Automated Distributed Element Model Generation for Neural Interface Co-Design

F. N.U. Tala; Mehdi Bandali; Benjamin C. Johnson

Automated Distributed Element Model Generation for Neural Interface Co-Design

F. N.U. Tala, Mehdi Bandali, Benjamin C. Johnson

Electrical Engineering Department

Boise State University

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

We present a scripted distributed element modeling framework to enable process-portable co-design of neural recording and stimulation circuits and other applications that require co-design with an electrode-electrolyte interface. Using distributed elements enables designers to simulate the spatial voltage and current profiles in tissue to determine key parameters such as stimulator voltage headroom, stimulation artifact, and charge-balance. Designers specify 2D or 3D physical parameters of the electrode configuration in MATLAB, which in turn generates a netlist in Cadence Virtuoso for simulation with circuitry. Using this framework, we show that time-domain artifact cancellation techniques outperform frequency-domain techniques for concurrent neural recording and stimulation.

Original language	American English
Title of host publication	2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS)
State	Published - 1 Jan 2020

Keywords

Integrated circuit modeling
electrode interface
electrodes
neural recording
neural stimulation
neuromodulation

EGS Disciplines

Electrical and Computer Engineering

Access to Document

https://doi.org/10.1109/MWSCAS48704.2020.9184671

Cite this

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title = "Automated Distributed Element Model Generation for Neural Interface Co-Design",

abstract = " We present a scripted distributed element modeling framework to enable process-portable co-design of neural recording and stimulation circuits and other applications that require co-design with an electrode-electrolyte interface. Using distributed elements enables designers to simulate the spatial voltage and current profiles in tissue to determine key parameters such as stimulator voltage headroom, stimulation artifact, and charge-balance. Designers specify 2D or 3D physical parameters of the electrode configuration in MATLAB, which in turn generates a netlist in Cadence Virtuoso for simulation with circuitry. Using this framework, we show that time-domain artifact cancellation techniques outperform frequency-domain techniques for concurrent neural recording and stimulation.",

keywords = "Integrated circuit modeling, electrode interface, electrodes, neural recording, neural stimulation, neuromodulation",

author = "Tala, {F. N.U.} and Mehdi Bandali and Johnson, {Benjamin C.}",

year = "2020",

month = jan,

day = "1",

language = "American English",

booktitle = "2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS)",

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T1 - Automated Distributed Element Model Generation for Neural Interface Co-Design

AU - Tala, F. N.U.

AU - Bandali, Mehdi

AU - Johnson, Benjamin C.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - We present a scripted distributed element modeling framework to enable process-portable co-design of neural recording and stimulation circuits and other applications that require co-design with an electrode-electrolyte interface. Using distributed elements enables designers to simulate the spatial voltage and current profiles in tissue to determine key parameters such as stimulator voltage headroom, stimulation artifact, and charge-balance. Designers specify 2D or 3D physical parameters of the electrode configuration in MATLAB, which in turn generates a netlist in Cadence Virtuoso for simulation with circuitry. Using this framework, we show that time-domain artifact cancellation techniques outperform frequency-domain techniques for concurrent neural recording and stimulation.

AB - We present a scripted distributed element modeling framework to enable process-portable co-design of neural recording and stimulation circuits and other applications that require co-design with an electrode-electrolyte interface. Using distributed elements enables designers to simulate the spatial voltage and current profiles in tissue to determine key parameters such as stimulator voltage headroom, stimulation artifact, and charge-balance. Designers specify 2D or 3D physical parameters of the electrode configuration in MATLAB, which in turn generates a netlist in Cadence Virtuoso for simulation with circuitry. Using this framework, we show that time-domain artifact cancellation techniques outperform frequency-domain techniques for concurrent neural recording and stimulation.

KW - Integrated circuit modeling

KW - electrode interface

KW - electrodes

KW - neural recording

KW - neural stimulation

KW - neuromodulation

UR - https://scholarworks.boisestate.edu/electrical_facpubs/507

UR - https://doi.org/10.1109/MWSCAS48704.2020.9184671

M3 - Chapter

BT - 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS)

ER -

Automated Distributed Element Model Generation for Neural Interface Co-Design

Abstract

Keywords

EGS Disciplines

Access to Document

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