The use of multichannel electrode arrays (MEAs) presents a number of practical challenges to experimenters including correctly labelling different recording channel locations and identifying sites that may be non-functional or short-circuited. These challenges are likely to increase as the number of sites used in recording increases.
This paper presents a simple method for assessing MEA integrity based on the observation that physiologically induced signal correlations between nearby channels fall off with distance. Channels that violate this relationship are flagged as being potentially problematic.
The method is able to present to the user a list of potentially faulty channels for further inspection. Underlying problems include non-functional, shorted and mislocalised channels and channels carrying spurious noisy signals unrelated to those on other channels.
COMPARISON WITH EXISTING METHODS
Computational methods which automatically screen MEAs for faulty electrode channels do not appear to exist in the literature. Currently a user would have to examine single channels, or channel pairs, individually, which would be very time-consuming.
Shorted or mislocalised channels may be more prevalent in MEA recordings than users suspect. The paper presents a simple screening method for identifying such channels prior to carrying out spike-sorting.
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