bear-blog-publisher
Publish blog posts to Bear Blog platform. Supports user-provided markdown, AI-generated content, and auto-generated diagrams.
Simulates and decodes neural spike activity into cursor movement (BCI).
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install aadipapp/neuralink-decoderExaminez 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.
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.
decode: Run the simulation and decoding loop.Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
This skill demonstrates a Brain-Computer Interface (BCI). It simulates neural activity from the Motor Cortex and decodes it to control a virtual cursor.
Run the BCI loop:
python3 scripts/decoder.py
clawhub publish
# 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.
# 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 ```
Publish blog posts to Bear Blog platform. Supports user-provided markdown, AI-generated content, and auto-generated diagrams.
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