spikeinterface-electrophysiology
Unified Python framework for extracellular electrophysiology. Load 20+ formats (SpikeGLX, OpenEphys, NWB, Intan, Maxwell, Blackrock), preprocess, run 10+ sorters (Kilosort4, SpykingCircus2, Tridesclous, MountainSort5) via one API, compute quality metrics (SNR, ISI, firing rate), compare sorters, export NWB/Phy. For format-agnostic multi-sorter workflows. For Neuropixels-specific PSTH/decoding use neuropixels.
npx skills add BioTender-max/awesome-bio-agent-skills --skill spikeinterface-electrophysiology --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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, IS
- Overview
- When to Use
- Prerequisites
- Quick Start
- Core API
- Module 1: Recording I/O
- Module 2: Preprocessing
- Module 3: Spike Sorting
- Module 4: Postprocessing (SortingAnalyzer)
- Module 5: Quality Metrics
- Module 6: Comparison and Export
- Common Workflows
- Workflow 1: Multi-Sorter Comparison on OpenEphys Data
- Workflow 2: Ground Truth Validation with Synthetic Recordings
pip install "spikeinterface[full]>=0.101" probeinterface pip install kilosort pip install phy
What does the spikeinterface-electrophysiology skill do?
Unified Python framework for extracellular electrophysiology. Load 20+ formats (SpikeGLX, OpenEphys, NWB, Intan, Maxwell, Blackrock), preprocess, run 10+ sorters (Kilosort4, SpykingCircus2, Tridesclous, MountainSort5) via one API, compute quality metrics (SNR, ISI, firing rate), compare sorters, export NWB/Phy. For format-agnostic multi-sorter workflows. For Neuropixels-specific PSTH/decoding use neuropixels.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill spikeinterface-electrophysiology --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.