eonsystemspbc

eonsystemspbc / fly-brain

Public

Emulation of the Drosophila Fly brain: Brian2, Brian2CUDA, PyTorch, NEST GPU, and neuromorphic chips

213
25
100% credibility
Found Mar 10, 2026 at 143 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This repository implements a whole-brain simulation of the adult fruit fly nervous system using the FlyWire connectome, allowing users to activate or silence neurons and benchmark performance across multiple neural simulation frameworks.

How It Works

1
🧠 Discover Fly Brain Simulator

You hear about a tool that recreates the entire brain of a fruit fly to study how neural signals spread when certain neurons are turned on or off.

2
📥 Get the Files

Download the project files to your computer so you can start experimenting with fly brain activity.

3
🛠️ Ready Your Workspace

Follow easy steps to prepare your computer, making sure it can handle the brain calculations smoothly with your graphics card.

4
🧪 Pick Your Experiment

Choose to activate sugar-sensing neurons or walking command neurons, and decide how long to run the simulation.

5
▶️ Launch Brain Simulation

Hit start to activate neurons and watch activity ripple through the 138,000 neurons and millions of connections in real time.

6
📊 Review Results

Check logs and charts showing simulation speeds, spike counts, and how activity propagates downstream.

✅ Unlock Brain Insights

You now have data on fly sensorimotor processing and performance comparisons to share or build upon.

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Star Growth

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AI-Generated Review

What is fly-brain?

This Python repo emulates the entire fruit fly brain using the FlyWire connectome, modeling 138k neurons and 5M synapses with leaky integrate-and-fire dynamics for realistic spike propagation. Activate neurons at fixed frequencies or silence them via simple CLI commands like `python main.py --pytorch --t_run 1 --n_run 30`, and get spike times, rates, and benchmarks saved to CSV or Parquet. It supports Brian2CUDA, PyTorch, and NEST GPU on CUDA hardware, plus CPU fallbacks, turning fly brain mapping data into runnable fly brain simulations.

Why is it gaining traction?

It delivers head-to-head benchmarks across neural sim frameworks, revealing realtime ratios for fly brain connectome activity on GPUs—rare for whole-brain fruit fly brain GitHub projects. The one-command setup with Conda and WSL scripts gets you simulating fly brain anatomy fast, without custom neuron models or data wrangling. Developers dig the reproducible results for comparing fly brain scan emulations against neuromorphic chips.

Who should use this?

Computational neuroscientists benchmarking fly brain neurons or sensorimotor processing in the connectome. Hardware devs testing GPU/ neuromorphic chips with fly brain atlas data. Bio researchers replicating papers on Drosophila brain activity without rebuilding from scratch.

Verdict

Grab it if you're in fly brain simulation—solid CLI, data included, and cross-framework benchmarks make it instantly useful despite 91 stars and 1.0% credibility score. Still early; docs are strong but needs more examples and community tests for production trust.

(198 words)

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