ArticleNeuroImage2019
A framework for offline evaluation and optimization of real-time algorithms for use in neurofeedback, demonstrated on an instantaneous proxy for correlations.
Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Real-time fMRI neurofeedback boosts heartbeat perception by modulating insula activation pattern during interoceptive attention.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Reducing default mode network connectivity with mindfulness-based fMRI neurofeedback: a pilot study among adolescents with affective disorder history.Molecular psychiatry · 2023Article
- Closed-loop neuromodulation for studying spontaneous activity and causality.Trends in cognitive sciences · 2022Review
- A Library for fMRI Real-Time Processing Systems in Python (RTPSpy) With Comprehensive Online Noise Reduction, Fast and Accurate Anatomical Image Processing, and Online Processing Simulation.Frontiers in neuroscience · 2022Article
- Conducting decoded neurofeedback studies.Social cognitive and affective neuroscience · 2021Article
- Prevent breaking bad: A proof of concept study of rebalancing the brain's rumination circuit with real-time fMRI functional connectivity neurofeedback.Human brain mapping · 2021Article
- Quality and denoising in real-time functional magnetic resonance imaging neurofeedback: A methods review.Human brain mapping · 2020Review
- Connectome-wide search for functional connectivity locus associated with pathological rumination as a target for real-time fMRI neurofeedback intervention.NeuroImage. Clinical · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Interest in real-time fMRI neurofeedback has grown exponentially over the past few years, both for use as a basic science research tool, and as part of the search for novel clinical interventions for neurological and psychiatric illnesses. In order to expand the range of questions which can be addressed with this tool however, new neurofeedback methods must be developed, going beyond feedback of activations in a single region. These new methods, several of which have already been proposed, are by their nature complex, involving many possible parameters. Here we suggest a framework for evaluating and optimizing algorithms for use in a real-time setting, before beginning the neurofeedback experiment, by offline simulations of algorithm output using a previously collected dataset. We demonstrate the application of this framework on the instantaneous proxy for correlations which we developed for training connectivity between different network nodes, identify the optimal parameters for use with this algorithm, and compare it to more traditional correlation methods. We also examine the effects of advanced imaging techniques, such as multi-echo acquisition, and the integration of these into the real-time processing stream.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.