Neuroscience data analysis framework for reproducible research built by Loren Frank Lab at UCSF
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Updated
Nov 10, 2026 - Jupyter Notebook
Neuroscience data analysis framework for reproducible research built by Loren Frank Lab at UCSF
Matlab user interface for the analysis of LFP and spike data from extracellular recordings supporting a variety of existing Python and Matlab tools.
Automatic and manual spike sorting based on SpikeInterface
Local-first web app for LFP-only neural representation inference and reference spike-activity decoding with a locked pretrained model, 256D features, UMAP visualization, and no data upload.
A fast, memory-bounded Rust engine for electrophysiology signal processing — Neuropixels-scale, callable from Python.
Lossless electrophysiology compression with direct SpikeInterface and Kilosort4 readers
NeuroConv conversion of a simulated multi-port Utah array walking session to NWB, with tests that check the written file against the source data.
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