2018Unpublished venueOpen access

A Novel µECoG Electrode Interface for Comparison of Local and Common Averaged Referenced Signals

Ashley J. Williams, Michael Trumpis, Brinnae Bent, Chia‐Han Chiang, Jonathan Viventi

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Abstract

Micro-electrocorticography (µECoG) is a minimally invasive neural interface that allows for recording from the surface of the brain with high spatial and temporal resolution [1], [2]. However, discerning multi-unit and local field potential (LFP) activity with potentially highly-correlated signals across a dense µECoG array can be challenging. Here we describe a novel µECoG design to compare the effect of referencing recordings to a local reference electrode and common average referencing (CAR). The filtering effect and the significant increase in signal to noise ratio of the evoked response (ESNR) can be seen after re-referencing for both types of referencing. In a preliminary analysis, re-referencing the µECoG signals can increase recording performance at high contact densities in the auditory cortex. This also provides promising evidence for a versatile in-house fabricated µECoG electrode.

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What this paper is about

Micro-electrocorticography (µECoG) is a minimally invasive neural interface that allows for recording from the surface of the brain with high spatial and temporal resolution [1], [2]. However, discerning multi-unit and local field potential (LFP) activity with potentially highly-correlated signals across a dense µECoG array can be challenging. Here we describe a novel µECoG design to compare the effect of referencing recordings to a local reference electrode and common average referencing (CAR). The filtering effect and the significant increase in signal to noise ratio of the evoked response (ESNR) can be seen after re-referencing for both types of referencing. In a preliminary analysis, re-referencing the µECoG signals can increase recording performance at high contact densities in the auditory cortex. This also provides promising evidence for a versatile in-house fabricated µECoG electrode.

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Available abstract

Micro-electrocorticography (µECoG) is a minimally invasive neural interface that allows for recording from the surface of the brain with high spatial and temporal resolution [1], [2]. However, discerning multi-unit and local field potential (LFP) activity with potentially highly-correlated signals across a dense µECoG array can be challenging. Here we describe a novel µECoG design to compare the effect of referencing recordings to a local reference electrode and common average referencing (CAR). The filtering effect and the significant increase in signal to noise ratio of the evoked response (ESNR) can be seen after re-referencing for both types of referencing. In a preliminary analysis, re-referencing the µECoG signals can increase recording performance at high contact densities in the auditory cortex. This also provides promising evidence for a versatile in-house fabricated µECoG electrode.

Key concepts: Electrocorticography, Local field potential, Computer science, Interface (matter), Brain–computer interface, SIGNAL (programming language), Noise (video), Pattern recognition (psychology)

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