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Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)
3. Recording to Neurodata Without Borders format
Description: Neurodata Without Borders (NWB) is a recently developed data format that aims to simplify the process of sharing data across labs. It's based on HDF5, a format designed to store scientific datasets within hierarchical, self-documenting files. The Open Ephys GUI can currently be configured to save data as binary files or in Kwik files, another HDF5-based format. Adding the ability to save directly to the NWB format will be beneficial to a number of users, as NWB becomes more widely adopted by members of the field. Additionally, the project could include adding support for other commonly used binary formats, such as those developed by Neuralynx and Plexon. We have already implemented a modular recording architecture, which greatly simplifies the process of adding support for new formats.
Skills required: Proficiency in C++, familiarity with HDF5
Level of difficulty: Easy
Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)
4. Event-triggered averaging module
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Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)
45. Julia plugin module
Description: Creating custom processing modules for the Open Ephys GUI currently requires knowledge of C++. However, most scientists prefer to write code in high-level languages, such as Python and Matlab. Julia is a relatively new language for scientific computing that combines a syntax similar to Matlab with the speed of compiled C++. It's easy to call Julia code from a C++ application using the Julia C++ interface. In order to take advantage of the vast amount of signal processing code that's been written by neuroscientists, and to make it easier for users to modify the GUI, we'd like to make it possible to run Julia code directly within our software. Julia modules could be used for such applications as detecting patterns in spiking activity or performing spectral analysis on neural signals. We already have a working minimal prototype (https://github.com/open-ephys/gui/tree/jvoigts), but it needs to be made more robust and user-friendly.
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Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)
56. Behavior scoring with accelerometer data
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Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)
67. OpenBCI integration
Description: The majority of Open Ephys users are academic researchers performing experiments on animal models. However, the flexibility of the Open Ephys GUI would make it ideal for working with data from humans as well. Although the Open Ephys acquisition board can be adapted for use with human EEG, there are better alternatives out there. OpenBCI is a widely used open-source platform for streaming EEG data to a computer. Enabling the Open Ephys GUI to interface with OpenBCI hardware would allow our software to reach a much wider audience. We'd like to create a source module that could receive data from a 16-channel OpenBCI board. Next, existing visualization modules (such as the LFP Viewer) should be optimized for use with EEG data. In addition, modules for spectral analysis and machine learning could be created to respond to changes in brain state in real time.
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Mentors: Josh Siegle (@jsiegle), Jakob Voigts (@jvoigts), Aarón Cuevas López (@aacuevas)
78. Improving the spike-sorting module
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