Neuropixel Utils

Utilities for managing Neuropixel SpikeGLX datasets, Kilosort2 sorting, waveform extraction and other tools

Neuropixel Utils is a toolkit written in Matlab for manipulating datasets collected by SpikeGLX (e.g. imec.ap.bin files) and the results produced by Kilosort / Kilosort 2.

See documentation at https://djoshea.github.io/neuropixel-utils/

Please note that some of this functionality is redundant with the tools found in the Cortex Lab’s spikes repository, authored By Nick Steinmetz, Mush Okun, and others. Here, we prioritize an organized, easy to use, object-oriented approach to accessing, manipulating, and visualizing the data. This reduces the need to worry about metadata.

Neuropixel Utils facilitates the following data processing steps:
- Load and visualize raw neuropixel data from imec.ap.bin and imec.lf.bin files in Matlab
- Write custom pre-processing functions to apply to raw data either by writing a copy of the raw file or modifying it in place, optionally removing specific problematic time windows in the file
- Concatenate multiple Imec data files together while matching the amplifier gains
- Run Kilosort/Kilosort2, and load the results back into Matlab after manual inspection in Phy
- Plot drift maps using code adapted from the spikes repository
- Extract waveforms for each cluster from the raw data, optionally cleaning the snippets by subtracting templates for other clusters spiking during the same time window
- Visualize cluster electrical spiking images in space and cluster locations on the probe
- Determine trial boundaries in the file, and efficiently segment Kilosort results into individual trials

Neuropixel Utils was authored by Daniel J O’Shea (@djoshea) to facilitate precision artifact removal and careful inspection of raw data traces before running Kilosort, as well as post-hoc verification that the artifacts were removed successfully.