Browsing by Author "Lee, Tatia Mei-Chun"

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Cognitive Reserve Moderates Effects of White Matter Hyperintensity on Depressive Symptoms and Cognitive Function in Late-Life Depression
(2020-04-08)
Lin, Chemin
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Huang, Chih-Mao
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Fan, Yang-Teng
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Liu, Ho-Ling
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Chen, Yao-Liang
Introduction White matter hyperintensity (WMH) has been regarded as one of the major contributor of the vascular hypothesis of late-life depression (LLD) and cognitive decline in the elderly. On the other hand, cognitive reserve (CR) has long been hypothesized to provide resilience and adaptability against age- and disease-related insults. This study examined the role of CR, using proxy of education, in moderating the association between WMH and clinical LLD expression. Methods A total of 54 elderly diagnosed with major depressive disorder and 38 matched healthy controls participated in this study. They received MRI scanning and a battery of neuropsychological tests. WMH was quantified by an automated segmentation algorithm. Linear regression analyses were conducted separately in the LLD and control groups to examine the effects of WMH, education and their interaction in depression severity and various cognitive domains. Results WMH was significantly and negatively associated with executive function only in the healthy controls. In patients with LLD, we observed a significant interactive effect in education on the association between WMH and depression severity and language domain (category fluency task). Specifically, those with high education showed less depressive symptoms and cognitive decline as WMH increased. Conclusion WMH is associated with lower cognitive function. However, in patients with LLD, high education attenuates the deleterious effect of WMH on mood and cognition. Therefore, CR appears to exert a protective effect on neurocognitive functioning in people with LLD.
Complexity analysis of resting state fMRI signals in depressive patients
(2017-01-01)
Ho, Pei-Shan
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Lin, Chemin
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Chen, Guan-Yen
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Liu, Ho-Ling
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Huang, Chih-Mao
Analysis of brain signal complexity reveals the intrinsic network dynamics and is widely utilized in the investigation of mechanisms in mental disorders. In this study, the complexity of resting-state functional magnetic resonance imaging (fMRI) signals was explored in patients with depression using multiscale entropy (MSE). Thirty-five patients diagnosed with depression and 22 age-and gender-matched healthy controls were considered. The MSE profiles in five brain networks of the two participant groups were evaluated and analyzed. The results showed that depressive patients exhibited higher complexity in the left frontoparietal network than that seen in healthy controls, which is known to be critical for executive control functions. Through this study, the efficacy of MSE in identifying and understanding the mental disorders was also demonstrated.
Decreased Functional Connectivity in Salience Network is Correlated with Dysfunctional Attitude in Late Life Depression
(2015-03-01)
Lin, Chemin
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Huang, Chih-Mao
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Wai, Yau-Yau
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Liu, Ho-Ling
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Lee, Tatia Mei-Chun
Increased brain entropy of resting-state fMRI mediates the relationship between depression severity and mental health-related quality of life in late-life depressed elderly
(2019-05-01)
Lin, Chemin
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Lee, Shwu-Hua
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Huang, Chih-Mao
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Chen, Guan-Yen
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Ho, Pei-Shan
Background: Entropy analysis is a computational method used to quantify the complexity in a system, and loss of brain complexity is hypothesized to be related to mental disorders. Here, we applied entropy analysis to the resting-state functional magnetic resonance imaging (rs-fMRI) signal in subjects with late-life depression (LLD), an illness combined with emotion dysregulation and aging effect. Methods: A total of 35 unremitted depressed elderly and 22 control subjects were recruited. Multiscale entropy (MSE) analysis was performed in the entire brain, 90 automated anatomical labeling-parcellated ROIs, and five resting networks in each study participant. Limitations: Due to ethical concerns, all the participants were under medication during the study. Results: Regionally, subjects with LLD showed decreased entropy only in the right posterior cingulate gyrus but had universally increased entropy in affective processing (putamen and thalamus), sensory, motor, and temporal nodes across different time scales. We also found higher entropy in the left frontoparietal network (FPN), which partially mediated the negative correlation between depression severity and mental components of the quality of life, reflecting the possible neural compensation during depression treatment. Conclusion: MSE provides a novel and complementary approach in rs-fMRI analysis. The temporal-spatial complexity in the resting brain may provide the adaptive variability beneficial for the elderly with depression.
The correlation of perceived quality of life and functional connectivity in patients of late-life depression
(2015-12)
Lee, Shwu-Hua
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Lin, Chemin
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Huang, Chih-Mao
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Liu, Ho-Ling
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Lee, Tatia Mei-Chun