Optimizing real time fMRI neurofeedback for therapeutic discovery and development

L. E. Stoeckel, K. A. Garrison, S. Ghosh, P. Wighton, C. A. Hanlon, J. M. Gilman, S. Greer, N. B. Turk-Browne, M. T. Debettencourt, D. Scheinost, C. Craddock, T. Thompson, V. Calderon, C. C. Bauer, M. George, H. C. Breiter, S. Whitfield-Gabrieli, J. D. Gabrieli, S. M. Laconte, L. HirshbergJ. A. Brewer, M. Hampson, A. Van Der Kouwe, S. MacKey, A. E. Evins

Research output: Contribution to journalReview articlepeer-review

146 Scopus citations

Abstract

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health, 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.

Original languageEnglish (US)
Pages (from-to)245-255
Number of pages11
JournalNeuroImage: Clinical
Volume5
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Clinical Neurology
  • Neurology
  • Cognitive Neuroscience
  • Radiology Nuclear Medicine and imaging

Keywords

  • Brain-computer interface
  • Neurofeedback
  • Neurotherapeutic
  • Real time fMRI

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