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More than just statics: temporal dynamics of intrinsic brain activity predicts the suicidal ideation in depressed patients

Published online by Cambridge University Press:  18 June 2018

Jiao Li ,
Xujun Duan ,
Qian Cui ,
Huafu Chen  and
Wei Liao Open the ORCID record for Wei Liao [Opens in a new window]
Jiao Li
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 School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
Xujun Duan
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 School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
Qian Cui
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 School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
Huafu Chen
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 School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
Wei Liao*
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 School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, P.R. China
*
Author for correspondence: Wei Liao, E-mail: [email protected]
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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.

Keywords

Amplitude of low-frequency fluctuationsdynamicsintrinsic brain activitymajor depressionpredictive modelsuicidal ideation
Type
Original Articles
Information
Psychological Medicine , Volume 49 , Issue 5 , April 2019 , pp. 852 - 860
Copyright
Copyright © Cambridge University Press 2018 

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