Testing spike detection and sorting algorithms using synthesized noisy spike trains
نویسنده
چکیده
Neural signals recorded by extracellular electrodes (and in particular signals recorded from multielectrode arrays at the bottom of culture dishes) often suffer from low signal: noise ratios. This makes spike detection and sorting of interest. There are many algorithms for detecting and sorting spikes in noise (reviewed in [2]). However, assessing their quality is difficult because one does not normally know the ground truth: that is, where the actual spikes are. Wood et al [4] report over 20% errors using semiautomated spike sorting.
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تاریخ انتشار 2006