SpikeInterface — Unified Extracellular Electrophysiology Framework

Overview

SpikeInterface provides a common Python API to read extracellular recordings from 20+ file formats, preprocess raw voltage traces, run 10+ spike sorters, postprocess and quality-control sorted units, and export results — all without format-specific code. Its modular design lets users swap sorters, formats, and preprocessing steps without rewriting pipelines. SpikeInterface is built around lazy, chainable objects: a Recording holds raw data, a Sorting holds spike times, and a SortingAnalyzer ties them together for waveform and metric computation.

When to Use

• Loading recordings from multiple acquisition systems (SpikeGLX, OpenEphys, Intan, NWB, Maxwell MEA, Blackrock) with a unified API rather than format-specific parsers
• Running the same preprocessing and sorting pipeline across experiments recorded on different hardware
• Comparing two or more spike sorters on the same recording to assess agreement and choose the best output
• Running containerized sorters (Kilosort, IronClust, MountainSort5) via Docker or Singularity without local installation
• Computing standard quality metrics (SNR, ISI violations, firing rate, presence ratio, amplitude cutoff) and applying threshold-based curation
• Validating spike-sorting accuracy against synthetic or hybrid ground-truth recordings
• Exporting sorted results to NWB for data sharing or to Phy for manual curation
• Use neuropixels-analysis instead for a complete Neuropixels-specific Kilosort4 workflow including PSTH computation, tuning curves, and population decoding
• For EEG, ECG, or other biosignal processing (not spike sorting), use neurokit2 instead

Prerequisites