# Starting brain simulation with BrainX 

[BrainX](https://github.com/chaobrain) provides a comprehensive platform for 
simulating brain activity at multiple scales, from individual neurons to 
large-scale brain networks. 

This tutorial will guide you through the basics of setting up and running 
your first brain simulation using ``BrainX``.


## Who is this tutorial for?

- Learners new to BrainX who want a gentle, practical start.
- Students of computational neuroscience exploring multi‑scale modeling.
- Researchers and engineers prototyping neuron, network, or rate‑model simulations.
- Python users comfortable with Jupyter notebooks and basic numerical computing.

Recommended prerequisites:

- Python, Jupyter, and basic familiarity with differential equations and signals.
- A working BrainX [installation](./install.md) as set up in your environment for this repo.

## What does this tutorial cover?

This tutorial walks through BrainX across three model scales with runnable notebooks:

- Single‑neuron dynamics with Hodgkin–Huxley
- Excitatory/Inhibitory spiking microcircuits
- Neural‑mass (mesoscopic) modeling
- Network‑level spiking state examples
- And many more ...

Along the way you will:

- Configure models and connectivity, set simulation parameters, and run time‑stepping.
- Record and visualize results (time series, rasters, spectra) and export data.
- Perform small parameter scans and note tips for reproducibility.


## English version

```{toctree}
:maxdepth: 1

brainstate_LIF_neuron.ipynb
brainpy_EI_spiking_network.ipynb
braincell_HH_neuron.ipynb
braincell_HH_EI_network.ipynb
braincell_morphological_golgi_cell.ipynb
brainmass_jansenrit_node_simulation.ipynb
```


## 中文版本

```{toctree}
:maxdepth: 1
braincell_HH_neuron-zh.ipynb
braincell_HH_EI_network.ipynb
braincell_HH_EI_network-zh.ipynb
brainmass_Modeling_MEG_data_zh.ipynb
```