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. 2020 Jul 21:11:1784.
doi: 10.3389/fpsyg.2020.01784. eCollection 2020.

Aberrant Resting-State Brain Function in Adolescent Depression

Affiliations

Aberrant Resting-State Brain Function in Adolescent Depression

Ning Mao et al. Front Psychol. .

Abstract

To explore the changes of brain function and conduct clinical differential diagnosis based on support vector machine (SVM) in adolescent patients with depression. A total of 24 adolescent patients with depression according to CCMD-3 and DSM-5 and 23 gender, education level, body mass index, and age matched healthy controls were assessed with 17-item Hamilton Depression Rating Scale (HAMD). HAMD scores were requested from ≥17 of patients. Three-dimensional T1 and resting-state functional magnetic resonance imaging data were acquired from all participants. The data were analyzed using SPM 12 and REST1.8. Two-sample t-test was conducted to compare regional homogeneity (ReHo) values among the groups of participants. Finally, based on SVM classification, clinical differential diagnosis of the patients was carried out. The receiver operator characteristic (ROC) curve were used to confirm the performance of the SVM model. An increase ReHo values were observed in the lingual gyrus, middle occipital gyrus, postcentral gyrus, and precentral gyrus, whereas a decrease in ReHo was found in vermis compared with the control group. The SVM model showed good performance in classification prediction of adolescent depression, with an area under curve (AUC) of 0.778 [95% confidence interval (CI), 0.661-0.797]. The changes in the spontaneous neural activity of these regions may play an important role in the neuropathological mechanism of adolescent depression and may provide promising markers for clinical evaluation.

Keywords: adolescent; depression; magnetic resonance imaging; regional homogeneity; resting state.

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Figures

FIGURE 1
FIGURE 1
Statistical maps showing ReHo differences between patients and control group. Blue denotes decreased ReHo, and the color bar indicates the T-values from two-sample t-tests.
FIGURE 2
FIGURE 2
The ROC curve of SVM model. The SVM model showed good performance for the classification prediction of adolescent depression, with an AUC of 0.778.

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