electroCUDA

Robust pelectrophysiology tools with GPU acceleration

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Updated 19 Nov 2022

From GitHub

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electroCUDA – see wiki for documentation & theoretical overview

Summary statistics of a highly-localized neuronal source decomposed by electroCUDA
Summary statistics of an independent neuronal source decomposed by electroCUDA

ElectroCUDA – robust preprocessing & analysis for electrophysiology. Core features include noise-resistant signal processing, robust statistics & extensive hardware acceleration.

Routines are intended for any multichannel field potential recordings (LFP/EEG/MEG), but are currently tailored for human intracranial EEG (ECoG/sEEG).

Code is Matlab-based with calls to compiled CUDA, C/C++ & Fortran binaries. User-friendly wrappers abstract away all non-Matlab operations. Modular code & data structures facilitate easy interoperability with other packages. Compute performance is maximized via layered hardware acceleration & comprehensive code optimizations.

View electroCUDA on File Exchange

Development status: PRE-ALPHA

⚠️   Code is not yet validated & peer-reviewed for general use – hang tight!

Acknowledgements

This work was supported by National Science Foundation Graduate Research Fellowship DGE-1650604 and Department of Defense Grant 13RSA281. See wiki for full acknowledgments.

License

ElectroCUDA is free and open-source under GNU GPL 3.0

Terms of use

This code is for research purposes only and is not intended for clinical or medical use.

Use this code at your own risk. Users assume full responsibility for any eventuality related to this content.

USE AND DISTRIBUTION OF THIS SOFTWARE MAY BE SUBJECT TO UNIVERSITY OF CALIFORNIA INTELLECTUAL PROPERTY RIGHTS AND UNITED STATES MANDATES FOR FEDERALLY-FUNDED RESEARCH.

THE CONTENT HEREIN IS PROVIDED "AS IS" WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES. IN NO EVENT SHALL THE AUTHORS AND CONTRIBUTORS OF CONTENT HEREIN BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY OR CONSEQUENTIAL DAMAGES AND/OR ADVERSE OUTCOMES RELATED IN ANY WAY TO THE USE OF THIS CONTENT. ANY USE OF THIS CONTENT IMPLIES ACCEPTANCE OF THESE TERMS.

Cite As

Kevin Tan (2023). electroCUDA (https://github.com/kevmtan/electroCUDA), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2022b
Compatible with R2020a and later releases
Platform Compatibility
Windows macOS Linux

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