ArticlePsychiatry investigation2019
Promising Neuroimaging Biomarkers in Depression.
Article in Psychiatry investigation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 2 syntheses or guidelines pooled it, 73 citations in OpenAlex.
- Unraveling the mystery of white matter in depression: A translational perspective on recent advances.Brain and behavior · 2022Pooled it
- Resting State Functional Connectivity of Brain With Electroconvulsive Therapy in Depression: Meta-Analysis to Understand Its Mechanisms.Frontiers in human neuroscience · 2020Pooled it
- Major Depressive Disorder and Serum Inflammatory Biomarkers as Predictors of Reward-Processing Dysfunction in an American Indian Sample.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Article
- Molecular, Structural, and Functional Neuroimaging in Major Depression.Advances in experimental medicine and biology · 2026Review
- Generalizable structure-function covariation predictive of antidepressant response revealed by target-oriented multimodal fusion.Nature. Mental health · 2026Article
- Review
- Classify the fNIRS signals of first-episode drug-naive MDD patients with or without suicidal ideation using machine learning.BMC psychiatry · 2025Article
- Characterizing Microglia Morphology in the Frontal Cortex of Pair-Bonded and Unpaired Prairie Voles (International journal of molecular sciences · 2025Article
- Machine Learning-Based Alexithymia Assessment Using Resting-State Default Mode Network Functional Connectivity.Sensors (Basel, Switzerland) · 2025Article
- Deep graph learning of multimodal brain networks defines treatment-predictive signatures in major depression.Molecular psychiatry · 2025Article
- Advances and Challenges in Depression Marker Research.Neuropsychiatric disease and treatment · 2025Review
- Antidepressant Treatment Response Prediction With Early Assessment of Functional Near-Infrared Spectroscopy and Micro-RNA.IEEE journal of translational engineering in health and medicine · 2025Article
- Machine-Learning-Based Depression Detection Model from Electroencephalograph (EEG) Data Obtained by Consumer-Grade EEG Device.Brain sciences · 2024Article
- Optimizing Antidepressant Efficacy: Generalizable Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.medRxiv : the preprint server for health sciences · 2024Article
- From Connectivity to Controllability: Unraveling the Brain Biomarkers of Major Depressive Disorder.Brain sciences · 2024Article
- Functional Near-Infrared Spectroscopy-Based Computer-Aided Diagnosis of Major Depressive Disorder Using Convolutional Neural Network with a New Channel Embedding Layer Considering Inter-Hemispheric Asymmetry in Prefrontal Hemodynamic Responses.Depression and anxiety · 2024Article
- Measuring acute effects of subanesthetic ketamine on cerebrovascular hemodynamics in humans using TD-fNIRS.Scientific reports · 2023Article
- Affective neural circuits and inflammatory markers linked to depression and anxiety symptoms in patients with comorbid obesity.Journal of psychiatric research · 2023Article
- Automatic depression diagnosis through hybrid EEG and near-infrared spectroscopy features using support vector machine.Frontiers in neuroscience · 2023Article
- Alterations in brain iron deposition with progression of late-life depression measured by magnetic resonance imaging (MRI)-based quantitative susceptibility mapping.Quantitative imaging in medicine and surgery · 2022Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
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Abstract
The neuroimaging has been applied in the study of pathophysiology in major depressive disorder (MDD). In this review article, several kinds of methodologies of neuroimaging would be discussed to summarize the promising biomarkers in MDD. For the magnetic resonance imaging (MRI) and magnetoencephalography field, the literature review showed the potentially promising roles of frontal lobes, such as anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). In addition, the limbic regions, such as hippocampus and amygdala, might be the potentially promising biomarkers for MDD. The structures and functions of ACC, DLPFC, OFC, amygdala and hippocampus might be confirmed as the biomarkers for the prediction of antidepressant treatment responses and for the pathophysiology of MDD. The functions of cognitive control and emotion regulation of these regions might be crucial for the establishment of biomarkers. The near-infrared spectroscopy studies demonstrated that blood flow in the frontal lobe, such as the DLPFC and OFC, might be the biomarkers for the field of near-infrared spectroscopy. The electroencephalography also supported the promising role of frontal regions, such as the ACC, DLPFC and OFC in the biomarker exploration, especially for the sleep electroencephalogram to detect biomarkers in MDD. The positron emission tomography (PET) and single-photon emission computed tomography (SPECT) in MDD demonstrated the promising biomarkers for the frontal and limbic regions, such as ACC, DLPFC and amygdala. However, additional findings in brainstem and midbrain were also found in PET and SPECT. The promising neuroimaging biomarkers of MDD seemed focused in the fronto-limbic regions.
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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.