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Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)
7. Improving the Spike sorting module
Description: The majority of Open Ephys users employ multi-channel extracellular electrodes, such as tetrodes, or silicon probes. In order to identify the activity of individual neurons in the data coming of such multi-contact probes, spike sorting methods need to be used. Traditionally, spike sorting was performed off-line after the experiment, but for virtually all on-line analyses based on spike patterns, spike-sorting needs to be performed in real-time. The Open Ephys GUI already has a module that performs simple spike-sorting (https://github.com/open-ephys/plugin-GUI/tree/master/Source/Plugins/SpikeSorter), but both it's user interface, as well as the internal analysis methods would benefit from some updates. Further, the module currently only works with purely manual clustering, which is increasingly less viable because the number of channels recorded with modern probes exceeds what a human experimenter can manually process, or even look at in the time required for a single recording. Spike sorting is a very active field and many automated or semi-automated spike sorting methods were recently developed and published. Intergating such methods into the Open Ephys GUI would increase its usefulness for high-channel count experiments.
Skills required: Proficiency in C++, experience designing user interfaces, knowledge of basic machine learning algorithms (ideally implemented in C++, but Python or Julia could also work here)
Level of difficulty: Hard
Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)