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Quality and denoising in real-time fMRI neurofeedback - a methods review

This repository contains code and data related to the manuscript: Quality and denoising in real-time fMRI neurofeedback - a methods review (link to preprint)

Summary of the manuscript

The work investigated the state of denoising methods used in the field of fMRI neurofeedback. It specifically looked at the acquisition and processing tools that are available to researchers applying fMRI neurofeedback to help them improve the quality of the BOLD and neurofeedback signals. Furthermore, it investigated the reporting practices of a set of 128 recently published studies applying neurofeedback in both healthy and patient populations.

This repository contains:

  • A Jupyter notebook for reproducing the main figures (Fig 6 and Fig7 A-H) in the manuscript
  • Matlab code for reproducing earlier versions the figures in the manuscript
  • The coded data (tab delimited text files) for methods used in 128 real-time fMRI neurofeedback studies
  • A Jupyter notebook with which to interactively explore the data

Explore the data from your browser:

You don't have to install any software to explore the data. This interactive dashboard allows you to explore and visualize the review data:

Dashboard

The following Binder environment will allow you to interact with the code, data, and visualizations via a Jupyter notebook:

Binder

This Binder environment displays the previous notebook as an interactive webpage:

Binder

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This repository contains code and data for reproducing the figures in the manuscript: https://osf.io/xubhq

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