scientific-neuroscience-electrophysiology

What problem does it solve?

Neuroscience researchers often need an integrated, reproducible workflow to process multi-modal neural data—from spike sorting and signal quality assessment to ERP, HRV, EDA, EMG analyses, and connectivity studies—for consistent, publication-ready insights.

Core Features & Use Cases

• End-to-end pipelines that combine SpikeInterface-based spike sorting, quality metrics (SNR, ISI violations), ERP extraction with MNE-Python, HRV analysis with NeuroKit2, EDA and EMG processing, and functional connectivity estimation.
• Multi-modal support for Neuropixels/MEA electrophysiology, EEG/ERP, ECG HRV, and autonomic measures in unified workflows.
• Use Case: Reuse established neuroscience analysis patterns to transform raw neural and physiological data into comparable results across experiments.

Quick Start

Create a reproducible neuroscience pipeline that loads electrophysiology and physiological data, runs spike sorting and ERP/HRV/EDA/EMG analyses, and exports a unified report.