In this critical review, the authors appraise neuroimaging findings in bipolar disorder in emotion-processing, emotion-regulation, and reward-processing neural circuitry in order to synthesize the current knowledge of the neural underpinnings of bipolar disorder and provide a neuroimaging research road map for future studies.
The authors examined findings from all major studies in bipolar disorder that used functional MRI, volumetric analysis, diffusion imaging, and resting-state techniques, integrating findings to provide a better understanding of larger-scale neural circuitry abnormalities in bipolar disorder.
Bipolar disorder can be conceptualized, in neural circuitry terms, as parallel dysfunction in prefrontal cortical (especially ventrolateral prefrontal cortical)-hippocampal-amygdala emotion-processing and emotion-regulation circuits bilaterally, together with an “overactive” left-sided ventral striatal-ventrolateral and orbitofrontal cortical reward-processing circuitry, resulting in characteristic behavioral abnormalities associated with bipolar disorder: emotional lability, emotional dysregulation, and heightened reward sensitivity. A potential structural basis for these functional abnormalities is gray matter volume decreases in the prefrontal and temporal cortices, the amygdala, and the hippocampus and fractional anisotropy decreases in white matter tracts connecting prefrontal and subcortical regions.
Neuroimaging studies of bipolar disorder clearly demonstrate abnormalities in neural circuits supporting emotion processing, emotion regulation, and reward processing, although there are several limitations to these studies. Future neuroimaging research in bipolar disorder should include studies adopting dimensional approaches; larger studies examining neurodevelopmental trajectories in youths with bipolar disorder or at risk for bipolar disorder; multimodal neuroimaging studies using integrated systems approaches; and studies using pattern recognition approaches to provide clinically useful individual-level data. Such studies will help identify clinically relevant biomarkers to guide diagnosis and treatment decision making for individuals with bipolar disorder.