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blend-behavior-guided-neural

Distill privileged behavior knowledge into neural activity models for inference.

2|Updated Feb 12, 2026
Search Tags:#neuroscience#machine-learning#blend#behavior-decoding#neural-population-dynamics#privileged-distillation#behavior-guided
One-click install
npx skills add https://github.com/hiyenwong/ai_collection --skill blend-behavior-guided-neural
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: blend-behavior-guided-neural
Source: https://github.com/hiyenwong/ai_collection/tree/main/collection/skills/blend-behavior-guided-neural
Command: npx skills add https://github.com/hiyenwong/ai_collection --skill blend-behavior-guided-neural

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Neural activity and behavior are often difficult to model together, especially when behavior data is unavailable at inference time. BLEND addresses this by treating behavior as privileged information during training and relying on neural activity alone for inference using privileged knowledge distillation.

Core Features & Use Cases

  • Model-agnostic framework: works with diverse neural architectures.
  • Privileged knowledge distillation: teacher uses behavior signals to guide the student from neural data.
  • Flexible distillation strategies: supports multiple learning objectives and setups for neural decoding, neuron-type prediction, and brain-machine interface tasks.
  • Real-world applicability: suitable for neuroscience experiments, brain-machine interfaces, and electrophysiology datasets where behavior data is limited.

Quick Start

Provide neural activity data (and optionally behavior signals) to train a BLEND model and perform inference using only neural activity.

Frequently Asked Questions about blend-behavior-guided-neural

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I decode neural activity when behavior data is unavailable at inference?▼

BLEND enables behavior-guided neural dynamics by treating behavior as privileged information during training, allowing the student model to perform inference using only neural activity when behavior data is unavailable.

What is privileged knowledge distillation for neural decoding?▼

Privileged knowledge distillation for neural decoding uses a teacher model with behavior signals to guide a student model relying solely on neural activity, enabling behavior-informed inference when behavior data is missing.

Can I use BLEND with any PyTorch model for brain-machine interface tasks?▼

Yes, BLEND is a model-agnostic framework supporting diverse PyTorch-based neural architectures for brain-machine interface tasks, offering flexible distillation strategies for neural decoding and neuron-type prediction.

What's the best way to model neural population dynamics with limited behavior data?▼

The best way to model neural population dynamics with limited behavior data is behavior-guided distillation, treating behavior as privileged information during training while requiring only neural activity for inference.

Does neural decoding with privileged distillation work for electrophysiology datasets?▼

Yes, neural decoding with privileged distillation is suitable for electrophysiology datasets, using teacher-student architectures where the teacher leverages behavior signals to guide the student model using only neural activity.

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