ArticleBiological psychiatry. Cognitive neuroscience and neuroimaging2020
Diagnostic and Predictive Neuroimaging Biomarkers for Posttraumatic Stress Disorder.
Article in Biological psychiatry. Cognitive neuroscience and neuroimaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.
- PTSD subtypes and their underlying neural biomarkers: a systematic review.Psychological medicine · 2025Pooled it
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- Hyperbaric Oxygen Therapy for PTSD: Threshold Effect for Sustained Symptom Improvement in a Biologically Based Treatment.Brain and behavior · 2025Trial
- Article
- Plasma copeptin is coupled to resting-state frontoinsular-subgenual alpha dynamics in major depression with comorbid post-traumatic stress disorder.Frontiers in endocrinology · 2026Article
- Individual-Specific Animated Profiles of Mental Health.Perspectives on psychological science : a journal of the Association for Psychological Science · 2025Article
- An individual-specific understanding of how synchrony becomes curative: study protocol.BMC psychiatry · 2025Article
- Article
- Translational bioinformatics and data science for biomarker discovery in mental health: an analytical review.Briefings in bioinformatics · 2024Review
- Common and divergent neuroimaging features in major depression, posttraumatic stress disorder, and their comorbidity.Psychoradiology · 2024Review
- Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.NeuroImage · 2023Article
- Systematic review of machine learning in PTSD studies for automated diagnosis evaluation.Npj mental health research · 2023Review
- Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry.BMC medicine · 2023Article
- Elucidating behavioral and functional connectivity markers of aberrant threat discrimination in PTSD.Depression and anxiety · 2022Article
- Cortico-Striatal Activity Characterizes Human Safety Learning via Pavlovian Conditioned Inhibition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022Article
- Identifying Neurobiological Markers of Posttraumatic Stress Disorder Using Resting-State Functional Magnetic Resonance Imaging Data: The Promise of Data-Driven Computational Approaches.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2022Article
- Spontaneous brain activity, graph metrics, and head motion related to prospective post-traumatic stress disorder trauma-focused therapy response.Frontiers in human neuroscience · 2022Article
- Using deep learning to classify pediatric posttraumatic stress disorder at the individual level.BMC psychiatry · 2021Article
- Defining focal brain stimulation targets for PTSD using neuroimaging.Depression and anxiety · 2021Review
- Machine Learning Methods to Evaluate the Depression Status of Chinese Recruits: A Diagnostic Study.Neuropsychiatric disease and treatment · 2020Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundComorbidity between posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) has been commonly overlooked by studies examining resting-state functional connectivity patterns in PTSD. The current study used a data-driven approach to identify resting-state functional connectivity biomarkers to 1) differentiate individuals with PTSD (with or without MDD) from trauma-exposed healthy control subjects (TEHCs), 2) compare individuals with PTSD alone with those with comorbid PTSD+MDD, and 3) explore the clinical utility of the identified biomarkers by testing their associations with clinical symptoms and treatment response.
methodsResting-state magnetic resonance images were obtained from 51 individuals with PTSD alone, 52 individuals with PTSD+MDD, and 76 TEHCs. Of the 103 individuals with PTSD, 55 were enrolled in prolonged exposure treatment. A support vector machine model was used to identify resting-state functional connectivity biomarkers differentiating individuals with PTSD (with or without MDD) from TEHCs and differentiating individuals with PTSD alone from those with PTSD+MDD. The associations between the identified features and symptomatology were tested with Pearson correlations.
resultsThe support vector machine model achieved 70.6% accuracy in discriminating between individuals with PTSD and TEHCs and achieved 76.7% accuracy in discriminating between individuals with PTSD alone and those with PTSD+MDD for out-of-sample prediction. Within-network connectivity in the executive control network, prefrontal network, and salience network discriminated individuals with PTSD from TEHCs. The basal ganglia network played an important role in differentiating individuals with PTSD alone from those with PTSD+MDD. PTSD scores were inversely correlated with within-executive control network connectivity (p < .001), and executive control network connectivity was positively correlated with treatment response (p < .001).
conclusionsResults suggest that unique brain-based abnormalities differentiate individuals with PTSD from TEHCs, differentiate individuals with PTSD from those with PTSD+MDD, and demonstrate clinical utility in predicting levels of symptomatology and treatment response.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.