Compatible Technology

Supported File Formats

Currently, we support many popular file formats for both raw and sorted extracellular datasets. Given the standardized, modular design of our recording and sorting extractors, adding new file formats is straightforward so we expect this list to grow in future versions.

Most of format are supported on top on NEO

Raw Data Formats

For raw data formats, we currently support:

  • BlackRock - BlackRockRecordingExtractor

  • Binary - BinaryRecordingExtractor

  • Biocam HDF5 - BiocamRecordingExtractor

  • CED - CEDRecordingExtractor

  • Intan - IntanRecordingExtractor

  • Klusta - KlustaRecordingExtractor

  • MaxOne - MaxOneRecordingExtractor

  • MCSH5 - MCSH5RecordingExtractor

  • MEArec - MEArecRecordingExtractor

  • Mountainsort MDA - MdaRecordingExtractor

  • Neurodata Without Borders - NwbRecordingExtractor

  • Neuroscope - NeuroscopeRecordingExtractor

  • NIX - NIXIORecordingExtractor

  • Neuralynx - NeuralynxRecordingExtractor

  • Open Ephys Legacy - OpenEphysLegacyRecordingExtractor

  • Open Ephys Binary - OpenEphysBinaryRecordingExtractor

  • Phy/Kilosort - PhyRecordingExtractor/KilosortRecordingExtractor

  • Plexon - PlexonRecordingExtractor

  • Shybrid - SHYBRIDRecordingExtractor

  • SpikeGLX - SpikeGLXRecordingExtractor

  • Spyking Circus - SpykingCircusRecordingExtractor

Sorted Data Formats

For sorted data formats, we currently support:

  • BlackRock - BlackRockSortingExtractor

  • Combinato - CombinatoSortingExtractor

  • Experimental Directory Structure (Exdir) - ExdirSortingExtractor

  • HerdingSpikes2 - HS2SortingExtractor

  • JRClust - JRCSortingExtractor

  • Kilosort/Kilosort2 - KiloSortSortingExtractor

  • Klusta - KlustaSortingExtractor

  • MEArec - MEArecSortingExtractor

  • Mountainsort MDA - MdaSortingExtractor

  • Neurodata Without Borders - NwbSortingExtractor

  • Neuroscope - NeuroscopeSortingExtractor

  • NPZ (created by SpikeInterface) - NpzSortingExtractor

  • Open Ephys - OpenEphysSortingExtractor

  • Shybrid - SHYBRIDSortingExtractor

  • Spyking Circus - SpykingCircusSortingExtractor

  • Trideclous - TridesclousSortingExtractor

  • YASS - YassSortingExtractor

Installed Extractors

To check which extractors are useable in a given python environment, one can print the installed recording extractor list and the installed sorting extractor list. An example from a newly installed miniconda3 environment is shown below,

First, import the spikeextractors package,

import spikeinterface.extractors as se

Then you can check the installed RecordingExtractor list,


which outputs,


and the installed SortingExtractors list,


which outputs,


When trying to use an extractor that has not been installed in your environment, an installation message will appear indicating which python packages must be installed as a prerequisite to using the extractor,

mearec_file = 'path_to_exdir_file.h5'
recording = se.MEArecRecordingExtractor(mearec_file)

throws the error,

----> 1 se.MEArecRecordingExtractor(mearec_file)

AssertionError: To use the MEArecRecordingExtractor run:

pip install MEARec

Dealing with Non-Supported File Formats

Many users store their datasets in custom file formats that are not general enough to create new extractors. To allow these users to still utilize SpikeInterface with their data, we built two in-memory Extractors: the NumpyRecordingExtractor and the NumpySortingExtractor.

The NumpyRecordingExtractor can be instantiated with a numpy array that contains the underlying extracellular traces (channels x frames), the sampling frequency, and the probe geometry (optional). Once instantiated, the NumpyRecordingExtractor can be used like any other RecordingExtractor.

The NumpySortingExtractor does not need any data during instantiation. However, after instantiation, it can be filled with data using its built-in functions (load_from_extractor, set_times_labels, and add_unit). After sorted data is added to the NumpySortingExtractor, it can be used like any other SortingExtractor.

With these two objects, we hope that any user can access SpikeInterface regardless of the nature of their underlying file format. If you feel like a non-supported file format should be included in SpikeInterface as an actual extractor, please leave an issue in the spikeextractors repository.

Supported Spike Sorters

Currently, we support many popular semi-automatic spike sorters. Given the standardized, modular design of our sorters, adding new ones is straightforward so we expect this list to grow in future versions.

  • HerdingSpikes2 - HerdingspikesSorter

  • IronClust - IronClustSorter

  • Kilosort - KilosortSorter

  • Kilosort2 - Kilosort2Sorter

  • Kilosort2.5 - Kilosort2_5Sorter

  • Kilosort3 - Kilosort3Sorter

  • PyKilosort - PyKilosortSorter

  • Klusta - KlustaSorter

  • Mountainsort4 - Mountainsort4Sorter

  • SpyKING Circus - SpykingcircusSorter

  • Tridesclous - TridesclousSorter

  • Wave clus - WaveClusSorter

  • Combinato - CombinatoSorter

  • HDSort - HDSortSorter

  • yass - YassSorter

Installed Sorters

To check which sorters are useable in a given python environment, one can print the installed sorters list. An example is shown in a pre-defined miniconda3 environment.

First, import the spikesorters package,

import spikeinterface.sorters as ss

Then you can check the installed Sorter list,


which outputs,


When trying to use an sorter that has not been installed in your environment, an installation message will appear indicating how to install the given sorter,

recording = ss.run_ironclust(recording)

throws the error,

AssertionError: This sorter ironclust is not installed.
      Please install it with:

To use IronClust run:

      >>> git clone
  and provide the installation path by setting the IRONCLUST_PATH
  environment variables or using IronClustSorter.set_ironclust_path().