The development of advanced neuroprosthetic systems and brain-machine interfaces for high-capacity, real-time, bi-directional communication with the nervous system is a major challenge to the emerging neural engineering discipline. While recent advances in the fabrication of high-density microelectrode arrays (HDMEAs) for multiunit recording and stimulation have triggered numerous neurobiological discoveries, the resulting large data throughput and the variability of cortical responses over repeated trials preclude the ability to design a wireless, adaptive, fully implantable large-scale interface to the cortex. This severely limits the feasibility and space of experimental paradigms needed to improve our understanding of the nervous system functionality and characterize cortical responses in freely behaving subjects interacting naturally with their surroundings. The objective of this project is to develop a wireless interface to the cortex capable of processing simultaneously recorded neural signalsfrom 64 electrode channels in real time. The project has 3 aims: 1. Develop advanced signal processing algorithms for sensing and decoding neuronal response properties from distributed intra-cortical neural activity: 1) Optimize our existing signal processing algorithms for hardware implementation to extract the desired neural activity early in the data stream; 2) Develop new algorithms for decoding these responses to characterize the natural behavior of awake, behaving animal models. 2. Design low-power integrated circuits and wireless telemetry for a 64 channel system: 1) Optimize the design of a low power Neural Interface Node (NIN) module to feature wireless communication and powering capability for subcutaneous implantation; 2) Design and fabricate an extracranial Manager Interface Module (MIM) to permit: a) wireless powering and data exchange with up to 2 implanted NIN modules; b) wireless bidirectional exchange of data and control with a central base station. 3. Demonstrate the system functionality in vitro and vivo: 1) Build a 32 channel system and test its performance in vitro in retinal slices and in vivo in awake behaving rodents; 2) Demonstrate the real time functionality of a 64 channel system in vitro and explore its feasibility in vivo; 3) Optimize the entire system design, and benchmark it against a commercial 64 channel wired data acquisition system.
This project seeks to develop a wireless electronic microsystem to be implanted in the rat brain to continuously monitor neural signals when the rat is freely behaving in an open environment. This system will help understand how brain cells process information. This will help design assistive technology for people with severe paralysis. ? ?
|Oweiss, Karim G; Badreldin, Islam S (2015) Neuroplasticity subserving the operation of brain-machine interfaces. Neurobiol Dis 83:161-71|
|Eleryan, Ahmed; Vaidya, Mukta; Southerland, Joshua et al. (2014) Tracking single units in chronic, large scale, neural recordings for brain machine interface applications. Front Neuroeng 7:23|
|Byunghun Lee; Kiani, Mehdi; Ghovanloo, Maysam (2014) A smart homecage system with 3D tracking for long-term behavioral experiments. Conf Proc IEEE Eng Med Biol Soc 2014:2016-9|
|Aghagolzadeh, Mehdi; Mohebi, Ali; Oweiss, Karim G (2014) Sorting and tracking neuronal spikes via simple thresholding. IEEE Trans Neural Syst Rehabil Eng 22:858-69|
|Lee, Hyung-Min; Ghovanloo, Maysam (2013) A high frequency active voltage doubler in standard CMOS using offset-controlled comparators for inductive power transmission. IEEE Trans Biomed Circuits Syst 7:213-24|
|Lee, Seung Bae; Yin, Ming; Manns, Joseph R et al. (2013) A wideband dual-antenna receiver for wireless recording from animals behaving in large arenas. IEEE Trans Biomed Eng 60:1993-2004|
|Daly, John; Liu, Jianbo; Aghagolzadeh, Mehdi et al. (2012) Optimal space-time precoding of artificial sensory feedback through mutichannel microstimulation in bi-directional brain-machine interfaces. J Neural Eng 9:065004|
|Kwon, Ki Yong; Eldawlatly, Seif; Oweiss, Karim (2012) NeuroQuest: a comprehensive analysis tool for extracellular neural ensemble recordings. J Neurosci Methods 204:189-201|
|Kiani, Mehdi; Ghovanloo, Maysam (2012) A figure-of-merit for design of high performance inductive power transmission links for implantable microelectronic devices. Conf Proc IEEE Eng Med Biol Soc 2012:847-50|
|Lee, Hyung-Min; Ghovanloo, Maysam (2012) An Adaptive Reconfigurable Active Voltage Doubler/Rectifier for Extended-Range Inductive Power Transmission. IEEE Trans Circuits Syst II Express Briefs :286-288|
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