Dataset Information

Differing Spontaneous Brain Activity in Healthy Adults with Two Different Body Constitutions: A Resting-State Functional Magnetic Resonance Imaging Study.

ABSTRACT: Traditional Chinese medicine (TCM) practitioners assess body constitution (BC) as a treatment basis for maintaining body homeostasis. We investigated patterns in spontaneous brain activity in different BC groups using resting-state functional magnetic resonance imaging (rsfMRI) and determined the relationship between these patterns and quality of life (QOL). Thirty-two healthy individuals divided into two groups (body constitution questionnaire (BCQ)-gentleness [BCQ-G] and BCQ-deficiency [BCQ-D]) based on the body constitution questionnaire (BCQ) underwent rsfMRI to analyze regional homogeneity (ReHo) and the amplitude of low-frequency fluctuation (ALFF). The World Health Organization Quality of Life Instruments (brief edition) scale was used to evaluate the QOL. The BCQ-G group (n = 18) had significantly greater ReHo values in the right postcentral gyrus and lower ALFF values in the brainstem than the BCQ-D group (n = 14). In the BCQ-D group, decreased ReHo of the postcentral gyrus correlated with better physiological functioning; increased ALFF in the brainstem correlated with poor QOL. BCQ-subgroup analysis revealed a nonsignificant correlation between ReHo and Yang deficiency/phlegm and stasis (Phl & STA). Nonetheless, the BCQ-D group showed a positive correlation between ALFF and Phl & STA in the parahippocampus. This study identified differences between BCQ-G and BCQ-D types of healthy adults based on the rsfMRI analysis. The different BCQ types with varied brain endophenotypes may elucidate individualized TCM treatment strategies.

SUBMITTER: Liu CH

PROVIDER: S-EPMC6678373 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Differing Spontaneous Brain Activity in Healthy Adults with Two Different Body Constitutions: A Resting-State Functional Magnetic Resonance Imaging Study.

Liu Ching-Hsiung CH Liu Ching-Hsiung CH Kung Yen-Ying YY Yeh Tzu-Chen TC Hsu Pei-Shan PS Yang Ching-Ju CJ Cheng Chou-Ming CM Lin Hong-Chun HC Yang Jen-Lin JL Wu Ta-Peng TP Chang Ching-Mao CM Hsieh Jen-Chuen JC Chen Fang-Pey FP

Journal of clinical medicine 20190630 7

Traditional Chinese medicine (TCM) practitioners assess body constitution (BC) as a treatment basis for maintaining body homeostasis. We investigated patterns in spontaneous brain activity in different BC groups using resting-state functional magnetic resonance imaging (rsfMRI) and determined the relationship between these patterns and quality of life (QOL). Thirty-two healthy individuals divided into two groups (body constitution questionnaire (BCQ)-gentleness [BCQ-G] and BCQ-deficiency [BCQ-D] ...[more]

PMID: 31261997

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Project description:Introduction: Functional movement disorder (FMD) is a type of functional neurological disorder characterized by abnormal movements that patients do not perceive as self-generated. Prior imaging studies show a complex pattern of altered activity, linking regions of the brain involved in emotional responses, motor control, and agency. This study aimed to better characterize these relationships by building a classifier using a support vector machine to accurately distinguish between 61 FMD patients and 59 healthy controls using features derived from resting-state functional magnetic resonance imaging. Materials and Methods: First, we selected 66 seed regions based on prior related studies, then we calculated the full correlation matrix between them before performing recursive feature elimination to winnow the feature set to the most predictive features and building the classifier. Results: We identified 29 features of interest that were highly predictive of the FMD condition, classifying patients and controls with 80% accuracy. Several key features included regions in the right sensorimotor cortex, left dorsolateral prefrontal cortex, left cerebellum, and left posterior insula. Conclusions: The features selected by the model highlight the importance of the interconnected relationship between areas associated with emotion, reward, and sensorimotor integration, potentially mediating communication between regions associated with motor function, attention, and executive function. Exploratory machine learning was able to identify this distinctive abnormal pattern, suggesting that alterations in functional linkages between these regions may be a consistent feature of the condition in many FMD patients. Clinical-Trials.gov ID: NCT00500994 Impact statement Our research presents novel results that further elucidate the pathophysiology of functional movement disorder (FMD) with a machine learning model that classifies FMD and healthy controls correctly 80% of the time. Herein, we demonstrate how known differences in resting-state functional magnetic resonance imaging connectivity in FMD patients can be leveraged to better understand the complex pattern of neural changes in these patients. Knowing that there are measurable predictable differences in brain activity in patients with FMD may help both clinicians and patients conceptualize and better understand the illness at the point of diagnosis and during treatment. Our methods demonstrate how an effective combination of machine learning and qualitative approaches to analyzing functional brain connectivity can enhance our understanding of abnormal patterns of brain activity in FMD patients.

Dataset Information

Differing Spontaneous Brain Activity in Healthy Adults with Two Different Body Constitutions: A Resting-State Functional Magnetic Resonance Imaging Study.

Publications

Differing Spontaneous Brain Activity in Healthy Adults with Two Different Body Constitutions: A Resting-State Functional Magnetic Resonance Imaging Study.

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