brian2-simulation
CommunitySimulate spiking neural networks with Brian2.
Education & Research#computational neuroscience#stdp#brian2#spiking neurons#recurrent network#raster plot#mean-field analysis
Authorxjtulyc
Version1.0.0
Installs0
System Documentation
What problem does it solve?
It enables end-to-end simulation of spiking neural networks so you can study neuron dynamics, synaptic plasticity, and resulting firing statistics without building models from scratch each time.
Core Features & Use Cases
- Neuron model simulation (LIF/AdEx/HH): Run biologically inspired integrate-and-fire, adaptive exponential, and Hodgkin-Huxley style conductance dynamics.
- Network dynamics (recurrent E-I networks): Simulate excitatory/inhibitory populations with sparse connectivity and analyze emergent activity.
- Plasticity and analysis (STDP, raster plots, mean-field checks): Implement STDP learning rules and produce raster plots and firing-rate statistics for coding hypotheses.
Quick Start
Use the brian2-simulation skill to simulate an E-I spiking network with LIF neurons, generate a raster plot, and compute smoothed firing rates from the spike trains.
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: brian2-simulation Download link: https://github.com/xjtulyc/awesome-rosetta-skills/archive/main.zip#brian2-simulation Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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