# fly_frain

**Repository Path**: dxatar/fly_frain

## Basic Information

- **Project Name**: fly_frain
- **Description**: 基于果蝇大脑的运动可视化项目
- **Primary Language**: Unknown
- **License**: MulanPSL-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 4
- **Created**: 2026-09-19
- **Last Updated**: 2026-09-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README



# FlyBrain Simulation

A computational neuroscience simulation of Drosophila melanogaster (fruit fly) behavior, featuring a spiking neural network connectome, physical embodiment, and real-time web visualization.

## Overview

FlyBrain simulates the closed-loop interaction between a fly's neural activity and its physical behavior in a virtual environment. The system integrates:

- **LIF Neural Network**: Leaky Integrate-and-Fire neuron model with configurable connectivity
- **Connectome**: Hierarchical neural architecture (sensory → integration → motor)
- **Behavioral State Machine**: Real-time behavior classification (foraging, quiescence, etc.)
- **Physics Engine**: 2D body dynamics with environmental interaction
- **Web Interface**: Live visualization and experimental manipulation

## Installation

```bash
# Clone the repository
git clone https://gitee.com/dxatar/fly_frain.git
cd fly_frain

# Install dependencies
pip install -r requirements.txt
```

## Quick Start

```bash
python main.py --port 8765
```

Then open `http://localhost:8765` in your browser. Use the web controls to:
- Toggle free movement mode
- Monitor neural activity and behavior state
- Apply experimental manipulations

## Architecture

### Neural Subsystem

| Module | Purpose |
|--------|---------|
| `connectome.py` | Neural topology and synaptic weights |
| `brain_sim.py` | LIF network dynamics and integration |
| `motor_decode.py` | Neural activity → motor commands |

### Behavioral Subsystem

| Module | Purpose |
|--------|---------|
| `behavior.py` | Behavior classification from neural state |
| `exploration.py` | Spontaneous drive and satiety dynamics |

### Physical Subsystem

| Module | Purpose |
|--------|---------|
| `fly_physics.py` | Body dynamics and environmental interaction |
| `manipulations.py` | Experimental manipulations (optogenetics, silencing) |

### Interface

| Module | Purpose |
|--------|---------|
| `server.py` | HTTP API and websocket streaming |
| `web/` | Browser-based visualization |

## Usage

### Command Line Options

```bash
python main.py --port 8765 --speed 2.0 --headless 30
```

| Parameter | Description |
|-----------|-------------|
| `--port` | Web server port (default: 8765) |
| `--speed` | Simulation speed multiplier |
| `--headless` | Run without visualization for N seconds |

### Programmatic API

```python
from flybrain.connectome import Connectome
from flybrain.brain_sim import LIFNetwork
from flybrain.fly_physics import Environment

# Load connectome
con = Connectome.built_in()

# Initialize network
net = LIFNetwork(con)

# Run simulation step
I_ext = {n: 0.0 for n in con.keys()}
rates = net.step(I_ext)
```

## Experimental Manipulations

The system supports real-time manipulation of neural subsets:

- `ChR` - Channelrhodopsin excitation
- `GtAC1` - ArchT inhibition
- `sib` - Sibutramine manipulation

Apply via web interface or API:

```python
from flybrain.manipulations import ManipulationState

state = ManipulationState()
state.set("ChR", True)  # Activate ChR-expressing neurons
```

## Data Format

### Nodes CSV

| Column | Description |
|--------|-------------|
| id | Unique neuron identifier |
| layer | Processing layer (sensory/motor/etc.) |
| type | Neuron type |

### Edges CSV

| Column | Description |
|--------|-------------|
| src | Source neuron ID |
| dst | Destination neuron ID |
| weight | Synaptic strength |
| delay | Transmission delay (ms) |

## Development

### Running Tests

```bash
python -m pytest tests/
```

### Key Test Files

| File | Purpose |
|------|---------|
| `tests/behavior.py` | Behavior classification validation |
| `tests/manipulation.py` | Manipulation state tests |
| `tests/tune*.py` | Parameter optimization scripts |

## File Structure

```
fly_frain/
├── flybrain/           # Core simulation modules
│   ├── __init__.py
│   ├── behavior.py     # Behavior classifier
│   ├── brain_sim.py    # LIF network
│   ├── connectome.py   # Neural connectivity
│   ├── exploration.py  # Drive/satiety
│   ├── fly_physics.py  # Body dynamics
│   ├── manipulations.py # Experimental states
│   ├── motor_decode.py # Motor decoder
│   └── server.py       # HTTP interface
├── web/                # Frontend assets
├── data/               # Example datasets
├── tests/              # Test suite
├── main.py            # Entry point
└── requirements.txt   # Dependencies
```

## License

MIT License

## References

- Fly connectome: [Janelia FlyEM](https://www.janelia.org/project-teams/flyem)
- LIF neuron model: Abbott (1999)
- Behavioral ethogram: [FlyPedia](https://flybrain.neurobio.arizona.edu)