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Related Experiment Video

Updated: Jun 17, 2026

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
07:05

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training

Published on: August 24, 2017

The DecNef collection, fMRI data from closed-loop decoded neurofeedback experiments.

Aurelio Cortese1, Saori C Tanaka2, Kaoru Amano2,3

  • 1Computational Neuroscience Labs, ATR Institute International, 619-0288, Kyoto, Japan. cortese.aurelio@gmail.com.

Scientific Data
|February 24, 2021
PubMed
Summary

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This summary is machine-generated.

This study releases a public dataset for decoded neurofeedback (DecNef) using functional magnetic resonance imaging (fMRI). The data enables research into non-invasive brain modulation techniques and machine learning decoder development.

Area of Science:

  • Neuroscience
  • Machine Learning
  • Medical Imaging

Background:

  • Decoded neurofeedback (DecNef) combines functional magnetic resonance imaging (fMRI) with machine learning for brain modulation.
  • Limited public datasets hinder research into DecNef mechanisms and clinical applications.

Purpose of the Study:

  • To release a comprehensive public dataset from DecNef studies.
  • To facilitate research on non-invasive brain dynamics modulation.
  • To support the development and validation of machine learning decoders for neurofeedback.

Main Methods:

  • The dataset comprises 5 separate fMRI datasets from multiple DecNef studies.
  • Each participant has data from a decoder training session and multiple closed-loop neural reinforcement sessions.

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Last Updated: Jun 17, 2026

A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
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  • Data includes over 60 participants, with ongoing additions from new studies.

    • Main Results:

    • A large, publicly accessible dataset for DecNef research is now available.
    • The dataset supports analysis of factors influencing brain dynamics manipulation.
    • Facilitates understanding of closed-loop fMRI and machine learning interactions.

    Conclusions:

    • The released DecNef dataset is a valuable resource for the fMRI and neuroscience communities.
    • It will accelerate research into the mechanisms of non-invasive brain modulation.
    • Encourages further investigation into the clinical potential of DecNef.