OpenClaw · Skill
Neuralink Decoder
This skill simulates a Brain-Computer Interface (BCI). It generates synthetic neural spiking data based on cosine tuning (motor cortex model) and uses a linear decoder to reconstruct cursor velocity.
Install
Start with the primary install command. Alternate entrypoints are included below for ClawHub and OpenClaw CLI users.
Primary command
clawhub install aadipapp/neuralink-decoderClawHub installer
npx clawhub@latest install aadipapp/neuralink-decoderOpenClaw CLI
openclaw skills install aadipapp/neuralink-decoderDirect OpenClaw install
openclaw install aadipapp/neuralink-decoderWhat this skill does
This skill simulates a Brain-Computer Interface (BCI). It generates synthetic neural spiking data based on cosine tuning (motor cortex model) and uses a linear decoder to reconstruct cursor velocity.
Why it matters
Runs the full BCI decoding pipeline without physical neural recording hardware, making it accessible for development and education without specialized equipment.
Typical use cases
- Prototyping BCI decoding algorithms without physical hardware
- Testing neural decoder accuracy on synthetic spike data
- Teaching motor cortex signal processing in coursework
- Benchmarking cursor velocity reconstruction approaches
- Exploring cosine tuning models for BCI research
Source instructions
Neuralink Decoder Skill
This skill simulates a Brain-Computer Interface (BCI). It generates synthetic neural spiking data based on cosine tuning (motor cortex model) and uses a linear decoder to reconstruct cursor velocity.
Features
- Neural Simulator: Generates realistic spike trains for 64 neurons.
- Decoder: Maps spike rates to 2D velocity ($v_x, v_y$).
- Visualization: Prints the decoded trajectory.
Commands
decode: Run the simulation and decoding loop.