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(searched for: A Mini Review on Different Methods of Functional-MRI Data Analysis)
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Karunanithi Rajamanickam
Archives of Internal Medicine Research, Volume 3, pp 44-60; doi:10.26502/aimr.0022

Abstract:
Physiological changes due to blood oxygen level dependent (BOLD) signals from the brain can be probed by functional MRI (fMRI). Especially, several resting state fMRI (rs-fMRI) studies have evidenced the alterations in the default mode network (DMN), which is a fundamental network among the resting state networks (RSNs) with respect to progressing diminished brain function due to various disease conditions such as Alzheimer’s disease (AD). Recently, there are several techniques developed to analyze the rs-fMRI data such as voxel based morphometry (VBM), i.e., seed based analysis, independent component analysis (ICA), clustering algorithm, graph method, neural networks, pattern classification method and statistical parametric mapping. Though these techniques are promising, its application on routine clinical practice is not yet developed. However, it may play a vital role in future for diagnostic and prognosticating various dementia conditions. In this review, fundamentals of rs-fMRI, different data analysis techniques such as seed-based, independent component analysis and graph theory analysis, regional homogeneity analysis and amplitudes of low-frequency fluctuations of the rs-fMRI BOLD signal are discussed.
Sciprofile linkJohn C. Gore, MuWei Li, Yurui Gao, Tung-Lin Wu, Kurt G. Schilling, Yali Huang, Arabinda Mishra, Allen T. Newton, Baxter P. Rogers, Li Min Chen, et al.
Published: 1 November 2019
Magnetic Resonance Imaging, Volume 63, pp 1-11; doi:10.1016/j.mri.2019.07.017

The publisher has not yet granted permission to display this abstract.
Sha Yang, Jingwen Chen, Yuyi Guo, Yuke Teng, Tianyu Liu, Rongtao Ying, Zhaoxuan He, Sciprofile linkJianwei Wu, Shu-Guang Yu, Fang Zeng
Published: 30 August 2019
by BMJ
BMJ Open, Volume 9; doi:10.1136/bmjopen-2019-031089

Abstract:
IntroductionTaiji has been proven to be effective for regulating both the physical and mental state compared with simple aerobic exercise. However, whether the improvement of Taiji for constipation is related to regulate imbalanced brain–gut axis and emotional disorder for functional constipation (FC) remains uncertain. The results of the study will demonstrate the differences in regulation brain–gut balance between Taiji and simply aerobic exercise for patients with FC and provide a potential therapy for clinical treatment of FC, and a new approach for the research of mind–body exercise.Methods and analysisIn this randomised controlled neuroimaging trial, 80 patients with FC will be allocated into two groups: Taiji group and aerobic exercise group. The two groups will receive 10 weeks of Taiji exercise or aerobic exercise, respectively. The stool diary, Cleveland Constipation Score and Patient Assessment of Constipation Symptom, Patient Assessment of Constipation Quality of Life Questionnaire will be used to evaluate the clinical efficacy, the Self-rating Depression Scale, Self-rating Anxiety Scale, Eysenck Personality Questionnaires and Mini-Mental State Examinations will be used to assess the mental state at the baseline, the 5-week intervention and the end of intervention. The 24-hour heart rate variability will be used for assessing the autonomic nervous function, functional MRI and positron emission tomography-CT will be performed for detecting the cerebral functional changes at the baseline and the end of the intervention. The clinical data and multimodal imaging data will be analysed, respectively. Correlation analysis will be conducted to investigate the relationship between cerebral functional changes and symptom improvement.Ethics and disseminationThe procedures have been approved by the Sichuan Regional Ethics Review Committee on Traditional Chinese Medicine (No. 2018KL-047) and conformed to the Declaration of Helsinki. Results will be disseminated through policy briefs, workshops, peer-reviewed publications and conferences.Trial registration numberChinese Clinical Trial Registry (ChiCTR1800019781).
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