Package: neurora
![ ](img/logo.jpg “ “)#NeuroRAA Python Toolbox of Representational Analysis from Multimodal Neural Data## OverviewRepresentational Similarity Analysis (RSA)has become a popular and effective method to measure the representation of multivariable neural activity in different modes.NeuroRAis an easy-to-use toolbox based onPython, which can do some works aboutRSAamong nearly all kinds of neural data, includingbehavioral, EEG, MEG, fNIRS, sEEG, ECoG, fMRI and some other neuroelectrophysiological data.
In addition, users can doNeural Pattern Similarity (NPS),Spatiotemporal Pattern Similarity (STPS),Inter-Subject Correlation (ISC),Classification-based EEG Decodinganda novel cross-temporal RSA (CTRSA)onNeuroRA.## Installation
> pip install neurora## PaperLu, Z., & Ku, Y. (2020). NeuroRA: A Python toolbox of representational analysis from multi-modal neural data. Frontiers in Neuroinformatics. 14:563669. doi: 10.3389/fninf.2020.563669## Website & How to use
See more details at the [NeuroRA website](https://zitonglu1996.github.io/NeuroRA/).You can read the [Documentation here](https://neurora.github.io/documentation/index.html) or download the [Tutorial here](https://zitonglu1996.github.io/NeuroRA/neurora/Tutorial.pdf) to know how to use NeuroRA.## Required Dependencies:[Numpy](http://www.numpy.org): a fundamental package for scientific computing.[SciPy](https://www.scipy.org/scipylib/index.html): a package that provides many user-friendly and efficient numerical routines.[Scikit-learn](https://scikit-learn.org/stable/#): a Python module for machine learning.[Matplotlib](https://matplotlib.org): a Python 2D plotting library.[NiBabel](https://nipy.org/nibabel/): a package prividing read +/- write access to some common medical and neuroimaging file formats.[Nilearn](https://nilearn.github.io/): a Python module for fast and easy statistical learning on NeuroImaging data.[MNE-Python](https://mne.tools/): a Python software for exploring, visualizing, and analyzing human neurophysiological data.## FeaturesCalculate the Neural Pattern Similarity (NPS)Calculate the Spatiotemporal Neural Pattern Similarity (STPS)Calculate the Inter-Subject Correlation (ISC)Calculate the Representational Dissimilarity Matrix (RDM)Calculate the Cross-Temporal RDM (RDM)Calculate the Representational Similarity based on RDMsOne-Step Realize Representational Similarity Analysis (RSA)Conduct Cross-Temporal RSA (CTRSA)Conduct Classification-based EEG decodingConduct Statistical AnalysisSave the RSA result as a NIfTI file for fMRIPlot the results## Demos
There are several demos for NeuroRA, and you can see them in /demos/.. path (both .py files and .ipynb files are provided).| Run the Demo | View the Demo |- | — | —- |Demo 1 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1_colab.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo1.ipynb) |Demo 2 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2_colab.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo2.ipynb) |Demo 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3_colab.ipynb) | [![View the notebook](https://img.shields.io/badge/render-nbviewer-orange.svg)](https://nbviewer.jupyter.org/github/ZitongLu1996/NeuroRA/blob/master/demo/NeuroRA_Demo3.ipynb) |## About NeuroRANoteworthily, this toolbox is currently only atest version.
If you have any question, find some bugs or have some useful suggestions while using, you can email me and I will be happy and thankful to know.
>My email address:
>zitonglu1996@gmail.com /zitonglu@outlook.com>My personal homepage:
>https://zitonglu1996.github.io