Alpha-Sort is an offline spike sorter. Spikes are projected on a two dimensional Principal Component space, and are then represented by their projections on this space. Alpha-Sort has been developed for electrophysiological application, analyzing activity recorded from the nervous system using extracellular microelectrodes.
NEW VERSION
A Demo version is avilable for Download. | |
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| Features | - Statistical functions for monitoring the quality of a given classification.
- Data visualization.
- Built in Tools for defining Principal Components especially tailored for given data sets. New
- Visual comparison of online classification on the Principal Components space.
- Additional features. New
| Statistical functions for monitoring the quality of a given classification | - Time interval histograms (TIHs) and Cross interval histograms (CIHs)
- Firing rate plots
- Comparative statistics of spike shapes
| Data visualization | - Actual spike shapes or projections on the PC space can be viewed as either a series of snapshots in time, or as a movie, enabling an overview of the entire data set.
- Spike shapes from different classes can be superimposed for monitoring the goodness of a given class definition.
- Ability to view the actual spike shapes of selected spike projections, or conversely, to view the location of projection for selected spike shapes.
| Additional features | - Dynamic tracking of the spike projections, enabling reliable classification of non stationary data.
- User defined threshold level for signal to noise level of spikes, thus excluding noisy spikes or electrical artifacts from>classification
- Analysis of temporal aspects of spike timing within and between classes. Among these tools are Time Interval Histograms, Cross Interval Histograms, and Firing Rates.
- Analysis of waveforms of spikes within and between classes. These include direct comparison of spikes shapes, as well as of cluster averages.
- Overview of the entire data. Cluster structure and spike waveforms as a function of time can be seen as a movie or a series of snapshots.
- ALPHASORT allows for merging of any digital event data in the NDA format (MATLAB® or Text) with the classified spikes, allowing for further analysis in other applications (i.e., NeuroExplorer).
| Built in Tools for defining Principal Components especially tailored for given data sets | Alpha-Sort allows users to define their own Principal Components (PCs). This feature enables designing PCs specifically tailored for given experimental setups (i.e., different brain structures, preparations, filtering, electrode types, etc ..).
| | Visual comparison of online classification on the PC space. | Alpha-Sort enables visualization of online classified data on the PC component space, thus allowing for a more reliable and simple classification of the offline data.
| | Download | You can easily Download
a demo version and our software department will be happy to assist you regarding questions on how to use your data
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Original shape of individual spike (blue) and its approximation by Principal Components(red).
Original shape of individual spike (blue) and its approximation by Principal Components(red).
Firing rates of spikes in 3 different polygons
9 Snapshots of spike projections as they evolve in time.
Shape matches between the three cluster averages
The main classification interface. Three clusters with polygons around them are shown
Time interval histograms of spikes from three clusters (class 0 are the unclassified spikes).
A single frame from the ‘spike shape movie’. The black traces are the unclassified signals. | | | | | | | |
| | CAT | | Description | | Remarks | | | 407-000008-00 | | Alpha-Sort | | |
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