Resting-state functional connectivity represents the temporal coherence of the BOLD (blood oxygen level dependent)-signal within or between regions or networks during rest, and is an important noninvasive functional imaging technique in mapping the whole brain network affected in depression. Although advances have been made in identifying neural networks involved in depression, this information has yet to be translated into improved diagnostic or treatment interventions. In the first section of this review, we discuss dysfunctional connectivity in cognitive control, affective salience, and default mode networks observed in depression. We also address whether aberrant resting functional connectivity patterns can be used in discriminant analysis for the diagnosis of depression. In the second section, we discuss how fMRI neurofeedback involves presenting individuals with feedback about their patterns of neural activation in real time in order for them to learn to control specific brain processes. Furthermore, we provide a comprehensive review of the literature on fMRI neurofeedback studies of depression. Finally, we discuss possible avenues of future research to develop more effective neurofeedback guided by functional connectivity dysfunction in patients with depression. Although using functional neuroimaging for the diagnosis and treatment of depressed individuals is still relatively novel, we conclude by proposing, with cautious optimism, the future incorporation of neuroimaging into clinical practice as a tool to aid in diagnosis and treatment.
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