A Python Toolbox for Multimode Neural Data Representation Analysis
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#NeuroRA
A Python Toolbox of Representational Analysis from Multimode Neural Data
## Overview Representational Similarity Analysis (RSA) has become a popular and effective method to measure the representation of multivariable neural activity in different modes.
NeuroRA is an easy-to-use toolbox based on Python, which can do some works about RSA among nearly all kinds of neural data, including behavioral, EEG, MEG, fNIRS, ECoG, electrophysiological and fMRI data.
## Installation > pip install neurora
## Website & How to use See more details at the [NeuroRA website](https://zitonglu1996.github.io/NeuroRA/).
You can read 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.
[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
## Features
Calculate the Neural Pattern Similarity (NPS)
Calculate the Spatiotemporal Neural Pattern Similarity (STPS)
Calculate the Representational Dissimilarity Matrix (RDM)
Calculate the Representational Similarity based on RDMs
One-Step Realize Representational Similarity Analysis (RSA)
Save the RSA result as a NIfTI file for fMRI
Visualization for RSA results
## Paper
Lu, Z., & Ku, Y. NeuroRA: A Python toolbox of representational analysis from multi-modal neural data. (bioRxiv: https://doi.org/10.1101/2020.03.25.008086)
## About NeuroRA Noteworthily, this toolbox is currently only a test 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
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