Jeong-Hyeon Shin1, Yu Hyun Um2, Chang Uk Lee3, Hyun Kook Lim4, Joon-Kyung Seong5. 1. Department of Bio-convergence Engineering, Korea University, Seoul, Republic of Korea. 2. Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea. 3. Department of Psychiatry, Seoul Saint Mary's Hospital, The Catholic University of Korea, Seoul, Republic of Korea. 4. Department of Psychiatry, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea. Electronic address: drblues@catholic.ac.kr. 5. Department of Bio-convergence Engineering, Korea University, Seoul, Republic of Korea; School of Biomedical Engineering, Korea University, Seoul, Republic of Korea. Electronic address: jkseong@korea.ac.kr.
Abstract
BACKGROUND: Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. METHODS: In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients. Additionally, we investigated the structural sub-networks correlated with several clinical measurements including cognitive impairment and depression severity. RESULTS: We observed that small worldness, clustering coefficients, global and local efficiency, and hub structures in the brains of LLD patients were significantly different from healthy controls. We further found that a sub-network including the anterior cingulate, dorsolateral prefrontal cortex and superior prefrontal cortex is significantly associated with attention control and executive function. The severity of depression was associated with the sub-networks comprising the salience network, including the anterior cingulate and insula. LIMITATIONS: We investigated cortico-cortical connectivity, but omitted the subcortical structures such as the striatum and thalamus. CONCLUSION: We report differences in patterns between several clinical measurements and sub-networks from large-scale and individual-level cortical thickness networks in LLD.
BACKGROUND: Coordinated and pattern-wise changes in large scale gray matter structural networks reflect neural circuitry dysfunction in late life depression (LLD), which in turn is associated with emotional dysregulation and cognitive impairments. However, due to methodological limitations, there have been few attempts made to identify individual-level structural network properties or sub-networks that are involved in important brain functions in LLD. METHODS: In this study, we sought to construct individual-level gray matter structural networks using average cortical thicknesses of several brain areas to investigate the characteristics of the gray matter structural networks in normal controls and LLD patients. Additionally, we investigated the structural sub-networks correlated with several clinical measurements including cognitive impairment and depression severity. RESULTS: We observed that small worldness, clustering coefficients, global and local efficiency, and hub structures in the brains of LLD patients were significantly different from healthy controls. We further found that a sub-network including the anterior cingulate, dorsolateral prefrontal cortex and superior prefrontal cortex is significantly associated with attention control and executive function. The severity of depression was associated with the sub-networks comprising the salience network, including the anterior cingulate and insula. LIMITATIONS: We investigated cortico-cortical connectivity, but omitted the subcortical structures such as the striatum and thalamus. CONCLUSION: We report differences in patterns between several clinical measurements and sub-networks from large-scale and individual-level cortical thickness networks in LLD.
Authors: S J T van Montfort; E van Dellen; C J Stam; A H Ahmad; L J Mentink; C W Kraan; A Zalesky; A J C Slooter Journal: Neuroimage Clin Date: 2019-04-03 Impact factor: 4.881