The neural engine: a reprogrammable low power platform for closed-loop optogenetics
File(s)09006958.pdf (2.39 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
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.
Date Issued
2020-11-01
Date Acceptance
2020-02-06
Citation
IEEE Transactions on Biomedical Engineering, 2020, 67 (11), pp.3004-3015
ISSN
0018-9294
Publisher
Institute of Electrical and Electronics Engineers
Start Page
3004
End Page
3015
Journal / Book Title
IEEE Transactions on Biomedical Engineering
Volume
67
Issue
11
Copyright Statement
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Wellcome Trust
Identifier
https://ieeexplore.ieee.org/document/9006958
Grant Number
BH134389
Subjects
Biomedical Engineering
0801 Artificial Intelligence and Image Processing
0903 Biomedical Engineering
0906 Electrical and Electronic Engineering
Publication Status
Published
Date Publish Online
2020-02-21