Neuroelectronics
Neuroelectronics
History
Neuroelectronics, sometimes referred to as neurotechnology, is the discipline that deals with the interface between the human nervous system and electronic devices. It is a highly complex and interdisciplinary field with contributions from computer science, cognitive science, neurosurgery and biomedical engineering. Neuroelectronics has roughly three related branches: (1) neuroimaging, (2) brain-computer interfaces (BCIs), and (3) electrical neural stimulation. The discipline exists for more than half a century. However, in the last decade significant advances have been made, particularly in neuroimaging, which revolutionized the field by allowing researchers to directly monitor brain activity during experiments. And it is predicted that neuroelectronics, particularly neuroimaging and brain-computer interfacing, will be employed much more in the future.
Application Areas/Examples
Neuroimaging has two branches: (1) structural imaging, which tries to unravel the structure, or anatomy, of the brain, and (2) functional imaging, which tries to examine functions of (certain areas of) the brain. The latter enables a researcher to directly visualize how information is processed in different areas of the brain (European Technology Assessment Group, 2006). Both structural and functional neuroimaging are used for diagnostic as well as research purposes. Contemporary neuroimaging techniques such as Magnetic Resonance Imaging (MRI) and Functional Magnetic Resonance Imaging (fMRI) are used for cancer scanning, stroke rehabilitation and functional analyses of cognitive processes in the brain. fMRI is the cornerstone technology to study the human brain. Other neuroimaging techniques such as electroencephalography (EEG), positron emission tomography (PET), and magnetoencephalography (MEG), amongst others, are also used by researchers to study brain structure and function.
BCIs, sometimes called brain-machine interfaces (BMIs), are an emerging neurotechnology that translates brain activity into command signals for external devices. Research on BCIs began in the 1970s at the University of California Los Angeles (UCLA). Researchers at UCLA also coined the term brain-computer interface. A BCI establishes a direct communication pathway between the brain and the device to be controlled. They are mainly being developed for medical reasons, because there is a societal demand for technologies which help to restore functions of humans with central nervous system (CNS) disabilities (Berger, 2007). Patients for whom a BCI would be useful usually have disabilities in motor function or communication. This could be (partly) restored by using a BCI to steer a motorized wheelchair, prosthesis, or by selecting letters on a computer screen with a cursor. Invasive or non-invasive electrodes are used to detect brain activity, which is subsequently translated by a signal processing unit into command signals for the external device. The most common BCI responds to specific patterns detected in spatiotemporal EEGs measured non-invasively from the scalp. Spatiotemporal EEGs can be controlled by imagining specific movements (Gasson & Warwick, 2007). So, merely by imagining movements one can steer a wheelchair, prosthesis or a cursor on a computer screen.
- Brain fingerprinting.
Brain fingerprinting is a particular application of neuroimaging. The idea behind it is that the brain processes known, relevant information differently from the way it processes unknown or irrelevant information. The brain’s processing of known information, such as the details of a crime stored in the brain, is revealed by a specific pattern in the EEG. So it is claimed that brain fingerprinting can be used for lie detection (Simon, 2005)
- BCI to control an aircraft.
Defense Advanced Research Projects Agency (DARPA) has a brain-machine interface program to control an aircraft (Rocco & Bainbridge, 2002).
- BCI to control a motorized wheelchair.
A BCI is being developed that enables a person with locked-in syndrome, a severe neurological disorder that almost totally paralyses a person, to control a motorized wheelchair (Berger, 2007).
- BCI for spelling.
A BCI may help to restore one’s ability to communicate. The application then uses brain signals to control a cursor on a computer screen. After some practice, the cursor control becomes accurate enough to spell words and sentences by using the interface to pick out letters of the alphabet from a virtual keyboard (Friman et al, 2007).
- Neuroimaging.
‘A wearable brain imaging tool will enable identification of children with learning disabilities, assessing the effectiveness of learning as well as identifying the emotional state of a human being’ (Beckert, Bluemel, Friedewald & Thielmann, 2008).
Definition and Defining Features
There are roughly three branches in neuroelectronics. Each branch uses different devices to interface with the brain, and each of these devices has different features. The first branch, neuroimaging, uses techniques such as fMRI, PET, MEG or EEG, amongst others, to extract information from the brain to diagnose disorders or to study the brain. The second branch, BCIs, uses invasive or non-invasive electrodes to extract information from the brain, not for diagnostic or research purposes, but to control external devices such as wheelchairs, computers or airplanes. And the third branch, electrical neural stimulation, uses invasive electrodes to send electrical signals to specific parts of the brain. The only defining feature these three branches have in common is that they all interface electrical devices with the brain, either to extract information from the brain or to send electrical signals to the brain.
