Starting brain simulation with BrainX#
BrainX 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 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#
- Constructing LIF neuron model with
brainstate - Simulating excitatory-inhibitory spiking networks with
brainpy - Simulating a Hodgkin–Huxley neuron with
braincell - Simulating excitatory-inhibitory Hodgkin-Huxley neuron networks using
braincell - Simulating morphological Golgi cell with
braincell - Simulating Jansen–Rit population dynamics with
brainmass