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A low-cost, scalable, current-sensing digital headstage for high channel count μECoG.

Publication ,  Journal Article
Trumpis, M; Insanally, M; Zou, J; Elsharif, A; Ghomashchi, A; Sertac Artan, N; Froemke, RC; Viventi, J
Published in: Journal of neural engineering
April 2017

High channel count electrode arrays allow for the monitoring of large-scale neural activity at high spatial resolution. Implantable arrays featuring many recording sites require compact, high bandwidth front-end electronics. In the present study, we investigated the use of a small, light weight, and low cost digital current-sensing integrated circuit for acquiring cortical surface signals from a 61-channel micro-electrocorticographic (μECoG) array.We recorded both acute and chronic μECoG signal from rat auditory cortex using our novel digital current-sensing headstage. For direct comparison, separate recordings were made in the same anesthetized preparations using an analog voltage headstage. A model of electrode impedance explained the transformation between current- and voltage-sensed signals, and was used to reconstruct cortical potential. We evaluated the digital headstage using several metrics of the baseline and response signals.The digital current headstage recorded neural signal with similar spatiotemporal statistics and auditory frequency tuning compared to the voltage signal. The signal-to-noise ratio of auditory evoked responses (AERs) was significantly stronger in the current signal. Stimulus decoding based on true and reconstructed voltage signals were not significantly different. Recordings from an implanted system showed AERs that were detectable and decodable for 52 d. The reconstruction filter mitigated the thermal current noise of the electrode impedance and enhanced overall SNR.We developed and validated a novel approach to headstage acquisition that used current-input circuits to independently digitize 61 channels of μECoG measurements of the cortical field. These low-cost circuits, intended to measure photo-currents in digital imaging, not only provided a signal representing the local cortical field with virtually the same sensitivity and specificity as a traditional voltage headstage but also resulted in a small, light headstage that can easily be scaled to record from hundreds of channels.

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Published In

Journal of neural engineering

DOI

EISSN

1741-2552

ISSN

1741-2560

Publication Date

April 2017

Volume

14

Issue

2

Start / End Page

026009

Related Subject Headings

  • Signal Processing, Computer-Assisted
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Rats, Sprague-Dawley
  • Rats
  • Microelectrodes
  • Microarray Analysis
  • Male
  • Feedback
  • Equipment Failure Analysis
 

Citation

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Trumpis, M., Insanally, M., Zou, J., Elsharif, A., Ghomashchi, A., Sertac Artan, N., … Viventi, J. (2017). A low-cost, scalable, current-sensing digital headstage for high channel count μECoG. Journal of Neural Engineering, 14(2), 026009. https://doi.org/10.1088/1741-2552/aa5a82
Trumpis, Michael, Michele Insanally, Jialin Zou, Ashraf Elsharif, Ali Ghomashchi, N. Sertac Artan, Robert C. Froemke, and Jonathan Viventi. “A low-cost, scalable, current-sensing digital headstage for high channel count μECoG.Journal of Neural Engineering 14, no. 2 (April 2017): 026009. https://doi.org/10.1088/1741-2552/aa5a82.
Trumpis M, Insanally M, Zou J, Elsharif A, Ghomashchi A, Sertac Artan N, et al. A low-cost, scalable, current-sensing digital headstage for high channel count μECoG. Journal of neural engineering. 2017 Apr;14(2):026009.
Trumpis, Michael, et al. “A low-cost, scalable, current-sensing digital headstage for high channel count μECoG.Journal of Neural Engineering, vol. 14, no. 2, Apr. 2017, p. 026009. Epmc, doi:10.1088/1741-2552/aa5a82.
Trumpis M, Insanally M, Zou J, Elsharif A, Ghomashchi A, Sertac Artan N, Froemke RC, Viventi J. A low-cost, scalable, current-sensing digital headstage for high channel count μECoG. Journal of neural engineering. 2017 Apr;14(2):026009.
Journal cover image

Published In

Journal of neural engineering

DOI

EISSN

1741-2552

ISSN

1741-2560

Publication Date

April 2017

Volume

14

Issue

2

Start / End Page

026009

Related Subject Headings

  • Signal Processing, Computer-Assisted
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Rats, Sprague-Dawley
  • Rats
  • Microelectrodes
  • Microarray Analysis
  • Male
  • Feedback
  • Equipment Failure Analysis