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IEEE Trans Biomed Eng. 2004 Jun;51(6):912-8.

On the variability of manual spike sorting.

Author information

1
Department of Computer Science, Brown University, Providence, RI 02912, USA. fwood@cs.brown.edu

Abstract

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.

PMID:
15188858
DOI:
10.1109/TBME.2004.826677
[Indexed for MEDLINE]
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