ArticlePsychoradiology2022
Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder.
Article in Psychoradiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 19 citations in OpenAlex.
- Brain functional network correlates and predictors of the perioperative antidepressant effect of esketamine in breast cancer patients: a double-blind randomized controlled trial using resting-state fMRI and graph theory.Translational psychiatry · 2026Trial
- Characteristics of the amygdala and its subregions in premenstrual syndrome/premenstrual dysphoric disorder patients.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Review
- Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments.eLife · 2024Article
- Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments.bioRxiv : the preprint server for biology · 2024Article
- Neuroimaging study of electroconvulsive therapy for depression.Frontiers in psychiatry · 2023Review
- Transcriptomics and magnetic resonance imaging in major psychiatric disorders.Frontiers in psychiatry · 2023Review
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus Methods: High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups. Results: Compared with HCs, the SCN within the hippocampus Conclusion: Our results provide the first evidence of atypical topologic characteristics within the hippocampus
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