NeuroRA

A Python Toolbox for Multimode Neural Data Representation Analysis - A Representational Analysis Toolbox for Neuroscience, including Neural Pattern Similarity (NPS), Representational Similarity Analysis (RSA), Spatiotemporal Pattern Similarity (STPS) & Inter-Subject Correlation (ISC)

View the Project on GitHub ZitongLu1996/NeuroRA

NeuroRA

A Python Toolbox of Representational Analysis from Multimodal 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, sEEG, ECoG, fMRI and some other neuroelectrophysiological data. In addition, users can do Neural Pattern Similarity (NPS), Spatiotemporal Pattern Similarity (STPS), Inter-Subject Correlation (ISC) & Classification-based EEG Decoding on NeuroRA.

Paper

Lu, 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

Installation

pip install neurora

Documentation

You can read the Documentation here or download the Tutorial here.

Required Dependencies:

Features

Typical schematic diagrams

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Script Demos to Know How to Use

There are two demos in Tutorial to let you know how to use NeuroRA to conduct representational analysis.

  Run the Demo View the Demo
Demo 1 Open In Colab View the notebook
Demo 2 Open In Colab View the notebook
Demo 3 Open In Colab View the notebook

Users can see more details from Demo Codes.

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

My personal homepage: https://zitonglu1996.github.io