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Title: Disturbed hippocampal intra-network in first-episode of drug-naïve major depressive disorder
Authors: Watanabe, Keita
Okamoto, Naomichi
Ueda, Issei
Tesen, Hirofumi
Fujii, Rintaro
Ikenouchi, Atsuko
Yoshimura, Reiji
Kakeda, Shingo
Author's alias: 渡邉, 啓太
Keywords: hippocampal network
structural covariance network
major depression
Issue Date: 2023
Publisher: Oxford University Press (OUP)
Journal title: Brain Communications
Volume: 5
Issue: 1
Thesis number: fcac328
Abstract: Complex networks inside the hippocampus could provide new insights into hippocampal abnormalities in various psychiatric disorders and dementia. However, evaluating intra-networks in the hippocampus using MRI is challenging. Here, we employed a high spatial resolution of conventional structural imaging and independent component analysis to investigate intra-networks structural covariance in the hippocampus. We extracted the intra-networks based on the intrinsic connectivity of each 0.9 mm isotropic voxel to every other voxel using a data-driven approach. With a total volume of 3 cc, the hippocampus contains 4115 voxels for a 0.9 mm isotropic voxel size or 375 voxels for a 2 mm isotropic voxel of high-resolution functional or diffusion tensor imaging. Therefore, the novel method presented in the current study could evaluate the hippocampal intra-networks in detail. Furthermore, we investigated the abnormality of the intra-networks in major depressive disorders. A total of 77 patients with first-episode drug-naïve major depressive disorder and 79 healthy subjects were recruited. The independent component analysis extracted seven intra-networks from hippocampal structural images, which were divided into four bilateral networks and three networks along the longitudinal axis. A significant difference was observed in the bilateral hippocampal tail network between patients with major depressive disorder and healthy subjects. In the logistic regression analysis, two bilateral networks were significant predictors of major depressive disorder, with an accuracy of 78.1%. In conclusion, we present a novel method for evaluating intra-networks in the hippocampus. One advantage of this method is that a detailed network can be estimated using conventional structural imaging. In addition, we found novel bilateral networks in the hippocampus that were disturbed in patients with major depressive disorders, and these bilateral networks could predict major depressive disorders.
Rights: © The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI(Published Version): 10.1093/braincomms/fcac323
PubMed ID: 36601619
Appears in Collections:Journal Articles

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