Costanza Iester, Clint Banzhaf, Ahmed Eldably, Betti Schopp, Andreas J Fallgatter, Laura Bonzano, Marco Bove, Ann-Christine Ehlis, Beatrix Barth
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However, there is a lack of freely accessible tools for research in this area that reflect the state of the art in research and technology.</p><p><strong>Aim: </strong>To address this need, we introduce Non-commercial Interface for Neuro-Feedback Acquisitions (NINFA), a user-friendly and flexible freely available neurofeedback application for real-time fNIRS, which is also open to other modalities such as electroencephalography (EEG).</p><p><strong>Approach: </strong>NINFA was developed in MATLAB and the lab streaming layer connection offers maximum flexibility in terms of combination with different fNIRS or EEG acquisition software and hardware.</p><p><strong>Results: </strong>The user-friendly interface allows measurements without requiring programming expertise. New neurofeedback protocols can be easily created, saved, and retrieved. We provide an example code for real-time data preprocessing and visual feedback; however, users can customize or expand it with appropriate programming skills.</p><p><strong>Conclusions: </strong>NINFA enables real-time recording, analysis, and feedback of brain signals. We were able to demonstrate the stability and reliability of the computational performance of preprocessing and analysis methods in the current version. NINFA is intended as an application that can, should, and may evolve with the help of contributions from the community.</p>","PeriodicalId":54335,"journal":{"name":"Neurophotonics","volume":"12 2","pages":"026601"},"PeriodicalIF":4.8000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12077575/pdf/","citationCount":"0","resultStr":"{\"title\":\"NINFA: Non-commercial interface for neuro-feedback acquisitions.\",\"authors\":\"Costanza Iester, Clint Banzhaf, Ahmed Eldably, Betti Schopp, Andreas J Fallgatter, Laura Bonzano, Marco Bove, Ann-Christine Ehlis, Beatrix Barth\",\"doi\":\"10.1117/1.NPh.12.2.026601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Significance: </strong>In recent years, functional near-infrared spectroscopy (fNIRS) has gained increasing attention in the field of neurofeedback. However, there is a lack of freely accessible tools for research in this area that reflect the state of the art in research and technology.</p><p><strong>Aim: </strong>To address this need, we introduce Non-commercial Interface for Neuro-Feedback Acquisitions (NINFA), a user-friendly and flexible freely available neurofeedback application for real-time fNIRS, which is also open to other modalities such as electroencephalography (EEG).</p><p><strong>Approach: </strong>NINFA was developed in MATLAB and the lab streaming layer connection offers maximum flexibility in terms of combination with different fNIRS or EEG acquisition software and hardware.</p><p><strong>Results: </strong>The user-friendly interface allows measurements without requiring programming expertise. New neurofeedback protocols can be easily created, saved, and retrieved. 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NINFA: Non-commercial interface for neuro-feedback acquisitions.
Significance: In recent years, functional near-infrared spectroscopy (fNIRS) has gained increasing attention in the field of neurofeedback. However, there is a lack of freely accessible tools for research in this area that reflect the state of the art in research and technology.
Aim: To address this need, we introduce Non-commercial Interface for Neuro-Feedback Acquisitions (NINFA), a user-friendly and flexible freely available neurofeedback application for real-time fNIRS, which is also open to other modalities such as electroencephalography (EEG).
Approach: NINFA was developed in MATLAB and the lab streaming layer connection offers maximum flexibility in terms of combination with different fNIRS or EEG acquisition software and hardware.
Results: The user-friendly interface allows measurements without requiring programming expertise. New neurofeedback protocols can be easily created, saved, and retrieved. We provide an example code for real-time data preprocessing and visual feedback; however, users can customize or expand it with appropriate programming skills.
Conclusions: NINFA enables real-time recording, analysis, and feedback of brain signals. We were able to demonstrate the stability and reliability of the computational performance of preprocessing and analysis methods in the current version. NINFA is intended as an application that can, should, and may evolve with the help of contributions from the community.
期刊介绍:
At the interface of optics and neuroscience, Neurophotonics is a peer-reviewed journal that covers advances in optical technology applicable to study of the brain and their impact on the basic and clinical neuroscience applications.