tsodyks-markram-chaotic-dynamics
CommunityReveal chaotic TM dynamics.
Education & Research#neuroscience#tsodyks-markram#chaotic-dynamics#shilnikov-bifurcation#bifurcation-analysis#lyapunov-exponent#deterministic-models
Authorhiyenwong
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Enables researchers to analyze and simulate chaotic dynamics in deterministic Tsodyks-Markram networks, revealing how Shilnikov-like bifurcations drive unpredictable activity.
Core Features & Use Cases
- Deterministic TM network simulation with configurable synaptic dynamics (U, tau_rec, tau_facil) and neuron parameters.
- Bifurcation and chaos analysis tools including Lyapunov exponent estimation and homoclinic orbit detection.
- Use cases in computational neuroscience education, synaptic plasticity modeling, and nonlinear dynamics research.
Quick Start
Configure the TMModelConfig with U, tau_rec, and tau_facil, then create a TMNetworkModel and run simulate with a simple input function.
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: tsodyks-markram-chaotic-dynamics Download link: https://github.com/hiyenwong/ai_collection/archive/main.zip#tsodyks-markram-chaotic-dynamics Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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