In overview:
- Neuroimaging technologies extract information from the brain to diagnose disorders or study brain structure or function.
- BCIs extract information from the brain to control external devices such as wheelchairs, prosthesis or computers.
- Electrical neural stimulation devices stimulate parts of the brain so that symptoms like tremor, clinical depression or pain are reduced.
Timeline
This seems to be an ongoing development for the time being.
Relation to Other Technologies
Neuroelectronics is closely related to bioelectronics; the field that interfaces the human body with electrical devices. Strictly speaking neuroelectronics is a branch of bioelectronics, since the brain and nervous system are part of the human body. Bioelectronics has resulted in several healthcare applications such as electrocardiography, cardiac peacemakers and blood glucose meters. Neuroelectronics is also related to biometrics, which are technologies to uniquely identify humans based upon one or more physical or behavioral traits. Neuroimaging technologies can be used to identify humans based on their brain activity patterns. Some have argued that neuroimaging and BCIs can be used for ambient intelligence systems. Such systems need as much information of its users as possible regarding their interactions, thoughts and feelings. And information from the brain extracted either with (portable) neuroimaging technologies or BCIs provide valuable information for an ambient intelligence system (Gasson & Warwick, 2007). Finally, neuroelectronics is highly interdisciplinary and receives contributions from computer science, cognitive science, neurosurgery and biomedical engineering.
Critical Issues
Several critical issues are expressed concerning neuroelectronics in one of the texts on emerging ICT. Neuroimaging and brain-computer interfacing allow processing of neural signals and it is assumed that neural signals may indicate – even represent – thoughts. Under what conditions can the extracted neural signals be considered as creative and specific enough to invoke intellectual-property rights? Furthermore, there is a fundamental right of protection of personal data and hereby states that personal data may only be processed on the basis of the consent of the person concerned or some other legitimate basis laid down by law. Also, can certain thoughts, when registered by neuroimaging or brain-computer interfacing, be a work of invention that falls under copyright law? One question is whether processing of neural signals (personal data) without consent of the data subject (thus on the basis of another legitimate basis) can be lawful in any situation. If yes, what situation would that be and under which conditions? For example, can employers (such as schools afraid of hiring pedophiles, or intelligence services screening personnel for infiltrators), insurance providers, or the police (lie detection) ever be allowed to compulsorily process brain signals? (Gasson & Warwick, 2007).
References
Beckert, B., Bluemel, C., Friedewald, M., Thielmann, A. (2008). Converging Technologies and their impact on the Social Sciences and Humanities (CONTECS). An analysis of critical issues and a suggestion for a future research agenda. Retrieved January 4, 2010 from http://www.contecs.fraunhofer.de/images/files/contecs_report_complete.pdf
Berger, T. W. (2007). Introduction. In International Assessment of Research and Development in Brain-Computer Interfaces. Chapter one. Retrieved December 18, 2007, from http://www.wtec.org/bci/BCI-finalreport-10Oct2007-lowres.pdf
European Technology Assessment Group. (2006). Technology Assessment on Converging Technologies. Retrieved January 4, 2010 from http://www.europarl.europa.eu/stoa/publications/studies/stoa183_en.pdf
Friman, O., Luth, T., Volosyak, I. and Graser, A. (2007). Spelling with Steady-State Visually Evoked Potentials. In 3rd International IEEE/EMBS Conference on Neural Engineering. 355 – 357.
Gasson, M. & Warwick, K. (2007). D12.1 Study On Emerging AmI Technologies. FIDIS – Future of Identity in the Information Society. [Scientific Report] Haynes, J-D. (2008). Detecting deception from neuroimaging signals – a data-driven perspective. Trends in Cognitive Science (12) 4, 126-127.
Kern, D. S. & Kumar, R. (2007). Deep Brain Stimulation. The Neurologist (13) 5, 237-252.
Rocco, M.H. & Bainbridge, W.S. (2003). Converging Technologies for Improving Human Performance: Nanotechnology, Biotechnology, Information Technology and Cognitive Science. Kluwer Academic Publishing. Retrieved January 4, 2010 from http://www.wtec.org/ConvergingTechnologies/1/NBIC_report.pdf
Simon, S. (2005). What you don’t know can’t hurt you. Retrieved March 27, 2010, from http://www.brainwavescience.com/LET%20Article.pdf
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