NDLI: Association of specific frequency bands of functional MRI signal oscillations with motor symptoms and depression in Parkinson’s disease

Content Provider	PubMed Central
Author	Song, Xiaopeng Xiao, Hu Zhou, Shuqin Xu, Yuanyuan Zhang, Yi Yuan, Yonggui Liu, Yijun Zhu, Huaiqiu Liu, Weiguo Gao, Jia-hong
Copyright Year	2015
Abstract	A novel empirical mode decomposition method was adopted to investigate the dissociative or interactive neural impact of depression and motor impairments in Parkinson’s disease (PD). Resting-state fMRI data of 59 PD subjects were first decomposed into characteristic frequency bands, and the main effects of motor severity and depression and their interaction on the energy of blood-oxygen-level-dependent signal oscillation in specific frequency bands were then evaluated. The results show that the severity of motor symptoms is negatively correlated with the energy in the frequency band of 0.10–0.25 Hz in the bilateral thalamus, but positively correlated with 0.01–0.027 Hz band energy in the bilateral postcentral gyrus. The severity of depression, on the other hand, is positively correlated with the energy of 0.10–0.25 Hz but negatively with 0.01–0.027 Hz in the bilateral subgenual gyrus. Notably, the interaction between motor and depressive symptoms is negatively correlated with the energy of 0.10–0.25 Hz in the substantia nigra, hippocampus, inferior orbitofrontal cortex, and temporoparietal junction, but positively correlated with 0.02–0.05 Hz in the same regions. These findings indicate unique associations of fMRI band signals with motor and depressive symptoms in PD in specific brain regions, which may underscore the neural impact of the comorbidity and the differentiation between the two PD-related disorders.
Related Links	http://dx.doi.org/10.1038/srep16376
Starting Page	16376
File Format	PDF
ISSN	20452322
e-ISSN	20452322
Journal	Scientific Reports
Volume Number	5
Language	English
Publisher	Nature Publishing Group
Publisher Date	2015-11-17
Access Restriction	Open
Rights Holder	Nature Publishing Group
Subject Keyword	Science and technology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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