Differentiating between bipolar and unipolar depression in functional and structural MRI studies

Mar 31, 2018Progress in neuro-psychopharmacology & biological psychiatry

Brain imaging differences between bipolar and unipolar depression

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Circadian Biology on OpenScience ↗PubMed ↗DOI ↗

Abstract

Distinct neural markers may help differentiate bipolar disorder depression from unipolar depression.

Numerous studies indicate different activation patterns in brain regions, including the amygdala and prefrontal cortex, during emotion- and cognition-related tasks between bipolar disorder and unipolar depression.
Bipolar disorder shows a stronger functional connectivity in default mode and frontoparietal networks compared to unipolar depression.
Differences in gray matter volume have been observed in regions such as the anterior cingulate cortex and hippocampus between bipolar and unipolar depression.
Bipolar disorder is associated with a thinner dorsolateral prefrontal cortex compared to unipolar depression.
Reduced integrity of the anterior part of the corpus callosum and posterior cingulum has been reported in bipolar disorder relative to unipolar depression.
Pattern classification analyses using neuroimaging data have achieved a moderate level of accuracy in distinguishing between bipolar and unipolar depression.

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Distinguishing depression in bipolar disorder (BD) from unipolar depression (UD) solely based on clinical clues is difficult, which has led to the exploration of promising neural markers in neuroimaging measures for discriminating between BD depression and UD. In this article, we review structural and functional magnetic resonance imaging (MRI) studies that directly compare UD and BD depression based on neuroimaging modalities including functional MRI studies on regional brain activation or functional connectivity, structural MRI on gray or white matter morphology, and pattern classification analyses using a machine learning approach. Numerous studies have reported distinct functional and structural alterations in emotion- or reward-processing neural circuits between BD depression and UD. Different activation patterns in neural networks including the amygdala, anterior cingulate cortex (ACC), prefrontal cortex (PFC), and striatum during emotion-, reward-, or cognition-related tasks have been reported between BD and UD. A stronger functional connectivity pattern in BD was pronounced in default mode and in frontoparietal networks and brain regions including the PFC, ACC, parietal and temporal regions, and thalamus compared to UD. Gray matter volume differences in the ACC, hippocampus, amygdala, and dorsolateral prefrontal cortex (DLPFC) have been reported between BD and UD, along with a thinner DLPFC in BD compared to UD. BD showed reduced integrity in the anterior part of the corpus callosum and posterior cingulum compared to UD. Several studies performed pattern classification analysis using structural and functional MRI data to distinguish between UD and BD depression using a supervised machine learning approach, which yielded a moderate level of accuracy in classification.

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Differentiating between bipolar and unipolar depression in functional and structural MRI studies

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