Brain technology
Brain technology, or self-learning know-how systems, defines a technology that employs latest findings in neuroscience. [see also neuro implants] The term was first introduced by the Artificial Intelligence Laboratory in Zurich, Switzerland, in the context of the Roboy project.<ref>NZZ- Die Zangengeburt eines möglichen Stammvaters. Website Neue Zürcher Zeitung. Seen 16. August 2013.</ref> Brain Technology can be employed in robots,<ref>Official Homepage Roboy Archived 2013-08-03 at the Wayback Machine. Website Roboy. Seen 16. August 2013.</ref> know-how management systems<ref>Official Homepage Starmind. Website Starmind. Seen 16. August 2013.</ref> and any other application with self-learning capabilities. In particular, Brain Technology applications allow the visualization of the underlying learning architecture often coined as “know-how maps”.
Research and applications
The first demonstrations of BC<ref name=DARPAfunded>Miranda, Robbin A.; Casebeer, William D.; Hein, Amy M.; Judy, Jack W.; Krotkov, Eric P.; Laabs, Tracy L.; Manzo, Justin E.; Pankratz, Kent G.; Pratt, Gill A.; Sanchez, Justin C.; Weber, Douglas J.; Wheeler, Tracey L.; Ling, Geoffrey S.F. (2015-04-15). "DARPA-funded efforts in the development of novel brain–computer interface technologies". Journal of Neuroscience Methods. 244: 52–67. doi:10.1016/j.jneumeth.2014.07.019. ISSN 0165-0270. PMID 25107852.</ref> in humans and animals took place in the 1960s when Grey Walter demonstrated use of non-invasively recorded encephalogram (EEG) signals from a human subject to control a slide projector (Graimann et al., 2010).
Soon after Jacques J. Vidal coined the term brain–computer interface (BCI)<ref name=DARPAfunded/> in 1971, the Defense Advanced Research Projects Agency (DARPA) first starting funding brain–computer interface research and has since funded several brain–computer interface projects. That market is expected to reach a value of $1.72 billion by 2022.<ref>"Brain Computer Interface Market Size Report, 2020-2027". www.grandviewresearch.com. Retrieved 2021-04-14.</ref> Brain–computer interfaces record brain activity, transmit the information out of the body, signal-process the data via algorithms, and convert them into command control signals.
In 2012, a landmark study<ref>May 16; Orenstein 401-863-1862, 2012 Media contact: David. "People with paralysis control robotic arms using brain–computer interface". news.brown.edu. Retrieved 2021-04-14.{{cite web}}: CS1 maint: numeric names: authors list (link)</ref> in Nature, led by pioneer Leigh Hochberg, MD, PhD, demonstrated that two people with tetraplegia were able to control robotic arms through thought when connected to the BrainGate neural interface system. The two participants were able to reach for and grasp objects in three-dimensional space, and one participant used the system to serve herself coffee for the first time since becoming paralyzed nearly 15 years prior.
And in October 2020, two patients were able to wirelessly control an operating system to text, email, shop and bank using direct thought through the Stentrode brain computer interface (Journal of NeuroInterventional Surgery) in a study led by Thomas Oxley. This was the first time a brain–computer interface was implanted via the patient’s blood vessels, eliminating the need for open brain surgery.
Currently a number of groups are exploring a range of experimental devices using brain–computer interfaces, which have the potential to fundamentally change the way of life for patients with paralysis and a wide range of neurological disorders. These include: as Elon Musk, Facebook, and the University of California in San Francisco.<ref>"The Machine That Reads Your Mind (Kinda) and Talks (Sorta)". Wired. ISSN 1059-1028. Retrieved 2021-04-14.</ref> The systems This technology is also being explored as a neuromodulation device and may ultimately help diagnose and treat a range of brain pathologies, such as epilepsy and Parkinson’s disease
