neuralink-decoder
Simulates and decodes neural spike activity into cursor movement (BCI).
Setup & Installation
Install command
clawhub install aadipapp/neuralink-decoderIf the CLI is not installed:
Install command
npx clawhub@latest install aadipapp/neuralink-decoderOr install with OpenClaw CLI:
Install command
openclaw skills install aadipapp/neuralink-decoderor paste the repo link into your assistant's chat
Install command
https://github.com/openclaw/skills/tree/main/skills/aadipapp/neuralink-decoderWhat This Skill Does
Simulates a Brain-Computer Interface by generating synthetic spike trains for 64 neurons using a cosine tuning motor cortex model. A linear decoder maps spike rates to 2D cursor velocity and prints the reconstructed trajectory.
Runs the full BCI decoding pipeline without physical neural recording hardware, making it accessible for development and education without specialized equipment.
When to Use It
- 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
View original SKILL.md file
# 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.
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Prototyping BCI decoding algorithms without physical hardware
- 1Prototyping BCI decoding algorithms without physical hardware
- 2Testing neural decoder accuracy on synthetic spike data
- 3Teaching motor cortex signal processing in coursework
- 4Benchmarking cursor velocity reconstruction approaches
- 5Exploring cosine tuning models for BCI research
Simulates and decodes neural spike activity into cursor movement (BCI).
Security Audits
These signals reflect official OpenClaw status values. A Suspicious status means the skill should be used with extra caution.