Inicio » Charlas Profesores Invitados » Evento : “Escuchando a las neuronas : La próxima generación de interfaces neurales”

Evento : “Escuchando a las neuronas : La próxima generación de interfaces neurales”

Jueves 22 de marzo de 17:30 a 19:30hs, Salón Azul (piso 5, salón 502) – Facultad de Ingeniería, J. Herrera y Reissig 565

El Instituto de Ingeniería Eléctrica de la Facultad de Ingeniería de la Universidad de la República invita al siguiente evento : “Escuchando a las neuronas : La próxima generación de interfaces neurales”. El mismo constará de dos charlas a cargo de destacados expertos internacionales en el área de interfaces neurales. A continuación el resumen de las charlas y la biografía de los conferencistas. El evento cuenta con el apoyo de IEEE-CAS.

Millimetre-scale implantable brain machine interfaces

Abstract : Being able to control devices with our thoughts is a concept that has for long captured the imagination. Neural Interfaces or Brain Machine Interfaces (BMIs) are devices that aim to do precisely this. Next generation devices will be distributed like the brain itself. It is currently estimated that if we could record electrical activity simultaneously from between 1,000 and 10,000 neurons, this would enable useful prosthetic control (e.g. of a prosthetic arm). However, rather than relying on a single, highly complex implant and trying to integrate more and more channels in this high density interface (the current paradigm) an emerging trend, and topic of this special session, is to develop a simpler, smaller, safer, and well-engineered primitive, and deploy multiple such devices. It is essential these are each compact, autonomous, calibration-free, and completely wireless. It is envisaged that each device will be mm-scale, and be capable of monitoring fewer sites, but also perform real-time signal processing. This processing will achieve data reduction to wirelessly communicate only useful information, rather than raw data, which can most often be just noise and of no use. Making these underlying devices “simpler” will overcome many of the common challenges that are associated with scaling of neural interfaces, for example, wires breaking, biocompatibility of the packaging, thermal dissipation and yield. By distributing tens to hundreds of these in a “network” of neural interfaces, many of the desirable features of distributed networks come into play; for example, redundancy and robustness to single component failure. Such devices will communicate the neural “control signals” to an external prosthetic device. These can then, for example, be used for: an amputee to control a robotic prosthesis; a paraplegic to control a mobility aid; or an individual with locked-in syndrome to communicate with the outside world.

Biography : Timothy Constandinou received the B.Eng. and Ph.D. degrees in electronic engineering from Imperial College London, in 2001 and 2005, respectively. He is currently a Reader of Neural Microsystems within the Circuits and Systems Group, Department of Electrical and Electronic Engineering at Imperial College London and also the Deputy Director of the Centre for Bio-Inspired Technology. His current research interests include neural microsystems, neural prosthetics, brain machine interfaces, implantable devices, and low-power microelectronics. He leads the Next Generation Neural Interfaces research group at Imperial. The group utilises integrated circuit and microsystem technologies to create advanced neural interfaces that enable new scientific and prosthetic applications. He is a senior member of the IEEE, fellow of the IET, a chartered engineer, and member of the IoP. Within the IEEE, he serves on several committees/panels, regularly contributing to conference organization, technical activities, and governance. He currently serves on the IEEE Circuits & Systems Society (CASS) Board of Governors for the term 2017-19, is associate editor of IEEE Transactions on Biomedical Circuits & Systems (TBioCAS), chairs the IEEE CASS Sensory Systems Technical Committee, and serves on the IEEE BRAIN Initiative Steering Committee and IEEE CASS BioCAS Technical Committee. He was the technical program Co-Chair of the 2010, 2011 and 2018 IEEE BioCAS conferences, General Chair of the BrainCAS 2016 and NeuroCAS 2018 workshops, Special Session Co-Chair of the 2017 IEEE ISCAS Conference, and Demonstrations Co-Chair of the 2017 BioCAS Conference.

Dynamic range considerations for neural recording channels

Abstract : Neural readout microelectronic interfaces are essential in implanted central nerve system prostheses aimed for brain-machine interfaces, the amelioration of disease effects, or the development of robotic mechanisms for the restitution/rehabilitation of abilities lost after injury or disease. Neural signals which can be recorded and used as biomarkers of the brain activity include local field potentials (LFPs) and action potentials (APs). They exhibit small amplitude (typically, below 1mV for LFPs and 100mV for APs) and narrow band characteristics (0.5-200Hz for LFPs and 200Hz-7kHz for APs). A priori, these signals can be easily digitized with low-to-medium resolution ADCs, thus paving the way for neural prostheses with small area and power consumptions. However, along with the biomarkers, strong in band artifacts, which can be much larger that the signals of interest, may contaminate the recording or even preclude it altogether if the front-end saturates. Different causes can be at the origin of artifacts; for instance, they can be motion related or generated by electrical stimulations close to the recording sites. Coping with these large artifacts would demand for high dynamic range (of about 75dB) front-ends and data converters with large effective resolutions (beyond 13-14 bits). However, recent proposals for artifact-aware analog front ends have demonstrated that modest ADCs can still be used for neural recording even in the presence of artifacts. This work reviews these proposals and also presents state-of-the-art techniques for the suppression of differential and common-mode artifacts from neural recordings.

Biography : Manuel Delgado-Restituto (IEEE M’96–SM’12) received the M.S. degree in physics and the Ph.D. degree (with honors) in physics-electronics from the University of Seville, Seville, Spain, in 1988 and 1996, respectively. He is a Senior Research Scientist of the Institute of Microelectronics of Seville (IMSE-CNM/CSIC), Spain, where he currently heads a research group on low-power medical microelectronics and works in the design of silicon microsystems to understanding biological neural systems, the development of neural prostheses and brain-machine interfaces, the implementation of wireless Body Area Network transceivers and the realization of RFID transponders with biomedical sensing capabilities.He has coauthored two books; more than 20 chapters in contributed books, including original tutorials on chaotic integrated circuits, design of data converters, and chips for bioengineering and neuroscience; and some 150 articles in peer-review specialized publications. Dr. Delgado-Restituto served as an Associate Editor for the IEEE TRANSACTIONS on CIRCUITS AND SYSTEMS—II: EXPRESS BRIEFS (2006–2007) and for the IEEE TRANSACTIONS on CIRCUITS AND SYSTEMS—I: REGULAR PAPERS (2008–2011). He served as Deputy Editor-in-Chief (2011–2013) and as Editor-in-Chief (2014–2015) for the IEEE JOURNAL on EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS. Currently, he is Vice President for Publications of IEEE CAS (2016–). He is in the committee of different international conferences and has served as technical program chair in different international IEEE conferences.

Afiche del evento