a task that requires constant focus. A BCI could detect the brain activity that precedes break in attention and create an output (a sound for example) that would alert the person. It could also supplement natural CNS output, such as in the case of a person that uses a BCI to control a third robotic arm, for example, or to choose items when a user that is controlling the position of the cursor selects them. In these cases the BCI supplements the natural neuromuscular output with another, the artificial output. Finally, the BCI output could improve the natural CNS output. As an example, a person whose arm movements are compromised by a sensorimotor cortex damaged by a stroke could use a BCI system to measure signals from the damaged areas and then excite muscles or control an orthosis that would improve arm movement <ref name=”3”></ref>.		A BCI output could enhance natural CNS output. For example, as a method to prevent the loss of attention when someone is engaged in a task that requires constant focus. A BCI could detect the brain activity that precedes break in attention and create an output (a sound for example) that would alert the person. It could also supplement natural CNS output, such as in the case of a person that uses a BCI to control a third robotic arm, for example, or to choose items when a user that is controlling the position of the cursor selects them. In these cases the BCI supplements the natural neuromuscular output with another, the artificial output. Finally, the BCI output could improve the natural CNS output. As an example, a person whose arm movements are compromised by a sensorimotor cortex damaged by a stroke could use a BCI system to measure signals from the damaged areas and then excite muscles or control an orthosis that would improve arm movement <ref name=”3”></ref>.

			==See Also==
			'''[[OpenBCI]]'''

	==References==		==References==

Paulo Pacheco at 15:51, 7 September 2016

2016-09-07T15:51:21Z

Show changes

Xinreality at 20:33, 5 September 2016

2016-09-05T20:33:36Z

← Older revision		Revision as of 20:33, 5 September 2016
Line 34:		Line 34:

	==References==		==References==
			<references />

			[[Category:Terms]] [[Category:Technical Terms]]

← Older revision		Revision as of 22:38, 3 August 2017
Line 79:		Line 79:
	==See Also==		==See Also==
	'''[[OpenBCI]]'''		'''[[OpenBCI]]'''

			[[Neurable]] - Building BCI for [[VR]] and [[AR]]

	==References==		==References==