TDT OpenSorter 2.2

TDT OpenSorter is a stand-alone software package for sorting neural spike data. It offers powerful sorting methods such as Bayesian expectation-maximization, k-means, and closest-centers algorithms, as well as manual cluster cutting and waveform selection. It supports manual, semi-automated and fully automated processing, and can be used to sort individual channels, batches of datasets, or pooled supersets across blocks or channels.

OpenSorter is a stand-alone package for sorting neural spike data and is the latest addition to TDT’s OpenEx software suite. OpenSorter offers a number of powerful sorting methods including Bayesian expectation-maximization, k-means, and closest-centers algorithms in addition to manual cluster cutting and waveform selection.
Capabilities include manual, semi-automated, and fully automated processing. Spikes can be sorted as individual channels, batched for fast processing of groups of datasets, or combined across blocks or channels and sorted as a pooled superset.