Altered morphometric similarity networks in insomnia disorder
- PMID: 38801538
- DOI: 10.1007/s00429-024-02809-0
Altered morphometric similarity networks in insomnia disorder
Abstract
Previous studies on structural covariance network (SCN) suggested that patients with insomnia disorder (ID) show abnormal structural connectivity, primarily affecting the somatomotor network (SMN) and default mode network (DMN). However, evaluating a single structural index in SCN can only reveal direct covariance relationship between two brain regions, failing to uncover synergistic changes in multiple structural features. To cover this research gap, the present study utilized novel morphometric similarity networks (MSN) to examine the morphometric similarity between cortical areas in terms of multiple sMRI parameters measured at each area. With seven T1-weighted imaging morphometric features from the Desikan-Killiany atlas, individual MSN was constructed for patients with ID (N = 87) and healthy control groups (HCs, N = 84). Two-sample t-test revealed differences in MSN between patients with ID and HCs. Correlation analyses examined associations between MSNs and sleep quality, insomnia symptom severity, and depressive symptoms severity in patients with ID. The right paracentral lobule (PCL) exhibited decreased morphometric similarity in patients with ID compared to HCs, mainly manifested by its de-differentiation (meaning loss of distinctiveness) with the SMN, DMN, and ventral attention network (VAN), as well as its decoupling with the visual network (VN). Greater PCL-based de-differentiation correlated with less severe insomnia and fewer depressive symptoms in the patients group. Additionally, patients with less depressive symptoms showed greater PCL de-differentiation from the SMN. As an important pilot step in revealing the underlying morphometric similarity alterations in insomnia disorder, the present study identified the right PCL as a hub region that is de-differentiated with other high-order networks. Our study also revealed that MSN has an important potential to capture clinical significance related to insomnia disorder.
Keywords: Default mode network; Insomnia; Morphometric similarity networks; Paracentral lobule; Somatomotor network.
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
References
-
- Alexander-Bloch AF, Vértes PE, Stidd R, Lalonde F, Clasen L, Rapoport J, Giedd J, Bullmore ET, Gogtay N (2013) The anatomical distance of functional connections predicts brain network topology in health and schizophrenia. Cereb Cortex 23(1):127–138. https://doi.org/10.1093/cercor/bhr388 - DOI - PubMed
-
- Allan PG, Briggs RG, Conner AK, O’Neal CM, Bonney PA, Maxwell BD, Baker CM, Burks JD, Sali G, Glenn CA (2020) Parcellation-based tractographic modeling of the ventral attention network. J Neurol Sci 408:116548. https://doi.org/10.1016/j.jns.2019.116548 - DOI - PubMed
-
- Bai Y, Tan J, Liu X, Cui X, Li D, Yin H (2022) Resting-state functional connectivity of the sensory/somatomotor network associated with sleep quality: evidence from 202 young male samples. Brain Imaging Behav 16(4):1832–1841. https://doi.org/10.1007/s11682-022-00654-5 - DOI - PubMed - PMC
-
- Bastien CH, Vallières A, Morin CM (2001) Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med 2(4):297–307. https://doi.org/10.1016/s1389-9457(00)00065-4 - DOI - PubMed
-
- Beck AT, Beck RW (1972) Screening depressed patients in family practice: a rapid technic. Postgrad Med 52(6):81–85. https://doi.org/10.1080/00325481.1972.11713319 - DOI - PubMed
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Medical
Research Materials
Miscellaneous