More than just statics: temporal dynamics of intrinsic brain activity predicts the suicidal ideation in depressed patients
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.
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Other studies have reported lower rs-fMRI activity and functional connectivity, probably due to different outcome measures and heterogeneity of suicidal ideation.
“However, other studies have reported lower rs-fMRI activity and functional connectivity (85, 86, 92, 93), probably due to use of different outcome measures of rs-fMRI activity, for example, regional homogeneity, fractional amplitude of low-frequency fluctuations among studies, and heterogeneity of suicidal ideation.”
From A brain-centric model of suicidal behavior (2020) · cites this paper as [93]
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- Authors
- Li, J., Duan, X., Cui, Q., Chen, H., & Liao, W.
- Affiliations
- University of Electronic Science and Technology of China (CN)
- Corresponding author
- Liao, Wei
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2018-06-18
- Volume
- 49
- Issue
- 5
- Pages
- 852-860
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- OpenAlex
- W2809054788
- Cited by
- 208
- References
- 80
- Citations by year
- 2026: 14 · 2025: 26 · 2024: 17 · 2023: 30 · 2022: 31 · 2021: 36 · 2020: 37 · 2019: 15 · 2018: 2
- FWCI
- 13.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Higher Education Discipline Innovation Project
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
- Keywords
- suicidal ideation, major depressive disorder, intrinsic brain activity, dynamic amplitude of low-frequency fluctuation, temporal dynamics of brain activity, resting-state functional connectivity, dorsal anterior cingulate cortex, orbitofrontal cortex, hippocampus, inferior temporal gyrus, neuromarkers, suicide risk prediction
- MeSH terms
- Adult, Brain Mapping, Cerebral Cortex, Major Depressive Disorder, Depressive Disorder, Major, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Linear Models, Young Adult, Suicidal Ideation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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