# MULANIICodes

**Repository Path**: thegala/MULANIICodes

## Basic Information

- **Project Name**: MULANIICodes
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-01-14
- **Last Updated**: 2021-01-14

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# MULANIICodes

MULAN (MULtiple method ANalysis) is a method that uses fuzzy inference, genetic and algorithms to integrate multiple methods to infer consensus connectivity. And also it includes a platform to systematically evaluate any given connectivity analysis method.
MULAN is an open platform. Any new method can easily be added and tested.
The MULAN toolbox is written in two program languages: MATLAB and Python. MATLAB codes include 42 basic methods and MULAN algorithm. The simulated datasets and the definition of ground truth structures are also in MATLAB. The Python codes include the evaluation and output the graphs.

The User Guide is here: https://github.com/HuifangWang/MULANIICodes/blob/master/User_Guide_MULAN2.pdf

The paper reference: 
Wang, H. E., Friston, K. J., Bénar, C. G., Woodman, M. M., Chauvel, P., Jirsa, V., & Bernard, C. (2018). MULAN: Evaluation and ensemble statistical inference for functional connectivity. NeuroImage. https://doi.org/10.1016/j.neuroimage.2017.10.036