Does this skill support Neuropixels 2.0?

Yes, it supports both Neuropixels 1.0 and 2.0 (including single-probe and 4-shank) probe geometries and electrode mappings.

How does the AI-assisted curation feature work?

It leverages Claude's vision capabilities to examine waveform plots and correlograms, providing expert-level classification decisions for borderline neural units that automated metrics might miss.

Which spike sorters can I use with this skill?

The skill supports Kilosort4 (which requires a GPU) as well as several CPU-based alternatives like SpykingCircus2, Mountainsort5, and Tridesclous2.

Can I export data for manual review in other tools?

Absolutely. The skill includes built-in functions to export processed data and analyzers to Phy for manual curation and NWB for standardized data sharing.

What raw data formats are supported?

It natively handles formats from major acquisition systems including SpikeGLX (.bin/.meta files), Open Ephys (.oebin), and Neurodata Without Borders (.nwb).

Neuropixels Data Analysis

Name: Neuropixels Data Analysis
Author: Sologa

bySologa

数据科学与机器学习

Streamlines the analysis of high-density neural recordings from Neuropixels probes through automated preprocessing, spike sorting, and quality curation.

关于

This skill provides a comprehensive toolkit for analyzing Neuropixels 1.0 and 2.0 extracellular electrophysiology data, integrating industry-standard tools like SpikeInterface, Kilosort4, and Allen/IBL curation criteria. It automates the transition from raw data formats (SpikeGLX, Open Ephys) to publication-ready units by handling complex tasks such as motion correction, drift estimation, and AI-assisted visual curation. Whether you are computing quality metrics or exporting results to Phy/NWB, this skill ensures best practices for neuroscientific data workflows and high-throughput research.

主要功能

AI-assisted visual analysis for expert unit curation
Automated motion detection and non-rigid drift correction
Standardized quality metrics including SNR and ISI violations
Integrated spike sorting with Kilosort4 and CPU-based alternatives
Support for Neuropixels 1.0 and 2.0 probe geometries
0 GitHub stars

使用场景

Automating spike sorting pipelines with advanced drift correction
Validating and curating neural units using Allen Institute or IBL standards
Processing large-scale extracellular electrophysiology datasets

关于

主要功能

AI-assisted visual analysis for expert unit curation
Automated motion detection and non-rigid drift correction
Standardized quality metrics including SNR and ISI violations
Integrated spike sorting with Kilosort4 and CPU-based alternatives
Support for Neuropixels 1.0 and 2.0 probe geometries
0 GitHub stars

使用场景

Automating spike sorting pipelines with advanced drift correction
Validating and curating neural units using Allen Institute or IBL standards
Processing large-scale extracellular electrophysiology datasets