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Aberrant Temporal Variability in Brain Regions during Risk Decision Making in Patients with Bipolar I Disorder: A Dynamic Effective Connectivity Study

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Bipolar I disorder (BD-I) is associated with high-risk behaviors, such as suicide attempts and addictive substance abuse. Understanding brain activity exposure to risk decision making provides evidence for the treatment… Click to show full abstract

Bipolar I disorder (BD-I) is associated with high-risk behaviors, such as suicide attempts and addictive substance abuse. Understanding brain activity exposure to risk decision making provides evidence for the treatment of BD-I patients. This study aimed to investigate the temporal dynamics of brain connectivity underlying risk decision making in patients with BD-I. A total of 101 subjects (48 BD-I patients and 53 age- and gender-matched healthy controls) were included in this research. We analyzed the fMRI data acquired during Balloon Analog Risk Task (BART) performance. Voxel-wise dynamic effective connectivity (dEC) was employed to measure the activities in 264 brain regions. The coefficient of variation (CV) was calculated as temporal dynamics of brain connectivity. Finally, we used structural equation modeling (SEM) to determine the relationships of dEC in brain regions with clinical symptoms, behavior performances in patients. Results showed that BD-I patients exhibited increased dynamics in four lobes and exhibited decreased in three frontal regions. Besides, SEM results showed that the impulsive symptoms of patients were affected by the dEC during both resting and task states. Moreover, the dEC of left supramarginal gyrus (SMG) influenced those of left orbital frontal and right cuneus, as well as the affective symptoms and BART behaviors in patients with BD-I. Our results suggested that the altered temporal dynamics of brain connectivity might contribute to the impulsivity of BD-I during resting and task states. More importantly, the left SMG might be a therapeutic target to reduce the risk behavior in BD-I patients.

Keywords: connectivity; risk decision; brain regions; decision making; brain

Journal Title: Neuroscience
Year Published: 2021

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