Depression has become a major threat to human health, and researchers around the world are actively engaged in research on depression. In order to promote closer research, the study of the global depression knowledge map is significant. This study aims to map the knowledge map of depression research and show the current research distribution, hotspots, frontiers, and trends in the field of depression research, providing researchers with worthwhile information and ideas. Based on the Web of Science core collection of depression research from 2004 to 2019, this study systematically analyzed the country, journal, category, author, institution, cited article, and keyword aspects using bibliometric and data visualization methods. A relationship network of depression research was established, highlighting the highly influential countries, journals, categories, authors, institutions, cited articles, and keywords in this research field. The study identifies great research potential in the field of depression, provides scientific guidance for researchers to find potential collaborations through collaboration networks and coexistence networks, and systematically and accurately presents the hotspots, frontiers, and shortcomings of depression research through the knowledge map of global research on depression with the help of information analysis and fusion methods, which provides valuable information for researchers and institutions to determine meaningful research directions.

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Evolution and Emerging Trends in Depression Research From 2004 to 2019: A Literature Visualization Analysis.

Pre-partum HRV as a predictor of postpartum depression: The potential use of a smartphone application for physiological recordings.

The subgenual anterior cingulate cortex (sgACC) appears to play a central role in the pathophysiology of major depressive disorder (MDD). To wit, its functional interactive profile with the left dorsal lateral prefrontal cortex (DLPFC) has been shown to be related to treatment outcomes with transcranial magnetic stimulation (TMS) treatment outcomes. Nevertheless, previous research on sgACC functional connectivity (FC) in MDD has yielded inconsistent results, partly due to small sample sizes and limited statistical power of prior work. Here, leveraging a large multi-site sample (1660 MDD patients vs. 1341 healthy controls) from Phase II of the Depression Imaging REsearch ConsorTium (DIRECT), we systematically delineated case-control difference maps of sgACC FC and examined their clinical relevance to previously identified TMS targets. We also investigated case-control FC difference maps of left DLPFC sub-fields. In MDD patients we found significantly increased FC between sgACC and thalamus and reduced FC to a broad array of brain regions, including somatosensory area, occipital lobe, medial and lateral temporal lobe, and insular cortex, when global signal regression (GSR) was not implemented. Intriguingly, we found enhanced left DLPFC-sgACC FC in MDD patients when GSR was performed. We leveraged an prior independent sample to explore the possible relationship between the case-control differences regarding sgACC’s FC profiles and the treatment out comes of TMS. In sites in which open TMS treatment was administered, case-control differences in sgACC FC, with GSR, were related to clinical improvement. Next we tested whether the position of peak of the FC maps (previously identified TMS target) could be altered in MDD patients as compred with healthy controls (HC)s. We found the optimized TMS target differed in MDD patients. Several DLPFC sub-fields yielded case-control differences in whole-brain FC maps. In summary, we reliably delineated MDD-related abnormalities of sgACC FC profiles in a large sample. GSR was essential in applying case-control difference maps to identify optimized TMS targets. Our results highlight the functional heterogeneity of the left DLPFC and of precise TMS targets therein.

The Complexity of Functional Connectivity Profiles of the Subgenual Anterior Cingulate Cortex and Dorsal Lateral Prefrontal Cortex in Major Depressive Disorder: a DIRECT Consortium Study

Although treatment resistance to antidepressant pharmacotherapy is quite common, the phenomenon of refractory major depressive disorder (rMDD) is not well understood. Nevertheless, the metabolic activity of the subgenual anterior cingulate cortex (sgACC) has been put forward as a possible metabolic biomarker of clinical prediction and response, albeit sgACC lateralization differences in functional connectivity have not yet been extensively examined. Also not in the refractory depressed state. To examine sgACC lateralization differences in metabolic connectivity, we recruited 43 right-handed antidepressant-free unipolar melancholic rMDD patients and 32 right-handed healthy controls to participate in this 18FDG PET study and developed a searchlight-based interregional covariance connectivity approach. Compared to non-depressed individuals, sgACC covariance analysis showed stronger metabolic connections with frontolimbic brain regions known to be affected in the depressed state. Furthermore, whereas the left sgACC showed stronger metabolic connections with ventromedial prefrontal cortical regions, implicated in anhedonia, suicidal ideation, and self-referential processes, the right sgACC showed significantly stronger metabolic connections with posterior hippocampal and cerebellar regions, respectively specialized in memory and social processing. Overall, our results substantiate earlier research that the sgACC is a metabolic key player when clinically depressed and that distinct lateralized sgACC metabolic connectivity patterns are present.

Lateralized subgenual ACC metabolic connectivity patterns in refractory melancholic depression: does it matter?

Frequency-resolved connectome alterations in major depressive disorder: A multisite resting fMRI study.

Although accumulating evidence has been elucidating the neuronal basis of refractory/nonrefractory major depressive disorder (rMDD/nrMDD), the results are inconsistent, and little is known about the distinct neural mechanisms underlying rMDD. Here, we explored the convergent/divergent brain networks between first-episode MDD subtypes using the resting-state functional connectivity (RSFC) approach. In total, 33 healthy controls (HCs), 31 first-episode rMDD patients and 33 first-episode nrMDD patients were enrolled and underwent MRI scanning. The left subgenual anterior cingulate cortex (sgACC) was selected as the seed region, and RSFC was employed to evaluate associations between the seed and other regions in the whole brain. Both MDD subtypes exhibited convergent left sgACC-based neural networks, including increased RSFC with the dorsal prefrontal cortex (DPFC) and decreased RSFC with the bilateral orbitofrontal cortex (OFC) and right parahippocampus. rMDD patients exhibited increased left sgACC-OFC RSFC relative to nrMDD patients, and RSFC with the bilateral OFC in rMDD patients was negatively correlated with HAMD scores. These findings confirmed our speculation that convergent and divergent neural networks exist between rMDD and nrMDD. Cortical-limbic circuits, especially the prefrontal-limbic circuit, may serve as the convergent dysfunctional neural circuitry in MDD subtypes. As an important biomarker, a unique OFC-sgACC circuit abnormality was identified in rMDD patients, which might help elucidate the underlying mechanism regarding treatment responses in rMDD patients.

Functional connectivity patterns of the subgenual anterior cingulate cortex in first-episode refractory major depressive disorder.

Regional cerebral activity abnormality in pregnant women with antenatal depression.

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Functional connectivity patterns of the subgenual anterior cingulate cortex in first-episode refractory major depressive disorder.

Regional cerebral activity abnormality in pregnant women with antenatal depression.