Abstract
Studies comparing diverse groups have shown that many psychiatric diseases involve disruptions across distributed large-scale networks of the brain. There is hope that functional magnetic resonance imaging (fMRI) functional connectivity techniques will shed light on these disruptions, providing prognostic and diagnostic biomarkers as well as targets for therapeutic interventions. However, to date, progress on clinical translation of fMRI methods has been limited. Here, we argue that this limited translation is driven by a combination of intersubject heterogeneity and the relatively low reliability of standard fMRI techniques at the individual level. We review a potential solution to these limitations: the use of new “precision” fMRI approaches that shift the focus of analysis from groups to single individuals through the use of extended data acquisition strategies. We begin by discussing the potential advantages of fMRI functional connectivity methods for improving our understanding of functional neuroanatomy and disruptions in psychiatric disorders. We then discuss the budding field of precision fMRI and findings garnered from this work. We demonstrate that precision fMRI can improve the reliability of functional connectivity measures, while showing high stability and sensitivity to individual differences. We close by discussing the application of these approaches to clinical settings.
Original language | English (US) |
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Pages (from-to) | 28-39 |
Number of pages | 12 |
Journal | Biological psychiatry |
Volume | 88 |
Issue number | 1 |
DOIs | |
State | Published - Jul 1 2020 |
Funding
This research was supported by a McDonnell Foundation Collaborative Activity Award (to SEP); National Institutes of Health Grant Nos. R01MH118370 (to CG), K01MH104592 (to DJG), NS088590 (to NUFD), R25MH112473 (to TOL), and T32NS047987 (to BTK); and a Career Development Award No. 1IK2CX001680 (to EMG) from the U.S. Department of Veterans Affairs Clinical Sciences Research and Development Service. This research was supported by a McDonnell Foundation Collaborative Activity Award (to SEP); National Institutes of Health Grant Nos. R01MH118370 (to CG), K01MH104592 (to DJG), NS088590 (to NUFD), R25MH112473 (to TOL), and T32NS047987 (to BTK); and a Career Development Award No. 1IK2CX001680 (to EMG) from the U.S. Department of Veterans Affairs Clinical Sciences Research and Development Service. The contents of this manuscript do not represent the views of the U.S. Department of Veterans Affairs or the United States Government. NUFD has a financial interest in Nous Imaging Inc. and may financially benefit if the company is successful in marketing FIRMM software products. NUFD may receive royalty income based on FIRMM technology developed at Oregon Health and Sciences University and Washington University and licensed to Nous Imaging Inc. TOL is a patent holder on US Patent Applications 16/136,996 ?System and method for task-less mapping of brain activity? and 16/141,605 ?Supervised classifier for optimizing target for neuromodulation, implant localization, and ablation.? The other authors report no biomedical financial interests or potential conflicts of interest.
Keywords
- Brain networks
- Functional connectivity
- Individual differences
- Precision imaging
- Reliability
- fMRI
ASJC Scopus subject areas
- Biological Psychiatry