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Published October 15, 2012 | Accepted Version
Journal Article Open

Variability of acute extracellular action potential measurements with multisite silicon probes

Abstract

Device miniaturization technologies have led to significant advances in sensors for extracellular measurements of electrical activity in the brain. Multisite, silicon-based probes containing implantable electrode arrays afford greater coverage of neuronal activity than single electrodes and therefore potentially offer a more complete view of how neuronal ensembles encode information. However, scaling up the number of sites is not sufficient to ensure capture of multiple neurons, as action potential signals from extracellular electrodes may vary due to numerous factors. In order to understand the large-scale recording capabilities and potential limitations of multisite probes, it is important to quantify this variability, and to determine whether certain key device parameters influence the recordings. Here we investigate the effect of four parameters, namely, electrode surface, width of the structural support shafts, shaft number, and position of the recording site relative to the shaft tip. This study employs acutely implanted silicon probes containing up to 64 recording sites, whose performance is evaluated by the metrics of noise, spike amplitude, and spike detection probability. On average, we find no significant effect of device geometry on spike amplitude and detection probability but we find significant differences among individual experiments, with the likelihood of detecting spikes varying by a factor of approximately three across trials.

Additional Information

© 2012 Elsevier B.V. Received 9 April 2012. Received in revised form 31 July 2012. Accepted 4 August 2012. We thank T.J. Blanche for discussions on probe design and recording quality assessment, R.R. Harrison for developing the ASIC used to read out data from the probe, and M.L. Roukes for device fabrication support. Neural probe nanofabrication was carried out at the Kavli Nanoscience Institute at Caltech, and the Nanoelectronics Research Facility at UCLA. We acknowledge support from the Broad Foundations, the Della Martin Fund for Discoveries in Mental Illness, and the NIH (DA-17279 and AG-033954).

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