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Identifying the effects of visceral interoception on human brain connectome: A multivariate analysis of covariance of fMRI data

机译:识别内脏受精对人脑结缔组织的影响:fMRI数据协方差的多元分析

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Sources of variations in the neural circuitry of the human brain and interrelationship between intrinsic connectivity networks (ICNs) are still a matter of debate and ongoing research. Here, we applied a multivariate analysis of covariance (MANCOVA) based on high-dimensional independent component analysis (ICA) to identify the effects of interoception and related variables on human brain connectome. Fifteen healthy right-handed subjects (all females, age range 21 - 48 years; mean age = 30.3, SD = 8.7 years) underwent a blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) that included continuous intravesical saline infusion and drainage. The design matrix included the intravesical fullness, subject fullness rating, normalized right and left insula thickness, age, and neuropsychological assessments (Mini-Mental State Exam; MMSE, and Hospital Anxiety and Depression Scale; HADS) as covariates of interest. Univariate tests were also performed with a reduced design matrix (p <; 0.05, corrected for multiple comparisons using false discovery rate) to study the nature and extent of the relationship between these covariates and three ICA outcome measures, namely, the spatial map intensity, frequency spectral power, and functional network connectivity. Results showed significant effects of interoception (intravesical fullness) on spatial map intensity of the salience network (anchored by insula and anterior cingulate cortex) and the frontoparietal central executive network, The left and right insula thickness influenced the spatial map intensity of the subcortical network, and the attention/cognitive and default-mode networks, respectively. The intravesical fullness also showed an effect on the spectral power of the subcortical network. Further investigations of the effect of internal (bodily) sensations on the ICN properties can provide an invaluable tool for understanding the role of interoception in health and illness.
机译:人脑神经回路的变化以及内在连接网络(ICN)之间的相互关系的来源仍然是辩论和正在进行的研究的问题。在这里,我们基于高维独立成分分析(ICA)应用了协方差的多变量分析(MANCOVA),以识别互感和相关变量对人脑连接组的影响。 15位健康的右撇子受试者(所有女性,年龄范围21-48岁;平均年龄= 30.3,SD = 8.7岁)进行了血氧水平依赖性(BOLD)功能磁共振成像(fMRI),包括连续膀胱内输注生理盐水。设计矩阵包括膀胱内充盈度,受试者充盈度等级,标准化的左右绝缘岛厚度,年龄和神经心理学评估(迷你精神状态检查; MMSE,以及医院焦虑和抑郁量表; HADS)作为相关协变量。还使用简化的设计矩阵(p <; 0.05,使用错误发现率对多个比较进行校正)进行单变量检验,以研究这些协变量与三种ICA结果指标(即空间图强度,频谱功率和功能性网络连接。结果显示,套入(膀胱内充盈)对显着网络(由岛突和前扣带回皮层锚定)和额顶中央执行网络的空间图强度具有显着影响,左和右岛间厚度影响着皮质下网络的空间图强度,以及注意力/认知和默认模式网络。膀胱内充满度还显示出对皮层下网络的频谱功率的影响。进一步研究内部(身体)感觉对ICN特性的影响,可以为了解互感在健康和疾病中的作用提供宝贵的工具。

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