NCPNet 1.0.3

Learning synapse-level brain circuit networks. Include training, inferring, evaluation, and visualization.

NCPNet

1. Brief Introduction

Neuronal Circuit Prediction Network (NCPNet), a simple and effective model for inferring neuron-level connections in a brain circuit network.

2. Installation

Requirements

• Linux
• CUDA environment >=10.2
• NVIDIA CUDA Compiler Driver NVCC version>=10.2. This is used for compiling the dependencies of torch_geometric: torch-cluster,torch-sparse,torch-scatter.
• torch==1.8.0

Step 1

1. Ensure that nvcc is accessible from terminal and version >=10.2

nvcc --version

If NVCC is not not included in your device, it can be installed through the CUDA Toolkit. NVCC is a part of the CUDA Toolkit.

2. Ensure that CUDA is usable and version >=10.2

nvidia-smi |grep Version
>>>CUDA Version: >=10.2

Step 2

Use pip to install NCPNet

pip install NCPNet

Note that it takes a long time to build torch-cluster,torch-sparse,and torch-scatter by pip. Don`t worry, just wait for a while.

Our main dependencies:

torch==1.8.0
torch_geometric==2.0.1
torch-cluster==1.5.9
torch-sparse==0.6.12
torch-scatter==2.0.8
navis==1.3.1
neuprint-python==0.4.25

If you would like to reproduce our experiments and plots, please also install jupyter.

pip install jupyter

Code structure:

Source Code
├── data
|   ├──Hemibrain
|   └──C.Elegans
├── example
├── runs
├── configs
├── NCPNet
|   ├── approaches
|   ├── brain_data.py
|   ├── task.py
|   ├── trainer.py
|   └── utils.py
└── requirements.txt

Examples

1. Easy train a model on Drosophila HemiBrain

NCPNet uses a configuration file (yaml) to control training and test.

Run

python main_run.py -c configs/linkpred.yaml

linkpred.yaml include the hyperparameters of NCPNet.

2. Predict neuronal connection

Once you train a model, such as 'model.ncpnet', then use the following command to predict the probility between two neurons:

python -m NCPNet -pred 1721996278 1722670151 -m model.ncpnet

Response:

Inferring the connection probability of (1721996278->1722670151)
The score of (1721996278->1722670151): 0.874

Reproducibility of Our Paper

Please try to use jupyter to reproduce our experiments in ./examples/

Access Data

Raw Data

The Drosophila connectome is available at https://www.janelia.org/project-team/flyem/hemibrain.

The C.elegans connectome is available at https://wormwiring.org/

Preprocessed Data

The data will be released after the review process.