ArticlebioRxiv : the preprint server for biology2025
A Semi-Automated MEA Spike sorting (SAMS) method for high throughput assessment of cultured neurons.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Neurons derived from human pluripotent stem cells (hPSCs) are valuable models for studying brain development and developing therapies for brain disorders. Evaluating human-derived neurons requires assessing their electrical activity, which can be achieved using multi-electrode arrays (MEAs) for extracellular recordings. Because each electrode channel generally detects activity from multiple neurons, resolving the activity of single neurons requires a process called spike sorting. However, currently available spike sorting methods are not optimized for the analysis of hPSC-derived neurons, and require complex workflows and time-consuming manual intervention. Here, we introduce a Highlights: SAMS is designed and optimized for high throughput analysis of hPSC-derived neurons.SAMS is more efficient and accurate compared to recommended spike-sorting software.SAMS resolves phenotypic differences previously not observed without spike sorting.SAMS is an open-source software.
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