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Neuroimage Clin. 2014 Jul 10;5:245-55. doi: 10.1016/j.nicl.2014.07.002. eCollection 2014.

Optimizing real time fMRI neurofeedback for therapeutic discovery and development.

Author information

1
Massachusetts General Hospital, Department of Psychiatry, USA ; Harvard Medical School, USA ; Athinoula A. Martinos Center, USA ; McGovern Institute for Brain Research, Massachusetts Institute of Technology, USA.
2
Yale University School of Medicine, Department of Psychiatry, USA.
3
McGovern Institute for Brain Research, Massachusetts Institute of Technology, USA.
4
Athinoula A. Martinos Center, USA ; Massachusetts General Hospital, Department of Radiology, USA.
5
Department of Psychiatry, Medical University of South Carolina, USA.
6
Massachusetts General Hospital, Department of Psychiatry, USA ; Harvard Medical School, USA ; Athinoula A. Martinos Center, USA.
7
Department of Neuroscience, University of California, Berkeley, USA.
8
Department of Psychology, Princeton University, USA.
9
Princeton Neuroscience Institute, Princeton University, USA.
10
Department of Diagnostic Radiology, Yale University School of Medicine, USA.
11
Child Mind Institute, USA.
12
Massachusetts General Hospital, Department of Psychiatry, USA.
13
Universidad Nacional Autonoma de Mexico, Instituto de Neurobiologia, Mexico.
14
Massachusetts General Hospital, Department of Psychiatry, USA ; Northwestern University Feinberg School of Medicine, Department of Psychiatry and Behavioral Sciences, USA.
15
School of Biomedical Engineering and Sciences, Virginia Tech, USA ; Virginia Tech Carilion Research Institute, USA.
16
Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, USA.
17
Yale University School of Medicine, Department of Psychiatry, USA ; Department of Medicine and Psychiatry, University of Massachusetts Medical School, USA.
18
Department of Anesthesia, Stanford University School of Medicine, USA.
19
Massachusetts General Hospital, Department of Psychiatry, USA ; Harvard Medical School, USA.

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.

KEYWORDS:

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

PMID:
25161891
PMCID:
PMC4141981
DOI:
10.1016/j.nicl.2014.07.002
[Indexed for MEDLINE]
Free PMC Article

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