Skip Navigation Links

Speaker Details

 
 

print  
   Biography
 
Nitish V. Thakor is a Professor of Biomedical Engineering, Electrical and Computer Engineering and at Johns Hopkins University since 1983. He is also the Founding Director of Singapore Institute for Neurotechnology at the National University of Singapore (2012-2018) and currently the Professor of Biomedical Engineering at the National University of Singapore. Prof. Thakor’s technical expertise is in the field of Neuroengineering, where he has pioneered many technologies for brain monitoring, implantable neurotechnologies, neuroprosthesis and brain-machine interface. He has published over 395 refereed journal papers (H Index 81 with more than 27000 citations). He has received 16 US and international patents and co-founded 3 active companies. He was previously the Editor in Chief of IEEE Transactions on Neural Systems and Rehabilitation Engineering from 2006-2011, and since 2012 the EIC of Medical and Biological Engineering and Computing (Springr/Nature). He is the Editor of an upcoming authoritative reference Handbook of Neuroengineering to be published by Springer Press. Prof. Thakor is a recipient of the Technical Achievement Award (Neuroengineering) as well as the Academic Career Award from the IEEE Engineering in Medicine and Biology Society. He received a Research Career Development Award from the National Institutes of Health and a Presidential Young Investigator Award from the National Science Foundation, and is a Fellow of the American Institute of Medical and Biological Engineering, Life Fellow of IEEE, Biomedical Engineering Society, and International Federation of Medical and Biological Engineering. He is a recipient of a Distinguished Alumnus Award from Indian Institute of Technology, Bombay, India, and a Centennial Medal from the University of Wisconsin School of Engineering.
 
 
  Abstract
 
Neurotechnologies to Build the Brain Machine Interface (and, Should We?)
Neurotechnologies to Build the Brain Machine Interface (and, Should We?) We are entering an exciting decade of impending revolution in neurotechnologies that have enabled the development of the brain machine interface. How did we get there? What are these technologies, and what technologies made this amazing interface possible? We got to the point of building brain machine interface by both learning sufficiently about the brain and its billions of interconnected neurons, and by mastering the technologies that can connect to or probe the functioning of the neurons. One important step was the development of micro/nano probes that can access the electrical activity of the neurons. The second important step was the microcircuit that can capture these signals and record or transmit them from the brain to the machine. The third step was the methods of decoding the signature of these neurons, whose individual pattern or collective rhythm can now be crudely interpreted to interpret the brain’s intention, such as move the arm. That brings us a lot closer to the commands we can now issue to the machine, whether it is a computer (move a cursor on a computer screen – useful for patients in a locked in syndrome) or move a robotic or prosthetic arm (useful for an amputee) or control a wheelchair (useful to paralyzed patients). From there, a wider range of medical and non-medical applications open up, e.g. rehabilitation of patients with stroke or communication assistance to patients with aphasia (inability to speak). The nonmedical revolution is now just becoming evident, thanks to significant investment in the field by highly successful entrepreneurs and pioneers. They may apply these technologies for applications such as gaming (with their vast commercial potential). Brain-machine interface to control more complex machines, such as humanoid robots to more advanced vehicles such as automobiles and drones seem possible, even though this demonstration right now is at a rudimentary level. But with the relentless progress in the micro/nanoprobes, electronics, and machine learning/Artificial intelligence (AI) approaches, this progress is relentlessly moving in a positive and accelerating direction. So, what does the future hold for the technologies? What other applications may we imagine possible? This is where we may start speculating about both the exciting future directions and the potential pitfalls and roadblocks – technical, societal and even moral. For example, we are on the verge of recording from million neurons (from dozens and hundreds only recently possible. The same AI tools that have brought the revolutionary algorithms to recognize faces with human-like accuracy and computers to beat human grandmasters at chess, can now be applied to decode the symphony of these millions, and some day many-many more neurons. That brings us to applications: clearly the medical applications are the most important driving forces. Ameliorating or treating the effects of stroke, amputation or brain trauma are the first targets. But after that come the harder problems of speech communication and memory restoration. It is not at all clear whether dementia or Alzheimer’s can be treated, but surely these disorders will be attacked directly or indirectly. Non-medically the drivers are the gaming, robotic machinery, autonomous vehicles, and even human-humanoid communication devices. The military side is evident, such as controlling defensive and offensive weapons, communication gears, vehicles and drones. But now new questions arise: what are the emerging and futuristic technologies, how and for what purpose they must be developed? But as importantly, should we develop these technologies, as they also develop ethical and moral question, from risk to the human subject to the potential misuse for unintended and potentially nefarious purposes. The ethics of the human brain-machine interface involves the safety of the subject, but also how it may affect others. While we accept robots that are stronger and faster than us, and machines that can beat us at chess and go games, are we ready to accept superhuman intelligence, or bilateral communication with machines, or even a machine’s ability to influence our brain, mind and emotions?