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Related Experiment Video

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NINFA: Non-commercial interface for neuro-feedback acquisitions.

Costanza Iester1, Clint Banzhaf2, Ahmed Eldably3,4

  • 1University of Genoa, Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Genoa, Italy.

Neurophotonics
|May 15, 2025
PubMed
Summary

Researchers developed Non-commercial Interface for Neuro-Feedback Acquisitions (NINFA), a free neurofeedback tool for functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). NINFA offers real-time analysis and feedback, enhancing neurofeedback research accessibility.

Keywords:
functional near-infrared spectroscopyneurofeedbackreal-time application

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Area of Science:

  • Neuroscience
  • Biomedical Engineering

Background:

  • Functional near-infrared spectroscopy (fNIRS) is increasingly used in neurofeedback research.
  • A significant gap exists in freely accessible, state-of-the-art neurofeedback tools for fNIRS and related modalities.

Purpose of the Study:

  • To introduce Non-commercial Interface for Neuro-Feedback Acquisitions (NINFA), an open-source neurofeedback application.
  • To provide a user-friendly and flexible platform for real-time fNIRS and electroencephalography (EEG) neurofeedback research.

Main Methods:

  • NINFA is developed in MATLAB, utilizing Lab Streaming Layer for broad compatibility with fNIRS/EEG hardware and software.
  • Features a user-friendly interface requiring no programming expertise for basic operation.
  • Includes example code for real-time data preprocessing and visual feedback, with options for customization.

Main Results:

  • NINFA enables real-time recording, analysis, and feedback of brain signals.
  • Demonstrated stability and reliability in computational performance for preprocessing and analysis.
  • The application is designed for community-driven evolution and expansion.

Conclusions:

  • NINFA addresses the need for accessible neurofeedback tools in fNIRS research.
  • It offers a flexible, user-friendly platform for real-time brain signal analysis and feedback.
  • Encourages community contributions to advance the application's capabilities.