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neuralink-decoder

Simulates and decodes neural spike activity into cursor movement (BCI).

aadipapp0 source installs☆ 0 Repository starsv0.1.0

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install aadipapp/neuralink-decoder

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill 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.

Source information

Source
github
Repository
openclaw/skills
Path
skills/aadipapp/neuralink-decoder
Version
0.1.0
Commit
4bc6b15d8befb02093041cb74fd3e94542470568
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

Neuralink Decoder Skill

This skill demonstrates a Brain-Computer Interface (BCI). It simulates neural activity from the Motor Cortex and decodes it to control a virtual cursor.

How it Works

  1. Neural Simulation: Uses a "Cosine Tuning" model to generate spike counts for 64 simulated neurons based on a movement intention (e.g., "Move Right").
  2. Decoding: Uses a Population Vector algorithm to aggregate the spiking activity and reconstruct the velocity vector.
  3. Result: The cursor moves in the direction of the user's intent.

Usage

Run the BCI loop:

python3 scripts/decoder.py

Publishing

clawhub publish

Extracted content

SKILL.md
# 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.
README
# Neuralink Decoder Skill

This skill demonstrates a **Brain-Computer Interface (BCI)**.
It simulates neural activity from the Motor Cortex and decodes it to control a virtual cursor.

## How it Works
1.  **Neural Simulation**: Uses a "Cosine Tuning" model to generate spike counts for 64 simulated neurons based on a movement intention (e.g., "Move Right").
2.  **Decoding**: Uses a **Population Vector** algorithm to aggregate the spiking activity and reconstruct the velocity vector.
3.  **Result**: The cursor moves in the direction of the user's intent.

## Usage

Run the BCI loop:
```bash
python3 scripts/decoder.py
```

## Publishing
```bash
clawhub publish
```

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