Optogenetics in silicon: a neural processor for predicting optically active neural networks

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Title: Optogenetics in silicon: a neural processor for predicting optically active neural networks
Authors: Luo, J
Nikolic, K
Evans, BD
Dong, N
Sun, X
Andras, P
Yakovlev, A
Degenaar, P
Item Type: Journal Article
Abstract: We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin–Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon hardware. Our architecture consists of a Field Programmable Gated Array (FPGA) with a custom-built computing data-path, a separate data management system and a memory approach based router. Advancements over previous work include the incorporation of short and long-term calcium and light-dependent ion channels in reconfigurable hardware. Also, the developed processor is computationally efficient, requiring only 0.03 ms processing time per sub-frame for a single neuron and 9.7 ms for a fully connected network of 500 neurons with a given FPGA frequency of 56.7 MHz. It can therefore be utilized for exploration of closed loop processing and tuning of biologically realistic optogenetic circuitry.
Issue Date: 17-Aug-2016
Date of Acceptance: 27-Apr-2016
URI: http://hdl.handle.net/10044/1/39654
DOI: http://dx.doi.org/10.1109/TBCAS.2016.2571339
ISSN: 1940-9990
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Start Page: 15
End Page: 27
Journal / Book Title: IEEE Transactions on Biomedical Circuits and Systems
Volume: 11
Issue: 1
Copyright Statement: © 2016 The Authors. This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
Sponsor/Funder: Biotechnology and Biological Sciences Research Council (BBSRC)
Biotechnology and Biological Sciences Research Cou
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: BB/L018268/1
4020012831
EP/N002474/1
Keywords: Electrical & Electronic Engineering
0903 Biomedical Engineering
0906 Electrical And Electronic Engineering
Publication Status: Published
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



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