The overall goal of the proposed research is to design, build, and test a miniature, ultra- low-power system of analog chips, suitable for long-term implantation in the brain, and capable of adaptive, real-time decoding of movement intention signals to be used in the control of prosthetic limbs in animal models, and eventually applied in the treatment of paralyzed human patients. When the system is functional, it will allow operation on a small implanted 100mAh with 1000 wireless recharges for 10 years, minimize chronic heat dissipation in the brain due to mW-level operation, allow large multi-electrode wireless cortical prosthetic systems to scale from our 100-electrode system, and minimize the risk of infection to the patient. The system will be built with ultra-low-power analog electronic techniques developed in the Sarpeshkar lab at MIT (PI's lab). Such techniques recently reduced power consumption in a cochlear implant processor by more than an order of magnitude. Analog architectures can be made robust, and programmable like digital systems and also made to have the capability to learn and adapt. The system will be tested with floating microelectrode arrays purchased from Microprobe Inc., packaged with electronic chips in a biocompatible parylene-based packaging process developed in the Tai lab (second co-investigator's lab) and tested in rodents and monkeys in the Andersen lab at Caltech (first co-investigator's lab). Extensive prior research in the Andersen lab has shown that such cortical prosthetics perform very well in decoding the intention of monkeys to move and in translating that intention to successfully control an artificial motor output. Because the system will be reconfigurable and consist of a programmable digital unit external to the scalp and a programmable analog system implanted between the scalp and skull that communicate with each other, it will be capable of functioning as a general-purpose chronic wireless brain-machine interface (BMI). This BMI will be able to report wireless raw digitized neural data, local-field-potential signals, pulsatile action-potential signals, or motor outputs, and be capable of being programmed wirelessly from the outside. It will thus also be widely useful to all experimental neuroscientists and neurologists.
The project `Low Power Analog Electronics for a Cortical Prosthetic'will create an ultra-low-power, chronic, wireless, small brain-machine interface (BMI) that is useful for curing and studying various neural disorders including paralysis and epilepsy. It will also enable portable large-scale long-term instrumentation and monitoring of the brain in experimental neuroscience in a wireless fashion.
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| Rapoport, Benjamin I; Kedzierski, Jakub T; Sarpeshkar, Rahul (2012) A glucose fuel cell for implantable brain-machine interfaces. PLoS One 7:e38436 |
| Arfin, Scott K; Sarpeshkar, Rahul (2012) An energy-efficient, adiabatic electrode stimulator with inductive energy recycling and feedback current regulation. IEEE Trans Biomed Circuits Syst 6:1-14 |
| Arfin, Scott K; Long, Michael A; Fee, Michale S et al. (2009) Wireless neural stimulation in freely behaving small animals. J Neurophysiol 102:598-605 |
| Rapoport, Benjamin I; Wattanapanitch, Woradorn; Penagos, Hector L et al. (2009) A biomimetic adaptive algorithm and low-power architecture for implantable neural decoders. Conf Proc IEEE Eng Med Biol Soc 2009:4214-7 |
