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Real-time fMRI neurofeedback: the promising potential of brain-training technology to advance clinical neuroscience

Neuropsychopharmacology (2022)Cite this article

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Although functional magnetic resonance imaging (fMRI) has advanced our understanding of the organization of the brain with the discovery of large-scale networks, the impact of this knowledge on the diagnosis and treatment of psychiatric conditions has yet to be fully realized. The development of real-time fMRI neurofeedback (rtfMRI-NF) provides a promising avenue by which fMRI might enter the clinic. First described two decades ago, the field has matured substantially, with specialized conferences, randomized clinical trials, and multisite consortia. A recent consensus statement outlines methodological approaches and important challenges [1]. A substantial evidence base describes applications in psychiatric [2] and substance use disorders [3]. The first meta-analysis of rtfMRI-NF for psychiatric disorders [2] in 17 studies meeting criteria for inclusion in the analysis recently reported a strong effect size for ‘transfer,’ which is to say—the demonstration that NF-trained subjects can maintain the ability to regulate neural signal in the absence of feedback—in comparison to subjects trained with sham/control feedback, (Hedges g = 0.84, p = 0.005). This analysis demonstrates the feasibility of rtfMRI-NF training for psychiatric patients, 52.9% of whom were taking medications. However, the effect on behavioral outcomes in this heterogeneous group was modest (overall symptoms: g = 0.37, p = 0.002; cognition: g = 0.23, p = 0.288). It should be noted that the studies conducted training for an average of only 2.3 sessions (range = 1–4), and this line of investigation opens some promising avenues where the techniques could be refined and improved to generate more robust clinical outcomes.

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References

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Funding

SFT is supported by NIMH (R01MH118634, R01MH120588, R21MH120633) and the Milken Institute/The Bessemer Giving Fund. MEM is supported by NIAAA (K01AA027558).

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  1. Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA

    Stephan F. Taylor & Meghan E. Martz

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  1. Stephan F. Taylor
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  2. Meghan E. Martz
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SFT and MEM wrote the manuscript.

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Correspondence to Stephan F. Taylor.

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Competing interests

SFT is a member of the editorial board of Neuropsychopharmacology. He has received compensation for advisory board/data safety and monitor board service for several NIH-funded studies and for the Prechter Bipolar Research Program. He has also served as principal investigator for a contracted clinical trial for Boehringer Ingelheim. MEM has no potential competing interests.

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Taylor, S.F., Martz, M.E. Real-time fMRI neurofeedback: the promising potential of brain-training technology to advance clinical neuroscience. Neuropsychopharmacol. (2022). https://doi.org/10.1038/s41386-022-01397-z

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  • DOI: https://doi.org/10.1038/s41386-022-01397-z

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