Overview

Pronounce it [tree day clue] in English.

The primary goal of tridesclous is to provide a toolkit to teach good practices in spike sorting techniques. This tool is now mature and can be used for experimental data.

Authors: Christophe Pouzat and Samuel Garcia

General workflow

Many tools claim to be “automatic” for spike sorting. In tridesclous we don’t, the workflow is:

  1. Construct catalog. This part is automatic but needs carefully chosen parameters. This is more or less the legacy chain of spike sorting = preprocessing+waveform+feature+clustering This can be done with a small subset of the whole dataset as long as it is stationary.
  2. Check and correct the catalog. This part is manual. It is done through a user interface. Multiple views in the interface help the end user make good decisions: change the threshold, enlarge waveform shape, change feature method, change clustering algorithm and of course merge and split clusters. This part is crucial and must be performed to clean clusters.
  3. “Peel spikes”. This is the real spike sorting. It is a template matching approach that subtracts spikes for signals as long as some spike matches the catalog. This part can be run offline as fast as possible or online (soft real time) if fast enough.
  4. Check the final result with a dedicated user interface. No manual action is required here.

Why is it different from other tools:

  • Today, some other tools propose more or less the same workflow except the central step: check the catalog before the template matching! This is critical. These tools often over split some clusters and this leads to long, useless and uncontrolled manual merges (or split sometimes) at the end of the process.
  • The catalog is built only from a small part of the dataset, let say some minutes. Some other tools try to cluster spike on long recording but there are many chances that signal, noise, amplitude will not be stationary. Clustering on a small part is faster and leads to more stable results.
  • The user interface (for catalogue check/correct and peeler check) is part of the same package. So viewers are closely linked to methods and everything is done to alleviate the pathologies of these methods.

Online spike sorting

If you have a pyacq compatible device (Blackrock, Multi channel system, NiDaqMx, Measurement computing, …) you can also test tridesclous online during the experiment. See online_demo.py

In pyacq, you can build your own viewers in a custom “Node”, so you should be able to monitor during the recording what you need (receptive field, …)