• Takashi Yamada, Ryu-Ichiro Hashimoto, Noriaki Yahata, Naho Ichikawa, Yujiro Yoshihara, Yasumasa Okamoto, Nobumasa Kato, Hidehiko Takahashi, and Mitsuo Kawato.
• Department of Decoded Neurofeedback, ATR Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan; Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan; Department of Language Sciences, Graduate School of Humanities, and Research Center for Language, Brain and Genetics, Tokyo Metropolitan University, Tokyo, Japan; Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan; Department of Youth Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Psychiatry and Neurosciences, Graduate School of Biomedical Sciences, Hiroshima University, Hiroshima, Japan; Department of Psychiatry, Kyoto University Graduate School of Medicine, Kyoto, Japan.
• Int. J. Neuropsychopharmacol. 2017 Oct 1; 20 (10): 769-781.

AbstractPsychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use.© The Author 2017. Published by Oxford University Press on behalf of CINP.

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