gp-cake-brain-connectivity
CommunityInfer brain connectivity with causal GP kernels.
Education & Research#neuroscience#time-series#gaussian-process#brain-connectivity#gp-cake#causal-kernel#nonparametric
Authorhiyenwong
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Understands and infers directional, causal interactions between neural regions from time-series data using GP CaKe's causal kernels, enabling nonparametric learning of effective connectivity.
Core Features & Use Cases
- Nonparametric learning of directional brain influence via causal kernels
- Applicability to MEG/EEG and fMRI time-series for dynamic connectivity modeling
- Biologically meaningful hyperparameters (time scale, delay, strength) that aid interpretation
Quick Start
Infer effective connectivity between source and target brain regions from your time-series data using GP CaKe.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: gp-cake-brain-connectivity Download link: https://github.com/hiyenwong/ai_collection/archive/main.zip#gp-cake-brain-connectivity Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 471,000+ vetted skills library on demand.