Citation

Li J, Duan X, Cui Q, Chen H, Liao W. Psychol. Med. 2019; 49(5): 852-860.

Affiliation

The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China,Chengdu 610054,P.R. China.

Copyright

(Copyright © 2019, Cambridge University Press)

DOI

10.1017/S0033291718001502

PMID

29909788

Abstract

BACKGROUND: Major depressive disorder (MDD) is associated with high risk of suicide. Conventional neuroimaging works showed abnormalities of static brain activity and connectivity in MDD with suicidal ideation (SI). However, little is known regarding alterations of brain dynamics. More broadly, it remains unclear whether temporal dynamics of the brain activity could predict the prognosis of SI.

METHODS: We included MDD patients (n = 48) with and without SI and age-, gender-, and education-matched healthy controls (n = 30) who underwent resting-state functional magnetic resonance imaging. We first assessed dynamic amplitude of low-frequency fluctuation (dALFF) - a proxy for intrinsic brain activity (iBA) - using sliding-window analysis. Furthermore, the temporal variability (dynamics) of iBA was quantified as the variance of dALFF over time. In addition, the prediction of the severity of SI from temporal variability was conducted using a general linear model.

RESULTS: Compared with MDD without SI, the SI group showed decreased brain dynamics (less temporal variability) in the dorsal anterior cingulate cortex, the left orbital frontal cortex, the left inferior temporal gyrus, and the left hippocampus. Importantly, these temporal variabilities could be used to predict the severity of SI (r = 0.43, p = 0.03), whereas static ALFF could not in the current data set.

CONCLUSIONS: These findings suggest that alterations of temporal variability in regions involved in executive and emotional processing are associated with SI in MDD patients. This novel predictive model using the dynamics of iBA could be useful in developing neuromarkers for clinical applications.

Language: en

Keywords

Amplitude of low-frequency fluctuations; dynamics; intrinsic brain activity; major depression; predictive model; suicidal ideation