Title

Predicting neural recording performance of implantable electrodes

RIS ID

135395

Publication Details

Harris, A. R., Allitt, B. J. & Paolini, A. G. (2019). Predicting neural recording performance of implantable electrodes. Analyst, 144 (9), 2973-2983.

Abstract

Recordings of neural activity can be used to aid communication, control prosthetic devices or alleviatedisease symptoms. Chronic recordings require a high signal-to-noise ratio that is stable for years. Currentcortical devices generally fail within months to years after implantation. Development of novel devices toincrease lifetime requires valid testing protocols and a knowledge of the critical parameters controllingelectrophysiological performance. Here we present electrochemical and electrophysiological protocolsfor assessing implantable electrodes. Biological noise from neural recording has significant impact on signal-to-noise ratio. A recently developed surgical approach was utilised to reduce biological noise. This allowed correlation of electrochemical and electrophysiological behaviour. The impedance versus frequency of modified electrodes was non-linear. It was found that impedance at low frequencies was astronger predictor of electrophysiological performance than the typically reported impedance at 1 kHz.Low frequency impedance is a function of electrode area, and a strong correlation of electrode area with electrophysiological response was also seen. Use of these standardised testing protocols will allow future devices to be compared before transfer to preclinical and clinical trials.

Grant Number

ARC/CE0561616, ARC/CE140100012

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