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neuralink-decoder

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

aadipapp0 installations selon la source☆ 0 Étoiles du dépôtv0.1.0

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install aadipapp/neuralink-decoder

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

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.

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/aadipapp/neuralink-decoder
Version
0.1.0
Commit
4bc6b15d8befb02093041cb74fd3e94542470568
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

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

Contenu extrait

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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