Online / real-time BCI · Applications
BRAND
Backend for Real-time Asynchronous Neural Decoding: a platform for closed-loop experiments with deep-network decoders.
- Specialized
- Research-focused
- Real-time ready
What problem does it solve?
Running modern neural-network decoders inside a millisecond-scale closed loop needs a system designed for it.
Who is it for?
Intracortical BCI labs running online experiments
At a glance
- Primary use
- Online / real-time BCI
- Licence
- MIT · permissive
- Language
- Python and C
- Current release
- No tagged release on GitHub
- Development activity
- Last commit 1 Sep 2026 · repository created 21 Jun 2023
- Maintainers
- BRAND developers (BrainGate collaborators)
- GitHub stars
- 50 as of 3 Oct 2026
Repository facts are a snapshot read from the GitHub API on 3 Oct 2026; they are reported as found, not scored.
Supported modalities and use
Common use cases
- Closed-loop cursor and speech experiments
- Modular real-time graphs
How it fits into a BCI stack
Hardware
2 tools
Acquisition
3 tools
Streaming
3 tools
Processing
6 tools
Decoding
4 tools
Applications
BRAND
Data & standards
3 tools
- Build an online motor decoderas Real-time synchronization
Publications
- An Accurate and Rapidly Calibrating Speech Neuroprosthesis
Card NS et al. · New England Journal of Medicine · 2024
Sources
- 01
github.com/brandbci/brand (opens in a new tab)
Open-source repositoryGitHubChecked against source 3 Oct 2026
Repository metadata read from the GitHub API.