neuropixels-analysis
Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.
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Neuropixels Neural Recording Analysis Toolkit
Overview
A SpikeInterface-based high-density Neuropixels neural recording analysis toolkit that fully supports end-to-end processing from raw data to curated units, compatible with mainstream formats such as SpikeGLX and Open Ephys.
Use Cases
1. In vivo Neuropixels recording data processing
Processes neural electrophysiology data acquired with Neuropixels 1.0/2.0 high-density probes, including raw formats like .ap.bin and .lf.bin, as well as stored NWB files. Supports single-probe and multi-probe (4-shank) recordings.
2. Spike sorting and quality curation
Runs mainstream spike-sorting algorithms such as Kilosort4, SpykingCircus2, and Mountainsort5; computes quality metrics like SNR, ISI violation rate, and presence ratio; applies Allen Institute or IBL lab standards for automatic curation.
3. Data preprocessing and motion correction
Automatically detects bad channels, applies high-pass filtering, performs phase-shift correction (Neuropixels 1.0), and common average referencing. Detects and corrects probe drift during recording, supporting rigid and non-rigid correction modes.
Core Features
1. Full analysis pipeline with one-call execution
A single function call completes the entire pipeline from preprocessing to curation: run_pipeline() automatically and sequentially executes data loading, preprocessing, motion estimation, spike sorting, postprocessing, and quality computation.
2. Support for mainstream formats and algorithms
3. AI-assisted visual curation
For units with borderline quality metrics, supports visual analysis of waveforms and autocorrelograms via the Claude API, providing expert-like curation suggestions. Interactive analysis is available directly in the Claude Code environment.
Frequently Asked Questions
What hardware is required for Neuropixels data analysis?
Kilosort4 is recommended to use GPU acceleration, which can speed up processing by 10–50x. If using CPU-based sorters (e.g., SpykingCircus2), a multi-core processor and sufficient memory (recommended 32 GB+) are required. Preprocessing and postprocessing support parallel computation.
What is the difference between processing Neuropixels 1.0 and 2.0 data?
The main difference is phase-shift correction: Neuropixels 1.0 requires this correction, while Neuropixels 2.0 does not. The 2.0 probes have a higher electrode density (1280 vs 960 electrodes), but the processing pipeline is the same.
What formats can the analyzed data be exported to?
Supports exporting to Phy (for manual curation), NWB (universal neurodata format), CSV (quality metrics), and other formats. The SortingAnalyzer object contains complete results including waveforms, templates, amplitudes, etc., for further analysis.