NeuroImage: ClinicalNeurosciencePeer-reviewed journal article
Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development
Luke Stoeckel, Kathleen A. Garrison, Satrajit S Ghosh, Paul Wighton, Colleen A. Hanlon, Jodi M. Gilman, Stephanie Greer, Nicholas B. Turk-Browne, Megan T. deBettencourt, Dustin ScheinostiD, Cameron CraddockiD, Todd Thompson, Vanessa Calderon, Clemens C. Bauer, Mark George, Hans C. Breiter, Susan Whitfield-Gabrieli, John D. Gabrieli, Stephen M. LaConte, Laurence M. Hirshberg, Judson A. Brewer, Michelle HampsoniD, Andre Van Der Kouwe, Sean Mackey, Anne E Evins
Abstract
While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health (BRAIN, 2013), the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Towards Semantic fMRI Neurofeedback: Navigating among Mental States using Real-time Representational Similarity Analysis
Andrea Gerardo Russo, Michael Lührs, … Rainer Goebel·Journal of Neural EngineeringPeer-reviewed·Mar 8, 2021
- Single Session Real-time fMRI Neurofeedback has a Lasting Impact on Cognitive Behavioral Therapy Strategies
Katherine E. MacDuffie, Jeff MacInnes, … R. Alison Adcock·NeuroImage ClinicalPeer-reviewed·Jan 1, 2018
- Determinants of Real-Time fMRI Neurofeedback Performance and Improvement: a Machine Learning Mega-Analysis
Amelie Haugg, Fabian M. Renz, … David Steyrl·bioRxiv·Oct 21, 2020
- Real-time neurofeedback to alter interpretations of a naturalistic narrative
Anne C. Mennen, Samuel A. Nastase, … Kenneth A. Norman·Neuroimage ReportsPeer-reviewed·Jul 2, 2022
- Connectome-wide search for functional connectivity locus associated with pathological rumination as a target for real-time fMRI neurofeedback intervention
Masaya Misaki, Aki Tsuchiyagaito, … Tulsa 1000 Investigators·NeuroImage ClinicalPeer-reviewed·Jan 1, 2020
- Whole-brain Mechanism of Neurofeedback Therapy: Predictive Modeling of Neurofeedback Outcomes on Repetitive Negative Thinking in Depression
Masaya Misaki, Aki Tsuchiyagaito, … Martin P. Paulus·Translational PsychiatryPeer-reviewed·Sep 3, 2024