Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more.
Features
- MEG, EEG, sEEG, ECoG, NIRS, and more
- Documentation for MNE-Python encompasses installation instructions, tutorials, and examples
- The user forum is the best place to ask questions about MNE-Python usage or the contribution process
- Distributed, sparse, mixed-norm, beamformers, dipole fitting, and more
- Receptive field estimation
- Explore your data from multiple perspectives
- Examples available
Categories
Machine LearningLicense
BSD LicenseFollow MNE-Python
Other Useful Business Software
Turn traffic into pipeline and prospects into customers
Docket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of MNE-Python!