On the variability of manual spike sorting
Wood, F.; Black, M.J.; Vargas-Irwin, C.; Fellows, M.; Donoghue, J.P.
Biomedical Engineering, IEEE Transactions on
Volume 51, Issue 6, June 2004 Page(s):912 - 918
Digital Object Identifier   10.1109/TBME.2004.826677
Summary:The analysis of action potentials, or "spikes," is central to systems neuroscience research. Spikes are typically identified from raw waveforms manually for off-line analysis or automatically by human-configured algorithms for on-line applications. The variability of manual spike "sorting" is studied and its implications for neural prostheses discussed. Waveforms were recorded using a micro-electrode array and were used to construct a statistically similar synthetic dataset. Results showed wide variability in the number of neurons and spikes detected in real data. Additionally, average error rates of 23% false positive and 30% false negative were found for synthetic data.

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