Utilities for managing Neuropixel datasets and Kilosort results
See the codeNeuropixel 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. 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.
See full documentation at https://djoshea.github.io/neuropixel-utils.
Neuropixel Utils facilitates the following data processing steps:
imec.ap.bin and imec.lf.bin files in MatlabNeuropixel 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.
To get started, clone the repo:
git clone https://github.com/djoshea/neuropixel-utils.git
And add it to your path in Matlab:
>> addpath('/path/to/neuropixel-utils')
Neuropixel Utils requires Matlab R2019b or later.
Utilities for managing Neuropixel datasets and Kilosort results
See the codeNeuropixel 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. 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.
See full documentation at https://djoshea.github.io/neuropixel-utils.
Neuropixel Utils facilitates the following data processing steps:
imec.ap.bin and imec.lf.bin files in MatlabNeuropixel 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.
To get started, clone the repo:
git clone https://github.com/djoshea/neuropixel-utils.git
And add it to your path in Matlab:
>> addpath('/path/to/neuropixel-utils')
Neuropixel Utils requires Matlab R2019b or later.