BibTex format

author = {Luo, J and Firflionis, D and Turnball, M and Xu, W and Walsh, D and Escobedo-Cousin, E and Soltan, A and Ramezani, R and Liu, Y and Bailey, R and O'Neill, A and Donaldson, N and Constandinou, T and Jackson, A and Degenaar, P},
doi = {10.1109/TBME.2020.2973934},
journal = {IEEE Transactions on Biomedical Engineering},
pages = {3004--3015},
title = {The neural engine: a reprogrammable low power platform for closed-loop optogenetics},
url = {},
volume = {67},
year = {2020}

RIS format (EndNote, RefMan)

AB - Brain-machine Interfaces (BMI) hold great potential for treating neurological disorders such as epilepsy. Technological progress is allowing for a shift from open-loop, pacemaker-class, intervention towards fully closed-loop neural control systems. Low power programmable processing systems are therefore required which can operate within the thermal window of 2° C for medical implants and maintain long battery life. In this work, we developed a low power neural engine with an optimized set of algorithms which can operate under a power cycling domain. By integrating with custom designed brain implant chip, we have demonstrated the operational applicability to the closed-loop modulating neural activities in in-vitro brain tissues: the local field potentials can be modulated at required central frequency ranges. Also, both a freely-moving non-human primate (24-hour) and a rodent (1-hour) in-vivo experiments were performed to show system long-term recording performance. The overall system consumes only 2.93mA during operation with a biological recording frequency 50Hz sampling rate (the lifespan is approximately 56 hours). A library of algorithms has been implemented in terms of detection, suppression and optical intervention to allow for exploratory applications in different neurological disorders. Thermal experiments demonstrated that operation creates minimal heating as well as battery performance exceeding 24 hours on a freely moving rodent. Therefore, this technology shows great capabilities for both neuroscience in-vitro/in-vivo applications and medical implantable processing units.
AU - Luo,J
AU - Firflionis,D
AU - Turnball,M
AU - Xu,W
AU - Walsh,D
AU - Escobedo-Cousin,E
AU - Soltan,A
AU - Ramezani,R
AU - Liu,Y
AU - Bailey,R
AU - O'Neill,A
AU - Donaldson,N
AU - Constandinou,T
AU - Jackson,A
AU - Degenaar,P
DO - 10.1109/TBME.2020.2973934
EP - 3015
PY - 2020///
SN - 0018-9294
SP - 3004
TI - The neural engine: a reprogrammable low power platform for closed-loop optogenetics
T2 - IEEE Transactions on Biomedical Engineering
UR -
UR -
UR -
VL - 67
ER -